KPLC Distribution

Kenya Distribution Master Plan

The Kenya Power & Lighting Company Limited

Final Report

Volume I

Distribution Master Plan Report

April 2013

Distribution Master Plan Study

Final Report

Volume I

Distribution Master Plan Report

April 2013

Prepared for The Kenya Power & Lighting Company Limited

Prepared by

Parsons Brinckerhoff

www.pbworld.co.uk

Kenya Distribution Master Plan

Overall Study Contents

Volume I: Distribution Master Plan Report Volume II: Design Manual

Volume III: Environmental Impact Assessment Scoping Report

Document History and Status Report Issue Date of Issue Prepared By: Checked By: Approved By:

2 4 April 2013

M Fraser O. Nanka-Bruce A Topari G Vukojevic M Safranek L Veitch J Kuchimanchi B Brewin E Tyldesley

M. Fraser K. Jackson

1 6 February 2013

0 19 November 2012

Report Title : Distribution Master Plan Report Report Status : Final Job No : 3511648A Date : April 2013 Prepared by : Authors listed below Checked by : M. Fraser Approved by : K. Jackson

Distribution Master Plan Report Prepared for KPLC Final Report

CONTENTS

LIST OF ABBREVIATIONS EXECUTIVE SUMMARY

1 INTRODUCTION .................................................................................................... 1.1 1.1 Key Drivers ............................................................................................................ 1.1 1.2 Study Documents ................................................................................................... 1.1

2 BACKGROUND ..................................................................................................... 2.1 2.1 Electricity Sector .................................................................................................... 2.1 2.2 Distribution Network Configuration.......................................................................... 2.2 2.3 On-going Projects .................................................................................................. 2.5 2.4 Network Planning Issues ........................................................................................ 2.5

3 MASTER PLAN APPROACH ................................................................................ 3.1 3.1 Overview ................................................................................................................ 3.1 3.2 Counterpart Team .................................................................................................. 3.2 3.3 Data Gathering ....................................................................................................... 3.2 3.4 Software Selection ................................................................................................. 3.2 3.5 Network Modelling and Assessment of Existing Networks....................................... 3.2 3.6 County Visits .......................................................................................................... 3.3 3.7 Demand Forecasting .............................................................................................. 3.3 3.8 Short-medium term planning .................................................................................. 3.3 3.9 Long term planning ................................................................................................ 3.3

4 DEMAND FORECAST ........................................................................................... 4.1 4.1 Background ............................................................................................................ 4.1 4.2 LCPDP Demand Forecast ...................................................................................... 4.1 4.3 Deriving the LCPDP Demand Forecast ................................................................... 4.4 4.4 County Statistics .................................................................................................... 4.7 4.5 County Demand Forecast ..................................................................................... 4.14 4.6 Disaggregation to Substation Level ...................................................................... 4.17

5 PLANNING CRITERIA AND GUIDELINES ............................................................ 5.1 5.1 Introduction ............................................................................................................ 5.1 5.2 Planning Criteria..................................................................................................... 5.1 5.3 Planning Guidelines ............................................................................................... 5.5 5.4 Planning Recommendations ................................................................................. 5.15


6 DESIGN STANDARDS .......................................................................................... 6.1 6.1 Introduction ............................................................................................................ 6.1 6.2 DSGM Review ....................................................................................................... 6.1 6.3 Draft Design Manual............................................................................................... 6.1 6.4 Implementation of Design Manual .......................................................................... 6.3 6.5 Prospective Additional Scope ................................................................................. 6.4

7 NETWORK DATA AND MODELLING ................................................................... 7.1 7.1 Network Data and Assumptions.............................................................................. 7.1 7.2 Network Models ..................................................................................................... 7.1

8 ASSESSMENT OF EXISTING NETWORKS .......................................................... 8.1 8.1 General .................................................................................................................. 8.1 8.2 Nairobi Region ....................................................................................................... 8.1 8.3 Mount Kenya Region .............................................................................................. 8.6 8.4 Coast Region ......................................................................................................... 8.9 8.5 Western Region ................................................................................................... 8.11

9 SHORT-MEDIUM TERM PLAN.............................................................................. 9.1 9.1 Basis for Expansion Plan ........................................................................................ 9.1 9.2 Nairobi Region ....................................................................................................... 9.1 9.3 Mount Kenya Region ............................................................................................ 9.10 9.4 Coast Region ....................................................................................................... 9.19 9.5 Western Region ................................................................................................... 9.27

10 ENVIRONMENTAL IMPACT ASSESSMENT SCOPING STUDIES ..................... 10.1 10.1 Background .......................................................................................................... 10.1 10.2 Purpose of this Scoping Report and Approach to the Scoping Study..................... 10.1 10.3 Distribution Master Plan Project Activities ............................................................. 10.2 10.4 Consultation ......................................................................................................... 10.2 10.5 Likely Environmental and Social Impacts of Distribution Master Plan Projects ....... 10.3 10.6 Mitigation and Monitoring ..................................................................................... 10.4 10.7 Environmental and Social Capacity Building ......................................................... 10.4

11 INTERCONNECTION OF OFF-GRID AREAS ..................................................... 11.1 11.1 Off-Grid Power Plants .......................................................................................... 11.1 11.2 Relevant Transmission Network Developments .................................................... 11.3 11.3 Assessment of Grid Connection ........................................................................... 11.3 11.4 Summary of results .............................................................................................. 11.8

12 LONG TERM PLAN AND INVESTMENT PLAN .................................................. 12.1


12.1 Introduction .......................................................................................................... 12.1 12.2 Generic Models .................................................................................................... 12.1 12.3 Investment Plan ................................................................................................... 12.7

13 CONCLUSIONS AND RECOMMENDATIONS .................................................... 13.1 13.1 Conclusions ......................................................................................................... 13.1 13.2 Recommendations ............................................................................................... 13.3

APPENDICES APPENDIX A PLANNING GUIDELINES

APPENDIX B NAIROBI REGION NETWORK STUDIES

APPENDIX C MT. KENYA REGION NETWORK STUDIES

APPENDIX D COAST REGION NETWORK STUDIES

APPENDIX E WESTERN REGION NETWORK STUDIES

APPENDIX F COMMITTED AND PROPOSED PROJECTS


LIST OF ABBREVIATIONS

ADMD After Diversity Maximum Demand

AVR Automatic Voltage Regulator

BBHs Branch Business Heads

BSP Bulk Supply Point

CAA Civil Aviation Authority

CT Current Transformer

DSGM Distribution Standards and Guidelines Manual

EIA Environmental Impact Assessment

EMCA Environmental Management and Coordination Act 1999

EN European Standards

ERC Energy Regulatory Commission

EIA Environmental Impact Assessment

ESMP Environmental & Social Management Plan

ESRP Energy Sector Recovery Project

FDB Facilities Database

GDC Geothermal Development Company

GDP Gross Domestic Product

GIS Geographic Information System

GWh Gigawatt-hour

HH Howard Humphreys

HV High Voltage

Hz Hertz

ICT Information and Communication Technology

IEC International Electro-technical Commission

IPP Independent Power Producer

KEEP Kenya Electricity Expansion Project

KenGen Kenya Generating Company

KeNHA Kenya National Highways Authority

KenInvest Kenya Investment Authority

KEPSA Kenya Private Sector Alliance

KeRRA Kenya Rural Roads Authority

KETRACO Kenya Electricity Transmission Co. Ltd

KFS Kenya Forestry Service


KPLC Kenya Power and Light Company (Kenya Power)

