Battery Storage Utility

Grid Controller

North Carolina State University Christen Pischke, Erin Fenton, Prince Patel, Ryan Cooper

Bobby Compton, Kevin Chen, Mesut Baran, Steven Whisenant

● NC State Senior Design Intro

● Battery Controller Product Overview ○ System Architecture

○ User Interface

○ Battery Management Tool

● Battery Chemistry Selection

● Circuit Data & Simulation Validation

● Circuit Operational Issues

● BESS Control Scheme Recommendations ○ Results

○ Cost & Benefit Analysis

● Challenges & Future Optimization

Outline

NCSU Senior Design

● Two-semester course that introduces students to the product development

process

● Students are instructed on:

○ Market Research

○ System Engineering

○ Project Planning and Management

○ Team Building

BESS Management Tool Matlab

Matlab Battery Controller

User Battery Parameters ● Battery Type ● Scheme ● Power ● SOC Limitations

Circuit Measurement Inputs ● Load Data ● Solar Data

OpenDSS Circuit Model

● Time-series Simulation Data

User Input ● Pricing Models ● Battery Rating

Outputs ● Losses Reduction ● Cost Savings ● Upgrade Deferral

Outputs ● kW/kWh ● State of Charge

User Interface

Circuit Inputs

● User Data

● Simulation Run Times

● Solar Generation Model

Battery Inputs

● Battery Chemistry

● Battery Rating

Simulation Inputs

● Create Monitors

● Plot Circuit Diagram

Energy Time Shift PV Smoothing PV Firming

Matlab Battery Controller

❏ Charge from solar generation

during time of low demand

❏ Discharge stored generation

during optimal time window

❏ Decrease fluctuation in solar

output over small time intervals

❏ Charge and discharge based

on the moving average of solar

output

❏ Charge battery from solar

overproduction during daytime

❏ Discharge stored generation

when solar farm does not

produce rated capacity (MW)

Lead Acid Li- Ion

Initial Cost* $255/kWh $300/kWh

Life Cycles 1400 5475

Efficiency Range* 60-100% 92-100%

Preferred Applications* Residential Solar, Slow

Charge/Discharge applications

PV Firming, Energy Time-

Shifting, Peak Demand

Reduction

Selecting Battery Chemistry

*Our preliminary product will take these factors into consideration in order to choose optimal battery type for each

application.

[3]

Modeling Battery Chemistry - Efficiency vs. Discharge Time

Cost Analysis - Time Shifting Method

Purpose: To analyze the economic impact of

integrating the BESS with the circuit.

Economic Dispatch Pricing Model:

Pricing is based on

power measured at

substation.

Off-Peak: < 3MW

Semi-Peak: 3-5 MW

Peak: > 5MW

Calculated Outputs:

❖ Upgrade Deferral ➢ Assume 2% annual load growth

without solar growth

❖ Cost Savings ➢ Price difference between the two

circuit loads (Base and BESS)

❖ Losses Reduction ➢ Reduction in system losses due to

the addition of battery storage

Inputs

Data Manipulation & Circuit Validation

5 min - 8.7% error

1. Standardized imported data

● Cleaned and configured any errors

● Interpolated for both 1 min and 5 min

sampling rates

2. Defined correct Load Profiles

● Extracted Solar data from Real Power

Load data

● Created per unit loadshape values

based total circuit load

3. Readied inputs for time-series simulation

● User defined data range, date range,

and sampling rate

● Updated system and generation

loadshapes

Head of Feeder

1 min - 22% error

5 min - 2.4% error

Solar Farm

1 min - 6.5% error

Circuit Issues

Solar Variability

High Voltage

Reverse Power Flow

Recommendation 1- Time-Shifting Scheme

Recommended Battery Ratings

● 3 - 5 MW

● 6 - 8 MWh

● Keep close to solar farm

Goals

● Discharge at peak demand times

● Minimize the battery size

● Reduce reverse power flow

Charging and Discharging Method

● Charges when solar output is greater

than demand

● Discharges at user-selected time

intervals

Time-Shifting Scheme

Test Case #1

(July 18th, 2016)

