An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators
This research aims to devise a methodology for optimizing the size of a Battery Energy Storage System (BESS) supporting Wind Energy Systems (WES) to enhance power commitment flexibility in the energy market. The methodology involves three essential steps: (i) estimating rated kW, (ii) initializing r...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10458937/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841563304481259520 |
|---|---|
| author | Shubham Kashyap Tirthadip Ghose |
| author_facet | Shubham Kashyap Tirthadip Ghose |
| author_sort | Shubham Kashyap |
| collection | DOAJ |
| description | This research aims to devise a methodology for optimizing the size of a Battery Energy Storage System (BESS) supporting Wind Energy Systems (WES) to enhance power commitment flexibility in the energy market. The methodology involves three essential steps: (i) estimating rated kW, (ii) initializing rated kWh of the BESSs, and (iii) iteratively adjusting the BESS size based on heuristic rules to prevent State of Charge (SoC) limit violations following the load cycle. Three realistic load cycles for the BESSs out of which one load cycle is generated based on maximum error values and the other load cycles are generated based on the mean and <inline-formula> <tex-math notation="LaTeX">$1\sigma $ </tex-math></inline-formula> of the Normal Distribution Curve (NDC) of forecast errors of WES located at Agasthianpalli, Tamil Nadu, India. Two simple yet effective heuristic rules have been proposed to optimize the BESS size, ensuring maximum SoC at the start of each day and maintaining SoC within limits throughout the day. This leads to two scenarios considering a single set of the BESS to serve the load cycle and two sets of the BESS operating alternatively, reaching maximum SoC on the subsequent day by charging from the grid. Cost analysis indicates that scenario 1 is more favorable in terms of both cost and BESS size, surpassing scenario 2 by 8.89% and 9.95%, respectively. This analysis results in shorter payback period for scenario 1. Validation using Genetic Algorithm (GA) is done by comparing the costs of BESSs, emphasizing the suitability of the proposed technique. |
| format | Article |
| id | doaj-art-8ad64667b10c4ba1a8bb4c7c523c86f0 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-8ad64667b10c4ba1a8bb4c7c523c86f02025-01-03T00:01:40ZengIEEEIEEE Access2169-35362025-01-011398099410.1109/ACCESS.2024.337305610458937An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind GeneratorsShubham Kashyap0https://orcid.org/0009-0005-3583-6566Tirthadip Ghose1https://orcid.org/0000-0002-7561-3157Department of Electrical and Electronics Engineering, Birla Institute of Technology–Mesra, Ranchi, IndiaDepartment of Electrical and Electronics Engineering, Birla Institute of Technology–Mesra, Ranchi, IndiaThis research aims to devise a methodology for optimizing the size of a Battery Energy Storage System (BESS) supporting Wind Energy Systems (WES) to enhance power commitment flexibility in the energy market. The methodology involves three essential steps: (i) estimating rated kW, (ii) initializing rated kWh of the BESSs, and (iii) iteratively adjusting the BESS size based on heuristic rules to prevent State of Charge (SoC) limit violations following the load cycle. Three realistic load cycles for the BESSs out of which one load cycle is generated based on maximum error values and the other load cycles are generated based on the mean and <inline-formula> <tex-math notation="LaTeX">$1\sigma $ </tex-math></inline-formula> of the Normal Distribution Curve (NDC) of forecast errors of WES located at Agasthianpalli, Tamil Nadu, India. Two simple yet effective heuristic rules have been proposed to optimize the BESS size, ensuring maximum SoC at the start of each day and maintaining SoC within limits throughout the day. This leads to two scenarios considering a single set of the BESS to serve the load cycle and two sets of the BESS operating alternatively, reaching maximum SoC on the subsequent day by charging from the grid. Cost analysis indicates that scenario 1 is more favorable in terms of both cost and BESS size, surpassing scenario 2 by 8.89% and 9.95%, respectively. This analysis results in shorter payback period for scenario 1. Validation using Genetic Algorithm (GA) is done by comparing the costs of BESSs, emphasizing the suitability of the proposed technique.https://ieeexplore.ieee.org/document/10458937/Battery energy storage systemsbattery sizingstate of chargewind generationheuristic-based technique |
| spellingShingle | Shubham Kashyap Tirthadip Ghose An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators IEEE Access Battery energy storage systems battery sizing state of charge wind generation heuristic-based technique |
| title | An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators |
| title_full | An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators |
| title_fullStr | An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators |
| title_full_unstemmed | An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators |
| title_short | An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators |
| title_sort | iterative heuristic optimization method for the optimum sizing of battery energy storage system to augment the dispatchability of wind generators |
| topic | Battery energy storage systems battery sizing state of charge wind generation heuristic-based technique |
| url | https://ieeexplore.ieee.org/document/10458937/ |
| work_keys_str_mv | AT shubhamkashyap aniterativeheuristicoptimizationmethodfortheoptimumsizingofbatteryenergystoragesystemtoaugmentthedispatchabilityofwindgenerators AT tirthadipghose aniterativeheuristicoptimizationmethodfortheoptimumsizingofbatteryenergystoragesystemtoaugmentthedispatchabilityofwindgenerators AT shubhamkashyap iterativeheuristicoptimizationmethodfortheoptimumsizingofbatteryenergystoragesystemtoaugmentthedispatchabilityofwindgenerators AT tirthadipghose iterativeheuristicoptimizationmethodfortheoptimumsizingofbatteryenergystoragesystemtoaugmentthedispatchabilityofwindgenerators |