KNBS Kenya National Bureau of Statistics

KSh Kenyan Shillings

KURA Kenya Urban Roads Authority

kV Kilovolt

kW Kilo-Watt

kWh Kilo-Watt-hour

KWS Kenya Wildlife Service

LCPDP Least Cost Power Development Plan

LRMC Long Run Marginal Cost

LV Low Voltage

MoE Ministry of Energy

MoK Museums of Kenya

MV Medium Voltage

MVA Mega-Volt Ampere

MW Mega-Watt

NCC National Control Centre

NEMA National Environmental Management Authority

NOPs Normally Open Points

OFAF Oil Forced, Air Forced

O&M Operation and Maintenance

OHL Overhead Lines

PAP Project Affected Person

PB Parsons Brinckerhoff

Pf Power Factor

PPA Power Purchase Agreement

PU Per Unit

PV Photovoltaic

RCC Regional Control Centre

REA Rural Electrification Authority

REM Rural Electrification Masterplan

SAIDI System Average Interruption Duration Index

SAIFI System Average Interruption Frequency Index

SCADA Supervisory Control and Data Acquisition

SHE Safety, Health and Environment


SVC Static VAR Compensator

TANESCO Tanzania Electric Supply Company

ToR Terms of Reference

UETCL Uganda Electricity Transmission Company

USD United States Dollar

VA Volt-Ampere

VT Voltage Transformer

EXECUTIVE SUMMARY

DISTRIBUTION MASTER PLAN

EXECUTIVE SUMMARY

Distribution Master Plan Study Prepared for KPLC Final Report

EXECUTIVE SUMMARY

Objectives

Parsons Brinckerhoff (PB) was appointed by The Kenya Power & Lighting Company Limited (KPLC) to conduct a

Distribution Master Plan Study to address the countrys distribution requirements up to 2030.

The main objectives of the study were to;

x conduct a detailed assessment of KPLCs distribution system requirements over the 2012-2030 planning period and develop a Distribution Master Plan and

x undertake an environmental scoping study for the investments recommended in the short-medium term (3-5 years).

Investment Requirements

The study indicates the need for the following investment in distribution infrastructure:

A. Short-medium term investment

1. Proposed 66 kV and 33 kV investment

The study identifies the need for approximately 300, 66 kV and 33 kV distribution projects beyond those that are

already committed or under construction, for completion over the 2013-2017 period. The estimated investment

required for the 66 kV and 33 kV projects over the 2013 207 period is $ 149 million as indicated in Table E-1-1.

Details of the proposed projects are provided in the report.

Table E-1-1: Proposed 66 kV and 33 kV investment in short-medium term (USD 000)

2. Proposed Bulk Supply Point (BSP) investment

Table E-1-2 shows an estimated investment requirement in new BSPs and reinforcement of existing BSPs

(beyond the committed BSP projects) of $107 million over the 2013-2017 period. This is for the BSP substations

only and does not include the cost of transmission lines required to connect the new BSPs to the grid.

Table E-1-2: Proposed BSP investment in short-medium term (USD 000)

Substation/Feeder Project Status 2013 2014 2015 2016 2017 Grand Total

Feeders (66 kV and 33 kV) Proposed 3,110 9,698 20,269 17,714 7,107 57,899

Primary substations Proposed 5,454 15,983 21,211 28,004 20,640 91,291

Grand Total 8,564 25,681 41,480 45,718 27,746 149,189

Substation/Feeder Project Status 2014 2015 2016 2017 Grand Total

Bulk Supply Points Proposed 16,728 35,717 39,980 15,002 107,428


EXECUTIVE SUMMARY


3. Estimated 11 kV and LV investment

The above figures do not include investment at the 11 kV and LV levels. Due to the scale of these networks it

was not practical to model them in their entirety. The estimated investment costs at these voltage levels were

calculated based on representative 11 kV and LV networks. The estimated level of investment is shown in Table

E-1-3. and is considerably more than that required at 66 kV and 33 kV. This difference is primarily due to the

scale of the infrastructure at these voltage levels. The cost of all 33/0.433 kV and 11/0.433 kV distribution

transformers is included within these figures.

Table E-1-3: Estimated 11 kV and LV investment in short-medium term (USD million)

Equipment 2013 2014 2015 2016 2017

11 kV and LV networks (including all

distribution transformers)

174 406 401 277 335

B. Long-term investment

The estimated long term annual investment in all distribution infrastructure from 66 kV to LV is indicated in Table

E-1-4.

Table E-1-4: Estimated long term investment - 66 kV LV (USD million)

2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

407 420 496 538 604 676 791 893 992 1,119 1,272 1,437 1,611

Key Drivers

Development of the power sector in Kenya is underpinned by Vision 2030, which is Kenyas development

blueprint covering the period 2008 to 2030. The objective of Vision 2030 is to help transform Kenya into a

middle-income country providing a high quality of life to all of its citizens by the year 2030. It identifies energy

and electricity as a key element of Kenyas sustained economic growth and transformation.

The power sector in Kenya requires high levels of investment to ensure that the rapidly growing demand is

adequately met. Major investments are being made in generation and transmission, however for benefits to be

realised, similar levels of investment are required in the distribution sub-sector. It is essential that this investment

is carefully planned to ensure efficient use of scarce resources.

Under the new constitution, power will be devolved to each of the forty seven counties. This is expected to result

in more equitable sharing of resources across the country, with increased levels of investment particularly in the

more remote counties that have historically been neglected. There exist wide ranging levels of household

electrification across the country, from around 75 % of households in Nairobi County to less than 2 % of


EXECUTIVE SUMMARY


households in Tana River County1. Electrification levels are increasing across the country and following

devolution, it is expected that the rate of increase will be highest in those counties that are currently poorly served

with electricity infrastructure.

The Distribution Master Plan includes a forecast of electricity demand for each of the counties and identifies the

distribution infrastructure required to meet that demand, whilst achieving acceptable levels of power quality and

reliability, based on well established principles of least-cost planning.

Approach

Throughout the period of the Master Plan Study, there was close collaboration between the PB team and the

KPLC counterpart team. The process as shown in Figure E.1 began with a detailed data gathering exercise at

central, regional and sub-regional level.

Figure E.1: Distribution Master Plan Process

The scope of the study included provision of suitable software to conduct the detailed network analysis and to

provide an ongoing tool for KPLC to use in the future. Selection and procurement of the software was conducted

in parallel with data gathering.

This was followed by network modelling and assessment of existing network issues and constraints, leading to

short-medium term planning studies covering the period from 2012-2017. The network modelling and analysis

for the various KPLC regions was conducted in parallel in order to minimise the time required for these detailed,

data-intensive tasks.

1 Based on the 2009 Kenya Population and Housing Census Report

Data gathering at central and regional level

Software selection Network modelling Assess existingNetwork issuesShort-medium term planning studies

Planning and designguidelines

Genericnetworks

Long term plan

Detailed interaction with counterparts

Demand forecasting

County level meetings (in each of the 47 countiesHosted by KPLC BBHs)

ESIA scopingstudies

Localised technicalissues

DISTRIBUTIONMASTER PLAN

3 week intensive training course in UKIncluding visits to industry

Investment plan

Off-gridassessment


EXECUTIVE SUMMARY


Apart from the network data and models, key inputs to the planning studies were; the demand forecast and the

planning and design guidelines.

Long term planning was based on the development of generic networks to represent the different typical network

topologies, i.e. urban, rural, Nairobi and off-grid configurations. These were used along with the county level

demand forecast to determine the longer term investment requirements.

A key aspect of the Master Plan study was consultation at a county level. This was used to inform the

Environmental Impact Assessment scoping studies and also provided valuable insights into technical issues at a

local level.

The Master Plan study draws together the key aspects of the assignment which are briefly described below.

Counterpart Team

An important factor leading to the successful completion of the Master Plan Study was the appointment by KPLC

of a dedicated team of knowledgeable counterparts. The counterpart team was pivotal during the data gathering

stage and provided invaluable local knowledge during development of the short-medium term plans.

The assignment included an intensive three-week training course in the UK for the counterparts. This covered

most of the key aspects of the study and included hands-on training in the use of the network planning software.

Data Gathering

Data gathering was conducted at central, regional and sub-regional level. County level meetings were also held

as described below.