Substation Monitor

Battery Details

● 3 MW / 6 MWh

● Located at Solar Farm

● Discharges between 5

- 11 pm

Legend

Blue - No Battery

Red - Battery

No Battery Battery

Time-Shifting Scheme

Test Case #2

(December 21st, 2016)

Substation Monitor

Legend

Blue - No Battery

Red - Battery

Battery Details

● 3 MW / 6 MWh

● Located at Solar Farm

● Discharges between

3:30 - 8:30 am

No Battery Battery

Base Circuit Time Shifting

Battery Rating No Battery 3MW/6MWh

Substation Load 2.00GWh 1.83GWh

Cost of Energy $6,348,662.90 $4,799,181.98

Cost Savings N/A $1,549,480.92

Losses Reduction N/A 3,158kWh

Upgrade Deferral N/A 6 years

Simulation Period: July 2016

Battery Used: Lithium-Ion ($300/kWh)

Economic Dispatch Assumed Costs: Off-Peak: $0.50/kWh

Semi-Peak: $1.88/kWh

Peak: $7.50/kWh

Cost Analysis - Simulation Results

Recommendation 2- Preliminary PV Firming Scheme

Goals

● Keep solar farm output under contracted MW limit

● Maximize solar farm energy savings & compliance

Charging and Discharging Method

● Charges solar during morning (6-9am)

● At peak production (10-5pm):

○ Charges when output exceeds MW limit

○ Discharges when output is under

contracted MW limit

● Discharges in evening (5pm-7pm)

Battery Recommendations

● Located inside solar farm

● 1-3MW / 2-10MWh

● Cost Analysis Tool will determine battery type

Assumptions

● 10% solar overproduction on DC side

● Contracted MW limit is 3.3MW

Solar Farm Output (kW)

Legend

Blue - No Battery

Red - Battery

Test Case Details:

Simulation Date - June 06, 2016

Battery Rating - 2MW/6MWh

Farm Rating: 5MW

Contracted MW Limit: 3.3MW

Charge Window - 6am-9am

PV Firming- Energy (kWh) Savings Product Output

* Preliminary benefit analysis for 07/30/06-07/31/06.

Subject to change after product testing and debugging

stage. Final product deliverable deadline of 11/27.

Legend

Blue - kWh in

Red - kWh out

Energy Savings for Developer: 981.23 kWh for 06/06

Energy Output of BES (kWh)

Test Case Details:

Simulation Date - June 06, 2016

Battery Rating - 2MW/6MWh

Farm Rating: 5MW

Contracted MW Limit: 3.3MW

Charge Window - 6am-9am

Challenges

Code

● Improve code efficiency and run-time

Battery Schemes

● Incorporate PV Smoothing Scheme

● Incorporate ramp rate control

● Implement battery efficiency look-up tables

User Manual

● Create a detailed user manual

General

● Export output data for future reference

Future Product Optimization

● OpenDSS Learning curve

● Errors in measured data

● Handling large amounts of data

● Battery modeling/chemistry depth

● Integration of subsystems

● Creating versatile and user friendly product

Thank You Grid PV

Duke Energy Sponsors

Kevin Chen

Steven Whisenant

Senior Design Mentors

Mesut Baran

Bobby Compton

Additional Help

Lisha Sun and Qian Long

Clemson Senior Design Team

References

Articles [1] M. Z. Daud, A. Mohamed, M. Wanik, M. Hannan. “Performance evaluation of grid-connected photovoltaic system with battery

energy storage”, IEEE International Conference on Power and Energy. DOI: //dx.doi.org/10.1109/PECon.2012.6450234.

[2] S. K. Solanki, V. Ramachandran. “Modeling of Utility Distribution Feeder in OpenDSS and Steady State Impact analysis of

Distributed Generation,” West Virginia University.

Images [1] https://research.ece.ncsu.edu/seniordesign/

[2] https://research.ece.ncsu.edu/seniordesign/

[3] Costs of Batteries from page 9 of: https://www.nrel.gov/docs/fy16osti/64987.pdf