DATA COLLECTION OF CITIES’ ENERGY SYSTEMS AND€¦ · Sustainable Energy Planning Kiev, Ukraine...

CHARACTERIZATION AND DATA COLLECTION OF CITIES’

ENERGY SYSTEMS AND NETWORKS:

INSIGHTS FROM INSMART PROJECT

Workshop on Tools and Methodologies for Municipal Sustainable Energy Planning

Kiev, Ukraine

10th and 11th of July 2017CO2

ENERGY &

CLIMATE

New Technologies & Low Carbon Practices

Climate Mitigation/ Adaptation

Consumers Profiles &

Energy Efficiency

Policy Support

Energy Transitions

Integrative Energy City

Planning

Luís Pereira [email protected]

CENSE, NOVA-FCT, 2017

Acknowledgements:G. Giannakidis, R.De Miglio, A. Chiodi, M. Gargiulo, G. Long, M. Pollard, D. Irons, N. Bilo, A. Whitley, S. Burioli, L. Anthopoulos, V. Nunes and all other members of InSmart consortium

S. Simões, . P. Gouveia, J. Seixas

AGENDA

› Context

› InSmart project (recap)

› City energy planning structure

› Methods & tools for data-driven integrated energy planning

› Buildings and transport

› Urban Spaces and public buildings & services analysis

› Energy supply system› Renewable energy source potential

› Conclusions and recomendations


CONTEXT

more than half of

global population80% of the world’s

GDP in 2013

two-thirds of primary

energy demand

70% of total energy-

related CO2 emissions

70% in 2050


INSMART PROJECT

› Vision› Cities sustainable energy future are achievable by:

› bringing together cities, scientific and industrial organizations, › considering the integration of the components of the city’s energy system, › selecting cost-effective options from multiple data sources and integrated tools, › choosing the best social-accepted technologies and measures.

› Purpose› Design comprehensive data-driven methods for enhancing the city’s sustainable

planning, addressing the current and future city energy needs. › Implement an integrative planning tool to identify the optimum mix of short,

medium and long term measures for a sustainable energy future for the city. › Address the efficiency of energy flows across all city sectors considering spatial

patterns and economic, environmental and social criteria. › Engage city agents to pave the implementation of priority actions.


METHODS & TOOLS FOR DATA-DRIVEN

INTEGRATED ENERGY PLANNING

First: Analysis of existing sustainable policies and data availability for each city –identification of data gaps

and challenges and propose specific measures either in the form of necessary actions, (e.g. necessary preliminary studies, data acquisition, monitoring) as well as organisationalrestructuring of the city administration in order to achieve the sustainability targets.

Include different departments of the municipality to contribute


METHODS & TOOLS FOR DATA-DRIVEN

INTEGRATED ENERGY PLANNING› Door-to-door Buildings and Transport and Mobility Surveys

› Comprehensive GIS energy city database (present situation and future scenarios)

› Cities buildings stock characterized and modeled through a typology approach (using Energy Plus modeling tools)

› Extensive data from smart meters (relying on a sample of the 31000 EDP Distribution S.A., INOVGRID project)

› Transport based energy and carbon model

› Integrated modeling with TIMES (The Integrated Markal-Efom System) technoeconomicoptimization modeling tool.

– used to analyse the mix of measures required to meet sustainable energy targets

› Selected measures assessed with respect to non-technical criteria using a multicriteria decision making method (PROMEΤHEE (Preference Ranking Organization Method for the Enrichment of Evaluations) to address economic, environmental as well as social issues.


TRANSPORT AND RESIDENTIAL SECTORS

› Model building energy consumption1. Initial data collection

2. Identify building typologies

3. Detailed housing surveys

4. Detailed electricity use analysis

5. Energy demand modelling

identify a set of building typologies, based on construction period and built form, to represent the city’s housing stock (e.g. modern detached houses built after 1980 or historic terraced or row housing built before 1900).

-data and local knowledge already exists -> census records, spatial datasets, municipal records and national surveys;

Conduct a survey of city households to collect the data required for the construction of energy models for each city’s building typologies, based on a representative sample of each city’s housing stock according to its distribution. The surveys collected a wide range of information including details of the built structure (materials, insulation, internal floorplans, glazing), its occupants (age, income, employment status), heating/cooling systems presence and use, electrical appliances and lighting;

Nottingham around 600 surveys were performed, and in Évora around 400.