Initial data collection was conducted at KPLCs central offices in Nairobi. This included centrally stored network

data and diagrams, relevant reports, branch sales data and relevant information from Kenya National Bureau of

Statistics (KNBS). The initial data gathering stage was followed in April with data gathering at the regional and

sub-regional level. This was conducted in three teams, each comprising members from the PB and KPLC

counterpart study teams. The teams covered the various KPLC regions as follows:

x Nairobi Region

x Coast and Mt. Kenya Regions

x Western Region

The data obtained in the regions and sub-regions was used to try to complete the many gaps in the data obtained

initially from the central offices. Most of the remaining gaps were resolved through collaboration with the KPLC

counterpart team, thereby minimising the number of assumptions that needed to be made with respect to the

network models.

Software Selection

The scope of the study included the procurement of a suitable software package, both for conducting the network

analysis during the study and for handing over to KPLC at the end of the study. Two potential software packages

were assessed and following a presentation by PB, KPLC chose NEPLAN.


EXECUTIVE SUMMARY


Network Modelling and Assessment of Existing Networks

The next stage was to develop detailed NEPLAN models of the 33 kV and 66 kV networks. These were initially

used to assess the performance of the existing networks in each of the four KPLC regions and to identify specific

network constraints. Representative 11 kV feeders were also modelled and assessed using NEPLAN.

County Visits

Stakeholder meetings were held within each of the 47 counties, in order to gather data for the EIA scoping study

and to understand key technical issues at a county level. County meetings were initially held in three pilot

counties. Following the pilot meetings, the agenda was refined and used as the basis for the remaining

meetings.

Demand Forecasting

The demand forecast contained within the Least Cost Power Development Plan (LCPDP) dated March 2011 was

used for the study. This was disaggregated to county level using a process that is described in detail in this

report. County demand growth rates were applied to the respective substations to determine substation

demands for the network studies. County growth rates were also used to determine investment requirements at a

county level.

Network expansion planning

The NEPLAN models were used in conjunction with GIS mapping to produce detailed short-medium term

expansion plans for the 66 kV and 33 kV networks in each of the four KPLC regions.

Generic or typical network configurations were developed to derive average incremental investment costs ($/kW)

for the various network topologies; urban, rural, Nairobi and off-grid. The county demand growth rates were then

used to calculate long term investment requirements.

The investment required at 11 kV and LV was determined at a county level both in the short-medium term and

long term using the average incremental cost approach.

Conclusions

The main conclusions that may be drawn from the study are briefly described below.

Short-Medium Term Plan

A short-medium term (2013-2017) distribution network reinforcement and expansion plan was developed for each

of the regions. This plan is based on detailed network analysis and identifies proposed 66 kV and 33 kV projects

that are required beyond the ongoing and committed projects. The need for additional BSPs, beyond the

committed transmission projects, and reinforcement of existing BSPs in order to support the distribution network

has also been identified.

The need for the projects is driven by the demand forecast which has been disaggregated to county level and

then applied to the individual substations across the network. The proposed projects should be considered to be

the minimum requirement to meet the forecast demand whilst complying with the planning criteria.

Across the network a total of approximately 300 projects are proposed for completion by 2017. These include

66 kV and 33 kV feeders, new and reinforced substations and reactive compensation. The estimated total

investment cost of these projects is $ 149 million. A further $ 107 million is required for new BSPs and


EXECUTIVE SUMMARY


reinforcement of existing BSPs over the same period. The corresponding investment in the 11 kV and LV

networks is included in the overall investment plan described below.

Interconnection of Off-grid Areas

The national grid does not currently extend to all parts of Kenya, and large parts of the country, particularly in the

north, remain off-grid. The total energy generated by the off-grid diesel power plants is relatively low, and for the

year 2010/11 represented just 0.8 % of the total electricity sales in the country.

Studies were conducted to assess the technical requirements and economic viability of extending the grid to each

of the off-grid areas. The studies include a comparison of the levelised cost of electricity for the grid connected

and off-grid options. The results indicate an economic case for extension of the grid to; Lodwar, Marsabit, Wajir,

Habaswein and Hola.2 These sites would be interconnected to the grid through extension of the transmission

network and therefore these projects are not included within the list of proposed distribution projects.

Environmental Impact Assessment

Environmental impact assessment scoping studies have been conducted for the projects proposed in the

Distribution Master Plan.

The scoping studies provide an initial assessment of the potential environmental and social impacts associated

with each of the projects currently proposed. The assessment has been based on desk study data used to

inform the county level baseline summaries as well as on feedback obtained from the in-county consultation

meetings. The impacts (and associated mitigation proposals) are necessarily high level since the exact project

locations and extents are as yet to be determined.

Based on the consultation feedback and high level assessments conducted to date, the negative impacts of

many of the proposed projects are expected to be minimal and the overall benefits of the projects are expected to

greatly outweigh the adverse impacts.

The EIA Scoping Report is intended to provide a basis for project-specific discussions with the relevant

authorities and stakeholders to help determine whether an Environmental Impact Assessment (EIA) is required

for each of the projects which come forward as part of the Distribution Master Plan.

Long Term Plan and Investment Plan

Generic models were developed to represent typical rural, urban and off-grid areas. These models were used to

derive average incremental investment costs which were applied to the demand forecast to obtain estimated long

term investment requirements for each of the counties.

The specific projects identified through detailed network studies only cover 66 kV and 33 kV network

requirements. The generic models were therefore also used to derive corresponding investments requirements

for the 11 kV and LV networks.

The total distribution infrastructure investment requirements for each county are provided in the report. This

includes estimated investment requirements for;

2 Garissa and Lamu were excluded from this analysis as there are ongoing projects to connect these areas to the grid.


EXECUTIVE SUMMARY


x the specific proposed short-medium term (2013-2017) 66 kV and 33 kV projects. Note that this excludes the costs associated with committed distribution projects,

x the estimated 11 kV and LV investment required in the short-medium term based on the generic models and

x the total estimated distribution investment requirements in the long term (2018-2030), based on the generic models.

The total annual investment in distribution infrastructure increases from $ 183 million in 2013 to $ 1.6 billion by

2030. The net present value of this investment at a discount rate of 12 % is $3.9 billion3.

Recommendations

Planning Data

During the data collection phase of this project it was observed that essential network planning data is not always

readily available. In order to improve the efficiency and effectiveness of the network planning process, it is

essential that improvements are made in the quality and accessibility of network and metering information

available to the planning department.

KPLCs network database was found to be only 60-70 % complete and in many cases conflicts were found

between the database and network schematics. For effective planning, it is important that the database and

schematics reflect as closely as possible the state of the network.

The lack of consistent primary substation and feeder load information is a significant issue and one that should

be addressed in order to improve the planning process and assist with prudent investment decisions.

Coordinated Approach

Distribution planning by necessity should be done at the local level within each region. Knowledge of the local

conditions, customers, and the existing network are all vital to distribution planning engineers. However there

should be a similar approach throughout the KPLC offices, applying national standards and planning criteria.

Currently, there is a wide variance in terms of training, tools, experience, and methodology of distribution

planning across the regions.

Standardised Planning

Procedures should be implemented and regular training provided to ensure that they are widely understood and

applied. Additionally, feedback from all regions should be used to update the standards and guidelines as

necessary.

Planning and Analysis Software

Implementation of planning and analysis software such as NEPLAN needs to be part of the overall

implementation of a coordinated network planning process. These packages are tools for planners to evaluate

different present and future scenarios to arrive at an optimum solution. However, without a coordinated network

planning process, these tools are of little benefit.

3 In money of 2012.


EXECUTIVE SUMMARY


It is recommended that KPLC invests further in training for distribution planning and that this training is rolled out

to each of the regions.

It is recommended that KPLC expands the use of NEPLAN to distribution planning engineers throughout Kenya

and continues the development of the network models. They need to be maintained in a controlled centralised

manner, ensuring that all network changes are captured.

