battery storage utility grid...
TRANSCRIPT
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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
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● 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
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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
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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
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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
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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)
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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]
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Modeling Battery Chemistry - Efficiency vs. Discharge Time
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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
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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
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Circuit Issues
Solar Variability
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High Voltage
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Reverse Power Flow
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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
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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
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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
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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
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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
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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
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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
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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
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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