› Model building energy consumption4. Detailed electricity use analysis

5. Energy demand modelling

Gouveia, J.P., Seixas, J. (2016). Unraveling electricity consumption profiles in households through clusters: Combining smart meters and door-to-door surveys. Energy and Buildings. 116, 666–676.

When smart meters data are available, they are highly valuable in understanding electricity use within each building typology. • Due to its high temporal granularity, data from smart meters shows

how energy is consumed over the course of a day and how this varies over the course of a year.

• identify potential fuel poverty within certain types of housing and/or in particular areas of a city.

• Important to calibrate the energy demand modelling and to guide the selection of measures while respecting the city’s socio-economic features.

Create simulation models using building energy modelling software. EnergyPluswas used for the four INSMART cities but other similar software tools could also be used. Sensitivity analysis is performed to identify the variables that have a signifcant impact on energy demand


› Housing retrofit modelling


Map of simulated total energy demand for residential buildings in Nottingham

Identify potential retrofit options for each building typology.These include options for upgrades to heating/cooling systems, addition of insulation to walls, roofs or floors, draught-proofing measures or the addition of shading devices. The impact of each retrofit option is simulated using the building energy models


› The model developed as part of the INSMART project is an easy to use, but complex model, requiring minimal input data and computational time, but still providing sufficient sophistication to produce meaningful outputs for a variety of scenarios. The model includes processes for:


• Trip Generation from household numbers and floor space information for non-residential locations;• Modal Choice between highway and public transport. • Route Choice for both highway and public transport, allowing for the testing of new roads, traffic restrictions and new or

altered service patterns and routes.• Splitting vehicular demand into detailed Fleet Types, by vehicle and fuel type and Euro class rating, to allow for detailed

emissions calculation. Fuel Consumption calculations for the entire city, split by movements between city zones, plus the zone where the fuel is consumed.

• Data on demand flows, vehicle kilometers and key emissions such as CO2, Hydrocarbons and PM10s is produced.

Modelling process

Creation of a Base Year model Running the model forward to 2030 Forecast scenariosRepresenting the current energy usage situation in each city;Transport surveys were undertaken in each city (a minimum of 400 surveys was required) to assess the different trip-making purposes and patterns

demonstrated the effect of changes in population and the vehicle fleet over time as people switched to more efficient vehicles and represented a ‘Do Nothing’ scenario to which allothers could be compared

Run wide range of forecast scenarios providing changes in demand, energy usage and emissions compared to the ‘Do Nothing’ scenario


TRANSPORT AND MOBILITY


METHODS AND TOOLS | APPROACH

Data Acquisition: Municipality teams+ technical teams contacted localstakeholders for data collection (alsocreated the opportunity tointroduce/open the project to localcommunity).

Analysis of the cities’ energy systemsand networks: Energy supply


URBAN SPACES AND PUBLIC BUILDINGS & SERVICES ANALYSIS AND

ENERGY SUPPLY SYSTEM

› Urban spaces

› Water and sewage system

› Municipal Solid Waste chain

› City Energy supply system

› Buildings under Municipal Management

› Private services Buildings


URBAN SPACES

Characterization of the public urban spaces with relative importance consumption of energy within the city

Gardens/green areas location in Évora municipality

Type/electricity

consumption

Peak

(kWh)

Off-peak

(kWh)Total

Gardens 79 304 52 811 132 115

Lighting 2 759 3 459 6 217

Irrigation 67 915 9 504 77 419

Other 29 433 36 100 65 533

Fountains 30 175 42 220 72 394

Electricity consumption of gardens and fountains in 2013 in Évora municipality

(kWh)

Public lighting


WATER SUPPLY, SEWAGEAND MSW SYSTEM

Plant Name of the PlantEnergy consumption

2014 kWhProduction

year 2014 kWhPlant operating hours per day

Quantity of treated sewage

Depurator DEP CESENA 2 907 937 886 322 24 7 177 473

DepuratorDEP PIEVESESTINA

298 265 - 24 466 464 Depurator DEP CALABRINA 23 390 - 24 4 854 Depurator FITO CALABRINA 11 090 - 24 4 980 Depurator FITO BAGNILE 1 785 - 24 3 481