Dedicated Distribution Planning Section

KPLC should establish a dedicated central distribution planning section. This section would be responsible for;

x Ensuring that network planning data is as complete and accurate as possible.

x Ensuring a coordinated approach to planning across the regions.

x Controlling the use of network planning software models across the regions.

Design Manual

The new Design Manual is a draft document and should be reviewed by KPLC before using it for network design.

The existing DSGM is likely to have evolved over some considerable time and may in many respects provide

adequate guidance.

The new Design Manual covers a number of areas as described above, including aspects not covered in the

DSGM. It is recommended that the new Design Manual is adopted over time. Some aspects may be found by

KPLC to be more useful and applicable than others and therefore is suggested that the document is gradually

amended and increasingly adopted by KPLC.

The report includes recommendations for training workshops associated with the Design Manual and also

includes recommendations for the development of related documentation including; construction and

maintenance manuals and technical specifications.

Updating the Distribution Master Plan

The Master Plan is based on many assumptions, not least the demand forecast. It should be reviewed annually

and modified as necessary to reflect changes in the underlying assumptions. The network planning software

(NEPLAN) provides the flexibility to readily incorporate changes and assess new requirements.

SECTION 1

INTRODUCTION

SECTION 1

INTRODUCTION

Distribution Master Plan Study Prepared for KPLC Final Report Page 1.1

1 INTRODUCTION

Parsons Brinckerhoff (PB) was appointed by The Kenya Power & Lighting Company Limited (KPLC) to conduct a

Distribution Master Plan Study to address the countrys distribution requirements up to 2030.

The main objectives of the study were to;

x conduct a detailed assessment of KPLCs distribution system requirements over the 2012-2030 planning period and develop a Distribution Master Plan and

x undertake an environmental scoping study for the investments recommended in the short-medium term (3-5 years).

1.1 Key Drivers

Development of the power sector in Kenya is underpinned by Vision 2030, which is Kenyas development

blueprint covering the period 2008 to 2030. The objective of Vision 2030 is to help transform Kenya into a,

middle-income country providing a high quality of life to all of its citizens by the year 2030. It identifies energy

and electricity as a key element of Kenyas sustained economic growth and transformation.

The power sector in Kenya requires high levels of investment to ensure that the rapidly growing demand is

adequately met. Major investments are being made in generation and transmission, however for benefits to be

realised, similar levels of investment are required in the distribution sub-sector. It is essential that this investment

is carefully planned to ensure efficient use of scarce resources.





households in Tana River County4. Electrification levels are increasing across the country and following



The Distribution Master Plan includes a forecast of electricity demand for each of the counties and identifies the

distribution infrastructure required to meet that demand, whilst achieving acceptable levels of power quality and

reliability, based on well established principles of least-cost planning.

1.2 Study Documents

The study documents have been compiled in three volumes as follows:

Volume I: Distribution Master Plan Report

Volume II: Design Manual

Volume III: Scoping Studies for Environmental Impact Assessment

4 Based on the 2009 Kenya Population and Housing Census Report


This report (Volume I), documents the work undertaken to produce a distribution master plan for Kenya and

includes a section to cover each of the main aspects of the study.

The first sections include a brief description of the distribution system in Kenya and describe the approach taken

by PB to conduct the study. The following section describes the demand forecast on which the Master Plan

Study was based and the process by which the national forecast was disaggregated to county level. The next

two sections cover planning criteria and design standards respectively. These also make reference to a Design

Manual which has been produced as a separate volume. These are followed by sections covering network data,

modelling and technical assessment of the existing networks. Network development in the short-medium term is

then covered in detail, including network planning studies spanning the first five years of the planning period.

The next section of the report includes a summary of the scoping study for the Environmental Impact

Assessment. The full scoping study is included in a separate volume. This is followed by a section which

considers extension of the grid to areas that are presently off-grid and includes technical and economic

assessment of grid extension versus continuing with off-grid solutions. The report then covers the approach to

long-term planning. The results of the short-medium term and long-term distribution network development plans

are brought together in the form of an investment plan, which identifies the projected investment requirements for

each of the counties over the planning period.

SECTION 2

BACKGROUND

SECTION 2

BACKGROUND


2 BACKGROUND

2.1 Electricity Sector

Figure 2-1 provides an overview of the Electricity Sector in Kenya and shows the relationships between the key

players.

Figure 2-1: Kenya Electricity Sector

The Electricity Sector falls under the Ministry of Energy (MoE), which provides policy direction. The Energy

Regulatory Commission (ERC) is responsible for formulating and enforcing regulations, licensing power

companies, providing customer protection, approving power purchase agreements (PPAs) and conducting tariff

reviews.

Kenya Electricity Generating Company (KenGen) is the largest generating company and is majority government

owned. The remaining grid-connected generation is provided by privately owned independent power producers

(IPPs). The Geothermal Development Company (GDC) develops geothermal steam fields for subsequent use by

generation companies.

KPLC, which is 51 % government owned, owns and operates both the transmission and distribution networks

throughout Kenya. KPLC is responsible for purchase of all bulk electricity and is the sole supplier to end use

customers throughout the country. KPLC also operates the majority of the off-grid diesel power plants on behalf

of the Rural Electrification Programme.

Ministry of Energy

Energy R

egulatory Com

mission

Policy Direction

GDCKenGen IPPs

KETRACO

KPLCRural ElectrificationAuthority

UETCLTANESCO

Retail Customers

Rural Electrification ProjectsImports/Exports

Enforce License Requirements

PPA and Bulk Tariff Approval

Retail Tariff Approval

Customer Complaints

SECTION 2

BACKGROUND


KPLC is the system operator and is responsible for generation scheduling and dispatch, frequency control,

voltage control, outage management and system security. Generation dispatch and control of the transmission

network is via the national control centre (NCC). The distribution networks are controlled regionally though each

of the four regional control centres (RCCs).

Kenya Electricity Transmission Company (KETRACO) is 100 % government owned, with responsibility for

constructing new transmission lines across the country and then handing them over to KPLC to operate and

maintain.

The Rural Electricity Authority (REA) has responsibility for implementing the governments Rural Electrification

Programme, which includes extension of the 33 kV and 11 kV distribution networks to facilitate the connection of

public facilities and private customers in rural areas.

Kenya is interconnected with Uganda at 132 kV, for import and export. Kenya supplies some border towns in

Tanzania at 33 kV and receives power from Ethiopia to supply a border town in the far north of the country.

2.2 Distribution Network Configuration

KPLCs distribution network includes the main interconnected grid in addition to a number of small off-grid

networks. The grid is operated in four distinct regions; Nairobi, Coast, Western and Mt. Kenya as shown in

Figure 2-2 with a further split into sub-regions as shown in Table 2-1. The extent of the grid covers the main

population centres in the four geographical regions.

2.2.1 Nairobi

Within the Nairobi Region, the network configuration differs from that of the other KPLC regions. The region is

supplied from the transmission network via several 220/66 kV and 132/66 kV transmission substations or bulk

supply points (BSPs). A number of 66 kV feeders emanate from each BSP and each 66 kV feeder supplies one

or more primary (66/11 kV) substations. Each primary substation supplies a number of 11 kV feeders, which in

turn supply 11/0.433 kV distribution substations. Larger customers may be supplied at 11 kV or 66 kV.

The Nairobi network is interconnected both at 66 kV and 11 kV, with normally open points to allow transfer of

load across BSPs or primary substations respectively.

The 66 kV feeders are mostly overhead using single and double circuit wood-pole construction. The 11 kV

feeders are also mostly overhead using single circuit wood or concrete pole construction.

In Nairobi city centre, where there are space constraints or issues with clearances, underground cables are used

for 11 kV and a few for 66 kV.

There are a few 66/33 kV substations on the outskirts of Nairobi, which supply neighbouring areas via long 33 kV

feeders.

SECTION 2

BACKGROUND


Figure 2-2: Extent and Regional Split of the Distribution Network

SECTION 2

BACKGROUND


Table 2-1: KPLC Regions

Region Sub-region

Nairobi

Nairobi South

Nairobi North

Nairobi West

Coast

Western

North Rift

Central Rift

West Kenya

Mt. Kenya Mt. Kenya North

Mt. Kenya South

2.2.2 Other Regions

The distribution network in the regions outside Nairobi is less interconnected, with many radial 33 kV feeders and

generally with long distances between BSPs. Standard BSP design typically consists of 2 x 132/33 kV two

winding transformers, however some BSPs are equipped with only a single transformer.

A number of 33 kV feeders emanate from each BSP and each 33 kV feeder generally supplies one or more

primary (33/11 kV) substations and many distribution (33/0.433 kV) substations. The 11 kV feeders emanating

from the primary substations in turn supply distribution substations.

In general, the primary substations are supplied from a single BSP, although some 33/11 kV substations have an

alternative supply at 33 kV from a different 132 kV substation. There are normally open points to avoid parallel

supply from different BSPs.

The 33 kV and 11 kV feeders are generally overhead using single circuit wood-pole or concrete-pole

construction. Underground cables are used as necessary due to space constraints in urban centres, although

their present level of use outside Nairobi is minimal.

In the urban centres, the 11 kV networks are interconnected where possible to provide alternative supply,

however in the rural areas the 11 kV feeders are radial.

SECTION 2

BACKGROUND


2.2.3 Off-grid Areas

Most of Kenya is off-grid as indicated in Figure 2-2, however the eight off-grid counties5, whilst geographically

large, account for just 7 percent of the population. It is important to note however that most of the rural areas

within the grid connected counties do not currently enjoy electricity access due to the limited extent of the grid.

This issue is being addressed by the Rural Electrification Authority (REA), which is undertaking donor and

government funded projects to extend the 33 kV and 11 kV networks. These projects are primarily aimed at

providing supplies for public facilities such as schools, health centres, trading centres and bore-holes.

In the larger towns in the off-grid counties, small isolated 11 kV networks are supplied via diesel generators, with

in some cases backup from renewable power sources such as solar photo-voltaic (PV). The REA is in the

process of extending some of these networks to nearby towns or villages by means of 33 kV transmission.

2.3 On-going Projects

Many projects are currently underway including new substations and feeders and reinforcement of existing

substations and feeders. These are aimed at extending the distribution network to new areas to increase

coverage and reinforcement of the existing network to accommodate demand growth and improve power quality

and reliability. The projects are grouped under various initiatives including the Energy Sector Recovery Project

(ESRP) and Kenya Electricity Expansion Project (KEEP) and include a combination of donor, government and

self funding by KPLC.

2.4 Network Planning Issues

The distribution network suffers from poor reliability and quality of supply, which is generally due to under-

investment. Some of the key issues identified during the study are briefly described below.

2.4.1 Feeder Length

Many parts of the distribution network are supplied over extremely long, radial 33 kV and 11 kV feeders, with no

alternative source of supply. In some cases, 33 kV feeders may be hundreds of km long, with many spurs,

resulting in a total length (in extreme cases) in excess of 1000 km supplied from a single source. A fault on such

a long feeder will have wide-spread impact, be difficult to locate and therefore will result in a long restoration time.

These parts of the network are not surprisingly subjected to frequent and prolonged outages.

Due to excessive feeder lengths and use of undersized conductors, voltage levels on feeders, particularly

outside of the urban areas are typically poor and significantly under the required standard. Automatic

voltage regulators (AVRs) have been installed on feeders in the past, however many of these have failed and

have subsequently been bypassed.

Excessively long, undersized feeders also result in high losses. As a distribution operator, losses must be paid

for as they represent a proportion of the energy purchased. Furthermore, distribution infrastructure must be sized

for both the delivered power and power losses. For these two reasons, there is a financial incentive to reduce

losses.

5 Lamu, Tana River, Garissa, Mandera, Wajir, Marsabit, Samburu and Turkana

SECTION 2

BACKGROUND


Economically, losses represent part of the generated energy and generation and transmission infrastructure must

be sized for both the delivered power and losses. Losses therefore have both energy and capacity cost

components and loss reduction measures on distribution networks tend to be self financing.

Generally however, provided distribution plant and feeders are not overloaded and voltage levels are within

normal limits, the level of losses will be acceptable. The Distribution Master Plan includes studies to identify

excessive feeder loading and poor voltage regulation and includes measures to address these issues. The

Master Plan also includes planning guidelines for feeders, identifying maximum MVA.km curves for the standard

and proposed conductor sizes.

2.4.2 Bulk Supply Points

A related issue concerns the number of BSPs across the system. In many parts of the country, the BSPs are

sparsely distributed; with no available alternative should that BSP fail. This issue of course has a direct bearing

on the 33 kV feeder lengths and the associated reliability and power quality issues.

KETRACO is currently investing in new transmission lines and associated substations, both in Nairobi and in

other parts of the country. These new BSPs will relieve loading on existing overloaded BSPs and will allow for

shorter feeder lengths and greater levels of interconnection. These measures will therefore improve voltage

levels and reliability.

In some cases the new BSPs will result in extension of the grid to currently off-grid areas, improving reliability of

supply to those areas and reducing the cost of supply by displacing expensive diesel generating plant.

The Master Plan includes studies to identify the need for and location of additional BSPs beyond those already

under construction or committed.

2.4.3 Security of Supply

Much of the distribution network does not have adequate capacity to effectively manage the present

demand, and many of the primary substations are loaded well beyond firm capacity. Adequate excess capacity

is unavailable, making it difficult to manage contingencies and meet future demand.

KPLC aims to achieve N-1 security of supply at least for major substations. However many primary substations

(and BSPs) are equipped with just a single transformer and even those with two or three transformers are often

loaded such that no spare capacity exists to cater for a transformer failure. This is a particular issue for parts of

the network with no alternative means of supply.6

In the event of such a failure, it is often necessary to source a spare transformer from another part of the network,

resulting in a prolonged outage before supply is restored.

The Master Plan identifies transformer loading across the network and makes recommendations for a graduated

move

6 In urban areas such as Nairobi, where a greater level of interconnection exists, there is often scope to switch a feeder onto an alternative BSP or primary substation at 66 kV and 11 kV respectively. In the more rural, radially fed areas, there is no scope for this type of switching and transformer redundancy is therefore particularly critical.

SECTION 3

MASTER PLAN APPROACH

SECTION 3



3 MASTER PLAN APPROACH

3.1 Overview

The process by which the Distribution Master Plan was completed is shown in Figure 3-1.

Figure 3-1: Master Plan Process

Throughout the period of the Master Plan Study, there was close collaboration between the PB team and the

KPLC counterpart team. The process began with a detailed data gathering exercise at a central, regional and

sub-regional level.

The scope of the study included provision of suitable software to conduct the detailed network analysis and to

provide an ongoing tool for KPLC to use in the future. Selection and procurement of the software was conducted

in parallel with data gathering as indicated in Figure 3-1.

This was followed by network modelling and assessment of existing network issues and constraints, leading to

short-medium term planning studies covering the period from 2012-2017. The network modelling and analysis

for the various KPLC regions was conducted in parallel in order to minimise the time required for these detailed,

data-intensive tasks.

Apart from the network data and models, key inputs to the planning studies were; the demand forecast and the

planning and design guidelines.

Long term planning was based on the development of generic networks to represent the different typical network

topologies, i.e. urban, rural, Nairobi and off-grid configurations. These were used along with the county level

demand forecast to determine the longer term investment requirements.

Data gathering at central and regional level

Software selection Network modelling Assess existingNetwork issuesShort-medium term planning studies

Planning and designguidelines

Genericnetworks

Long term plan

Detailed interaction with counterparts

Demand forecasting

County level meetings (in each of the 47 countiesHosted by KPLC BBHs)

ESIA scopingstudies

Localised technicalissues

DISTRIBUTIONMASTER PLAN

3 week intensive training course in UKIncluding visits to industry

Investment plan

Off-gridassessment

SECTION 3



A key aspect of the Master Plan study was consultation at a county level. This consultation was used to inform

the Environmental Impact Assessment scoping studies and also provided valuable insights into technical issues

at a local level.