Évora water system facilitiesTrikala Sewage systems (MWh/yr)


SERVICES SECTORBuildings managed by the Municipality

Location of Évora schools

SectorPeak

(MWh)

Off-peak

(MWh)

Total annual

(MWh)

Municipal buildings 394 617 1 011

Education 299 192 491

Dwellings for social housing 31 0 31

Churches and monuments

(lighting) 65 157 222

Sport facilities (e.g. swimming

pools, sports halls) 68 196 264

Leisure (e.g. Teatro Garcia de

Resende) 92 240 332

Electricity consumption of the buildings and equipment’s managed by Évora municipality in

2013


SERVICES SECTOR

Private Buildings

• Retail: Large Food supermarkets and local shops (thosewithin the residential areas);

• Office buildings

•Education: Primary, secondary and college/ University;

• Leisure: Restaurants, hotels and cinemas

• Health: Hospitals and health centers

Location of small services buildings in Évora municipality

Fuel Offices Retail Leisure Education Health

Electricity 116 87 50 26 29

Natural Gas 8 1 26 4 16

LPG 5 242 8 0 0

Gasoline 0 0 0 0 0

Diesel 0 4 0 0 0

Total 128 333 83 29 44

Energy consumption in 2013 (GJ)


ENERGY SUPPLY SYSTEM

Cesena natural gas network

Assessment of RES resource potential

1) Solar technologies (PV and solar water heaters)2) Geothermal (low enthalpy geothermal).4) Wind resources in the city.5) Biogas from the sewage treatment system and thelandfill.6) Biomass in areas surrounding the city.

Geothermal potential in Greece


Due to the growing importance of solar technologies as decentralized energy supply technologies a supplementary assessment was made in order to identify each city technical potential.

Solar technologies

Solar photovoltaic

Rooftop

ResidentialServices

Façade

Residential

Plant size

Solar thermal

Residential

ESTIMATE OF SOLAR POTENTIAL IN

THE CITIESDiverse PV technologies

• Monocrystalline silicon• Multicrystalline silicon• HIT (Heterojunction with

Intrinsic Thin Layer) • Amorphous silicon (non-

transparency type)


Location of PV-track systems for different land scenarios (1 MW project size)

PV utility scale

ESTIMATE OF SOLAR PV POTENTIAL IN

THE CITIES


Dias, L., Lourenço, P., Gouveia, J., Seixas, J. 2016. Interplay between photovoltaic systems potential and agriculture uses. Land Use Policy (under resubmit process after revisions)

Technical potential for all the cities

314 MW

Per Building typologies (Évora)

Per city zone (Nothingham)

ESTIMATE OF SOLAR PV POTENTIAL IN

THE CITIES


CONCLUSIONS (AND RECOMMENDATIONS)

› Challenges on the harmonization of data at different scales (e.g. point data on public lighting to areal information);

› All cities faced some difficulties on data privacy issues from the companies and on response time;

› The data collection allowed a important interaction and engagement with key city stakeholders, and the opportunity for dissemination of the project

› Engage the different city management departments in the early stages of project: data collection and measures co-creation and validation;

› Validate the cost-benefit allocation of work/time to model detail specific sectors/buildings;

› Endogenous renewable energy sources potential assessment is highly important;


THANK YOU

Workshop on Tools and Methodologies for Municipal Sustainable Energy Planning

Kiev, Ukraine

10th and 11th of July 2017CO2

ENERGY &

CLIMATE

New Technologies & Low Carbon Practices

Climate Mitigation/ Adaptation

Consumers Profiles &

Energy Efficiency

Policy Support

Energy Transitions

Integrative Energy City

Planning

Luís Pereira [email protected]


http://www.insmartenergy.com/


DATA COLLECTION OF CITIES’ ENERGY SYSTEMS AND€¦ · Sustainable Energy Planning Kiev, Ukraine...

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Transcript of DATA COLLECTION OF CITIES’ ENERGY SYSTEMS AND€¦ · Sustainable Energy Planning Kiev, Ukraine...