The Master Plan study draws together the key aspects of the assignment which are briefly described below.

3.2 Counterpart Team

An important factor leading to the successful completion of the Master Plan Study was the appointment by KPLC

of a dedicated team of knowledgeable counterparts. The counterpart team was pivotal during the data gathering

stage and provided invaluable local knowledge during development of the short-medium term plans.

The assignment included an intensive three-week training course in the UK. This covered most of the key

aspects of the study and included hands-on training in the use of the network planning software.

3.3 Data Gathering

Data gathering was conducted at central, regional and sub-regional level. County level meetings were also held

as described below.

Initial data collection was conducted at KPLCs central offices in Nairobi. This included centrally stored network

data and diagrams, relevant reports, branch sales data and relevant information from Kenya National Bureau of

Statistics (KNBS).

The initial data gathering stage was followed in April with data gathering at the regional and sub-regional level.

This was conducted in three teams, each comprising members from the PB and KPLC counterpart study teams.

The teams covered the various KPLC regions as follows:

x Nairobi Region

x Coast and Mt. Kenya Regions

x Western Region

The data obtained in the regions and sub-regions was used to try to complete the many gaps in the data obtained

initially from the central offices. Most of the remaining gaps were resolved through collaboration with the KPLC

counterpart team, thereby minimising the number of assumptions that needed to be made with respect to the

network models.

3.4 Software Selection

The scope of the study included the procurement of a suitable software package, both for conducting the network

analysis during the study and for handing over to KPLC at the end of the study. Two potential software packages

were assessed and following a presentation by PB, KPLC chose NEPLAN.

3.5 Network Modelling and Assessment of Existing Networks

The next stage was to develop detailed NEPLAN models of the 33 kV and 66 kV networks. These were initially

used to assess the performance of the existing networks in each of the four KPLC regions and to identify specific

network constraints.

SECTION 3



Representative 11 kV feeders for each of the four regions were also modelled and assessed using NEPLAN.

3.6 County Visits

Stakeholder meetings were held within each of the 47 counties, in order to gather data for the EIA scoping study

and to understand key technical issues at a county level.

County meetings were initially held in three pilot counties. Following the pilot meetings, the agenda was refined

and used as the basis for the remaining meetings.

3.7 Demand Forecasting

The demand forecast contained within the Least Cost Power Development Plan (LCPDP) dated March 2011 was

used for the study. This was disaggregated to county level using a process that is described in detail in this

report. County demand growth rates were applied to the respective substations to determine substation

demands for the network studies. County growth rates were also used to determine investment requirements at a

county level.

3.8 Short-medium term planning

The existing network models were used as the basis for the short-medium term planning studies. Ongoing and

committed projects were added to the models and studies were conducted for each of the years up to 2017. The

outcome of these studies was a list of projects that would be required beyond the ongoing and committed

projects, in order to meet the forecast demand whilst satisfying the planning criteria.

The short-medium term investment requirements at 33 kV and 66 kV were determined directly from these lists of

projects by applying estimated project costs.

3.9 Long term planning

Generic or typical network configurations were developed to derive average incremental investment costs ($/kW)

for the various network topologies; urban, rural, Nairobi and off-grid. The county demand growth rates were then

used to calculate long term investment requirements

The investment required at 11 kV and LV was determined at a county level both in the short-medium term and

long term using the average incremental cost approach.

SECTION 4

DEMAND FORECAST

SECTION 4

DEMAND FORECAST


4 DEMAND FORECAST

4.1 Background

Vision 2030 is Kenyas development blueprint covering the period 2008 to 2030. The objective of Vision 2030 is

to help transform Kenya into a, middle-income country providing a high quality of life to all of its citizens by the

year 2030. The Vision outlines the Government of Kenyas economic growth objectives. These objectives were

used to develop the official Kenyan demand forecast using an econometric model which links electricity sales to

economic growth and the price of electricity. This demand forecast is presented in the Least Cost Power

Development Plan (LCPDP) publications.

The LCPDP (and associated demand forecast) is updated annually by a committee comprising officers from the

Ministry of Energy (MoE), Energy Regulatory Commission (ERC), Kenya Electricity Generating Company

(KenGen), Kenya Power and Lighting Company (KPLC), Kenya Electricity Transmission Company (KETRACO),

Geothermal Development Company (GDC), Rural Electrification Authority (REA), The Ministry of State for

Planning, National Development and 2030, Kenya Vision 2030 Board, Kenya Investment Authority (KenInvest),

Kenya Private Sector Alliance (KEPSA) and the Kenya National Bureau of Statistics (KNBS). The LCPDP is the

key power generation and transmission system planning document in Kenya. The key message within the

LCPDP is that, there is a need to plan for sufficient electricity capacity additions to meet the growth aspirations

of the Vision 2030. Vision 2030 identifies energy and electricity as a key element of Kenyas sustained

economic growth and transformation.





households in Tana River County. Electrification levels are increasing across the country and following



In accordance with the terms of reference, the LCPDP demand forecast is to be applied in the Master Plan study.

The terms of reference for the Master Plan Study include the need to identify the distribution infrastructure

requirements to meet the needs of each county. A key element of this process is to develop a demand forecast

for each county as this will be the main driver for investment. In this section of the report we describe the

process by which the LCPDP forecast has been disaggregated to county level.

4.2 LCPDP Demand Forecast

The demand forecast that will be applied in the Distribution Master Plan Study is described in detail in the LCPDP

for the period 2011-2031, dated March 2011.

The LCPDP forecast is based on a number of inputs including; GDP growth rate projections, population growth

rates, levels of urbanisation, levels of electrification and specific consumption.

SECTION 4

DEMAND FORECAST


The results of the forecast are shown below. The energy (GWh) forecast refers to generated energy and

therefore includes transmission and distribution losses as described in the LCPDP and noted in Table 4-1. The

following levels of losses were taken from the LCPDP.

The peak (MW) demand forecast was calculated from the energy forecast using the load factors shown and

refers to generated power.

The forecast shown in Table 4-1 does not include the Vision 2030 Flagship Projects. Some of these are

particularly energy intensive and the estimated energy and capacity requirements along with the expected

completion dates for these projects are shown in Table 4-2.

Table 4-1: LCPDP Forecast Excluding Flagship Projects7

Source: LCPDP, March 2011.

The resultant total forecast including the Flagship Projects and also allowing for an element of gradually

decreasing suppressed demand is shown in Table 4-3. According to the LCPDP report, the forecast includes

100 MW of suppressed demand in 2010, gradually reducing to zero by 2015. Again the figures shown are at the

generation level and therefore include transmission and distribution losses.

7 The LCPDP forecast is at generation level and therefore includes transmission and distribution losses.

SECTION 4

DEMAND FORECAST


Table 4-2: Energy Intensive Vision 2030 Flagship Projects


Table 4-3: LCPDP Forecast including Flagship Projects


SECTION 4

DEMAND FORECAST


4.3 Deriving the LCPDP Demand Forecast

4.3.1 Introduction

In order to disaggregate the LCPDP demand forecast to county level, it was first necessary to understand how

the LCPDP forecast was derived. This was achieved by reconstructing the LCPDP forecast using the data and

assumptions provided in the LCPDP report. Once the LCPDP forecast had been derived on a national level, it

was possible to derive county level forecasts using the same methodology.

The objective in this sub-section is to re-create the LCPDP forecast. Using the methodology described in the

LCPDP report, a national level energy demand forecast was re-created for each consumer category including;

domestic urban, domestic rural, industrial & commercial and street lighting. The sum of the demand forecasts for

the various consumer categories derived in this way was then compared with the published LCPDP forecast to

confirm that a reasonable reconstruction had been achieved.

4.3.2 Methodology

The model presented in this section uses economic and technical assumptions set out in the LCPDP report and

aims to recreate the final Load Forecast set out in the LCPDP by applying appropriate logical linkages to specific

statistical inputs found in both 2009 Kenyan census statistics and Kenya Power Annual Report 2011 data. The

flow diagram below shows the steps followed by the model to calculate the energy and peak demand forecasts

for the Kenyan network.

4.3.3 Assumptions

Domestic Demand Assumptions

Many of the models assumptions are taken directly from the LCPDP. Population is assumed to grow from 38.6

million according to the 2009 Kenya Population and Housing Census Volume 1C (2009 Census) to 60.5 million

by 2030 according to the LCPDP.

Similarly, growth in urbanization levels of consumers is a key demographic input and driver of demand and sales.

This is assumed to rise from 32 % in 2009, to 63 % in 2031 as stated in the LCPDP.

The number of persons per household differs between urban and rural domestic settings. The number of persons

per urban household is expected to decrease from a present average of 5, to 4.3 by 2031. The number of

persons per rural household is expected to decrease from a present average of 6.5, to 5.9 by 2031.

The LCPDP differentiates between high, middle and low income groups in terms of future supply rates and

specific consumption. The LCPDP does not however specifically identify the proportions of the population falling

into each of these income groups in the urban and rural areas. These proportions were therefore estimated. The

weighted average specific consumption calculated from the estimated proportions was then compared with the

average specific consumption from the KPLC 2010/11 Annual Report. The proportions in the various income

groups were then adjusted until the calculated weighted average consumption approximated the actual average

specific consumption. The proportions derived in this way are as shown in Table 4-4.

SECTION 4

DEMAND FORECAST


Table 4-4: Estimated Proportions of Income Groups

Income Group Weighting

Urban High Income 10 %

Urban Middle Income 20 %

Urban Low Income 20 %

Rural High Income 5 %

Rural Middle Income 15 %

Rural Low Income 30 %

The calculated weighted average specific consumption for urban and rural areas was then as shown in Table 4-5.

Table 4-5: Estimated Specific Consumption

2009 2031

Urban (kWh/household/year) 1410 1338

Rural (kWh/household/year) 514 748

The electrification rates assumed for 2031 are given in the LCPDP and differ between the high, middle and low

income urban and rural consumers. Using the estimated proportions in each of the income groups and the 2031

supply rates in each of those groups as quoted in the LCPDP it was possible to derive a weighted average supply

rate for urban and rural households. This was assumed to reach 98 % for urban households and 58 % for rural

households by 2031.

Industrial and Commercial Demand Assumptions

The Industrial and commercial demand in the LCPDP forecast, is based on GDP growth. The level of economic

growth is a key driver for increased electricity consumption. The assumed coefficient factors are defined in the

LCPDP as consumption growth rate divided by the real GDP growth rate. The table below shows the assumed

coefficient factors that are used in the LCPDP model.

Year Electricity Intensity2012 1.252013 1.322014 1.38

2015-2031 1.44

SECTION 4

DEMAND FORECAST


Annual GDP growth rates were adjusted to obtain the required total demand in line with the LCPDP. The

resultant average annual GDP growth required to match the LCPDP forecast was 9.7 %.

Wider Assumptions

The LCPDP states that the number of lamps used for street lighting is assumed to grow at 80% of the growth rate

of the number of domestic consumers. There is also an assumed technical improvement increasing the efficiency

of the lamps and resulting in specific consumption decreasing by 1 % per year.

Levels of energy losses were assumed to be the level set out in the LCPDP at 14 %.

Load Factors were also assumed to be as stated in the LCPDP. The load factor for the domestic sector and

street lighting was assumed to be falling from 55 % to 45 % between 2012 and 2031. The commercial and

industrial load factors were assumed to be constant at 76 %.

4.3.4 Demand Forecast

The resultant demand forecast derived as described above is shown in Table 4-6.

The right-hand column, which is sales plus transmission and distribution losses, shows a close match with Table

4-3 (LCPDP Reference Scenario GWh).

Table 4-6: Derived LCPDP Forecast (GWh)

4.3.5 Summary

The load forecast model presented in this section of the report can be summarised as follows:

Domestic Urban

Domestic Rural

Ind & Commercial

Street Lighting Total sales

Flagship Projects

Generation (GWh)

2012 1434 103 5977 21 7535 282 90902013 1601 120 6805 23 8548 565 105972014 1786 138 7862 25 9812 847 123942015 1994 160 9662 28 11843 1130 150852016 2226 185 11088 30 13529 1412 173742017 2485 214 12685 33 15417 1695 198972018 2775 248 14511 36 17570 1977 227292019 3099 286 16287 39 19712 2259 255492020 3461 331 18515 43 22351 2542 289452021 3866 383 20915 47 25212 2824 326002022 4319 443 23626 51 28440 3107 366822023 4826 513 26517 56 31912 3389 410482024 5393 593 29954 60 36001 3672 461312025 6028 686 33836 66 40616 3954 518252026 6738 794 38124 71 45727 4236 580972027 7533 919 42955 77 51484 4519 651202028 8424 1063 48460 84 58030 4801 730602029 9421 1230 54671 91 65412 5084 819722030 10539 1423 61599 98 73658 5366 918882031 11623 1646 70025 105 83399 5648 103544

SECTION 4

DEMAND FORECAST


x The load forecast uses the assumptions stated in LCPDP and has attempted to replicate the results produced in the Vision 2030 flagship load forecast presented in the LCPDP March 2011.

x Where possible, all input data used was provided by the LCPDP. Where the LCPDP data was not available, relevant input data was extracted from the Kenyan Census 2009 or from the Kenya Power

Annual Reports 2011.

x The GDP growth rate assumptions take into account the growth created by the flagship projects due for completion 2012-2021.

4.4 County Statistics

Figure 4-1 shows the forty seven counties formed under the new constitution.

4.4.1 County Electrification Levels

Key statistics from the 2009 Population and Housing Census (Table 4-7) were used as the basis for

disaggregation of the LCPDP demand forecast to the county level. The 2009 Census data was obtained from the

Kenya National Bureau of Statistics (KNBS) and is the most up to date information available.

SECTION 4

DEMAND FORECAST


Figure 4-1: Kenya County Map

SECTION 4

DEMAND FORECAST


Table 4-7: Key Statistics from 2009 Census

Figure 4-2 and Figure 4-3 show the 2009 electrification levels (electrified households as a percentage of the total

households) per county for urban and rural areas respectively. It may be seen that there is a wide range in

household electrification in both urban and rural areas. The total urban household electrification level for Kenya

was approximately 50 % in 2009, whilst the corresponding rural figure was 5 %.

Region Sub-regionCounty

Rural Population

Urban Population

Total Population Urban (%)

Electrified (%) Urban

Electrified (%) Rural

Western Central Rift Baringo 445,828 63,168 508,996 14% 38.5% 4.7%Western West Kenya Bomet 694,881 108,268 803,149 15% 12.3% 2.9%Western West Kenya Bungoma 1,222,743 280,568 1,503,311 21% 14.4% 1.8%Western West Kenya Busia 592,092 112,992 705,084 18% 23.5% 2.1%Western North Rift Elgeyo Marakwet 309,965 46,420 356,385 15% 21.8% 4.6%Mt Kenya Mt Kenya North Embu 501,734 99,724 601,458 19% 47.4% 7.3%Off grid Off grid Garissa 343,133 102,332 445,465 26% 43.2% 0.5%Western West Kenya Homa Bay 817,725 129,084 946,809 16% 13.9% 1.4%Mt Kenya Mt Kenya North Isiolo 79,059 58,020 137,079 46% 37.0% 2.6%Nairobi Nairobi Kajiado 405,817 348,480 754,297 50% 66.8% 12.6%Western West Kenya Kakamega 1,127,102 225,576 1,352,678 19% 21.7% 2.2%Western West Kenya Kericho 361,012 203,080 564,092 40% 22.6% 4.6%Mt Kenya Mt Kenya North Kerinyaga 595,326 110,220 705,546 18% 46.2% 10.0%Nairobi Nairobi Kiambu 711,091 1,242,852 1,953,943 67% 67.2% 29.0%Coast Coast Kilifi 599,368 288,956 888,324 36% 39.4% 3.9%Western West Kenya Kisii 975,842 248,228 1,224,070 23% 23.3% 3.1%Western West Kenya Kisumu 479,856 498,488 978,344 55% 30.8% 3.1%Mt Kenya Mt Kenya South Kitui 806,633 135,468 942,101 16% 23.4% 1.1%Coast Coast Kwale 436,907 116,352 553,259 24% 33.5% 3.4%Mt Kenya Mt Kenya North Laikipia 347,090 117,060 464,150 28% 50.7% 4.6%Off grid Off grid Lamu 81,738 19,172 100,910 22% 62.8% 4.4%Nairobi Nairobi Machakos 536,853 601,104 1,137,957 57% 27.4% 3.4%Nairobi Nairobi Makueni 751,074 106,700 857,774 14% 24.7% 2.7%Off grid Off grid Mandera 480,255 93,260 573,515 19% 12.9% 0.2%Off grid Off grid Marsabit 212,177 47,188 259,365 21% 33.7% 0.6%Mt Kenya Mt Kenya North Meru 1,335,820 141,596 1,477,416 11% 60.1% 7.8%Western West Kenya Migori 535,072 265,464 800,536 37% 12.5% 1.1%Coast Coast Mombasa - 1,074,800 1,074,800 100% 59.0% 0.0%Mt Kenya Mt Kenya South Muranga 1,034,160 171,588 1,205,748 16% 34.7% 9.9%Nairobi Nairobi Nairobi - 3,940,064 3,940,064 100% 72.4% 0.0%Western Central Rift Nakuru 922,248 854,452 1,776,700 52% 56.0% 10.1%Western North Rift Nandi 612,542 94,980 707,522 15% 21.4% 3.6%Western Central Rift Narok 717,775 66,008 783,783 10% 43.6% 1.8%Western West Kenya Nyamira 427,573 61,648 489,221 14% 16.1% 4.4%Mt Kenya Mt Kenya North Nyandarua 537,863 117,760 655,623 20% 27.2% 6.2%Mt Kenya Mt Kenya North Nyeri 692,475 217,472 909,947 27% 55.3% 15.6%Off grid Off grid Samburu 180,137 36,108 216,245 19% 26.6% 1.4%Western West Kenya Siaya 830,358 89,448 919,806 11% 19.7% 2.4%Coast Coast Taita Taveta 247,934 73,352 321,286 26% 35.6% 7.8%Off grid Off grid Tana River 185,815 31,516 217,331 17% 10.1% 1.0%Mt Kenya Mt Kenya North Tharaka Nithi 309,697 91,640 401,337 26% 21.4% 3.8%Western North Rift Trans Nzoia 605,689 164,988 770,677 24% 27.5% 2.9%Off grid Off grid Turkana 470,357 92,460 562,817 19% 10.4% 0.6%Western North Rift Uasin Gishu 497,246 385,976 883,222 48% 51.3% 6.6%Western West Kenya Vihiga 395,378 156,896 552,274 32% 10.8% 5.3%Off grid Off grid Wajir 346,634 59,288 405,922 17% 20.2% 0.1%Western North Rift West Pokot 398,198 36,216 434,414 10% 21.1% 0.6%

Kenya 25,198,270 13,626,480 38,824,750 35% 50.4% 5.1%

SECTION 4

DEMAND FORECAST


Figure 4-2: Urban Household Electrification Levels

Figure 4-3: Rural Household Electrification Levels

The electrification levels are shown geographically in Figure 4-4 which indicates that the large counties in the

north and east of the country have the lowest electrification levels. There are however wide ranges in

electrification levels within individual counties. In the large off grid counties to the north and east of the country,

only the larger towns are served by isolated diesel power plants, generally feeding a small 11 kV network within

the town. Table 4-7 indicates that eight of the counties are currently off-grid, although in some of them the grid

extends to part of the county. This is covered in more detail in a later section of the report.

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

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0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

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SECTION 4

DEMAND FORECAST


Figure 4-4: Electrification Levels across the Country

4.4.2 Existing Demand

Disaggregation of the existing demand was based on 2011 sales data provided by KPLC from 84 branches. The

branch sales data provided was limited to Domestic and Small Commercial Sales which account for around 40 %

of the total sales. The remaining 60 % of sales are in the Industrial and Large Commercial categories. For

these, only a regional split was provided as follows:

SECTION 4

DEMAND FORECAST


In the absence of more information, the Industrial & Large Commercial sales were shared across the counties

within each of the KPLC regions in the same proportion as the Domestic and Small Commercial Sales. The

resultant regional split of sales and sales by county are shown in Table 4-8 and Table 4-9 respectively.

Table 4-8: Regional Split of 2011 Sales

KPLC Region Share of Industrial & Large Commercial salesNAIROBI 33%COAST 13%WESTERN 9%MT KENYA 4%TOTAL 60%

Region TotalCoast 17%Mt Kenya 8%Nairobi 57%Off grid 1%Western 17%Grand Total 100%

SECTION 4

DEMAND FORECAST


Table 4-9: 2011 Sales by County (GWh)

Region Sub-region CountySum of 2011 Domestic

Sales (GWh)Sum of 2011 Industrial & Commercial (GWh)

Sum of 2011 Total sales (GWh)

Coast Coast Kilifi 25 140 166Kwale 16 88 103Mombasa 102 572 674Taita Taveta 9 49 58

Coast Total 152 849 1001Mt Kenya Mt Kenya North Embu 13 37 50

Isiolo 6 15 21Kerinyaga 8 23 31Laikipia 15 42 57Meru 13 36 49Nyandarua 10 27 37Nyeri 27 74 102Tharaka Nithi 6 16 22

Mt Kenya South Kitui 8 23 32Muranga 10 28 38

Mt Kenya Total 117 321 438Nairobi Nairobi Kajiado 33 99 132

Kiambu 171 516 688Machakos 14 41 55Makueni 2 5 7Nairobi 610 1836 2446

Nairobi Total 830 2498 3328Off grid Off grid Garissa 7 4 11

Lamu 4 2 6Mandera 2 1 4Marsabit 2 1 3Samburu 2 4 6Tana River 1 1 2Turkana 2 1 4Wajir 2 2 4

Off grid Total 22 17 39Western Central Rift Baringo 2 6 8

Nakuru 79 211 290Narok 5 13 18

North Rift Elgeyo Marakwet 1 2 3Nandi 7 19 26Trans Nzoia 12 32 44Uasin Gishu 40 108 148West Pokot 2 5 7

West Kenya Bomet 2 5 8Bungoma 5 13 18Busia 6 17 24Homa Bay 5 12 16Kakamega 16 44 60Kericho 11 30 41Kisii 16 43 59Kisumu 40 107 147Migori 8 22 30Nyamira 2 6 9Siaya 7 19 26Vihiga 6 15 21

Western Total 274 729 1003Grand Total 1394 4415 5809

SECTION 4

DEMAND FORECAST


4.5 County Demand Forecast

The LCPDP demand forecast methodology was applied to obtain a county level forecast as described below. A

separate domestic urban, domestic rural and industrial & commercial forecast was produced as follows.

4.5.1 Domestic Urban

The starting point for the domestic urban forecast was the county urban population from the 2009 Census. The

total urban population in 2009 was 13.6 million, representing 32 % of the total population. According to the

LCPDP, the total Kenya population was expected to rise to 60.5 million by 2031, with 63 % living in urban areas.

This information was used to forecast urban population for each county.

The next step was to calculate the number of urban households per county. The LCPDP quotes a

KPLC Distribution

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