Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm Optimization
We present a day-ahead scheduling strategy for an Energy Storage System (ESS) in a microgrid using two algorithms - Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The scheduling strategy aims to minimize the cost paid by consumers in a microgrid subject to dynamic pricing. We define a...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9201434/ |
| _version_ | 1831678311115259904 |
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| author | Ajay Raghavan Paarth Maan Ajitha K. B. Shenoy |
| author_facet | Ajay Raghavan Paarth Maan Ajitha K. B. Shenoy |
| author_sort | Ajay Raghavan |
| collection | DOAJ |
| description | We present a day-ahead scheduling strategy for an Energy Storage System (ESS) in a microgrid using two algorithms - Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The scheduling strategy aims to minimize the cost paid by consumers in a microgrid subject to dynamic pricing. We define an objective function for the optimization problem, present its search space, and study its structural properties. We prove that the search space has a magnification of at least 50 × (B<sub>c</sub> - B<sub>d</sub> + 1), where Bc and Bd are the maximum depths of charge and discharge in an hour (in percentage) of the ESS respectively. In a simulation involving load, energy generation, and grid price forecasts for three microgrids of different sizes, we obtain ESS schedules that provide average cost reductions of 11.31% (using GA) and 14.31% (using PSO) over the ESS schedule obtained using Net Power Based Algorithm. |
| first_indexed | 2024-12-20T04:57:27Z |
| format | Article |
| id | doaj.art-97e502d653754a8e848926b69a9a76e4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T04:57:27Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-97e502d653754a8e848926b69a9a76e42022-12-21T19:52:41ZengIEEEIEEE Access2169-35362020-01-01817306817307810.1109/ACCESS.2020.30256739201434Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm OptimizationAjay Raghavan0https://orcid.org/0000-0001-6309-0160Paarth Maan1https://orcid.org/0000-0001-9622-3070Ajitha K. B. Shenoy2https://orcid.org/0000-0003-3995-1826Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaDepartment of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaDepartment of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaWe present a day-ahead scheduling strategy for an Energy Storage System (ESS) in a microgrid using two algorithms - Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The scheduling strategy aims to minimize the cost paid by consumers in a microgrid subject to dynamic pricing. We define an objective function for the optimization problem, present its search space, and study its structural properties. We prove that the search space has a magnification of at least 50 × (B<sub>c</sub> - B<sub>d</sub> + 1), where Bc and Bd are the maximum depths of charge and discharge in an hour (in percentage) of the ESS respectively. In a simulation involving load, energy generation, and grid price forecasts for three microgrids of different sizes, we obtain ESS schedules that provide average cost reductions of 11.31% (using GA) and 14.31% (using PSO) over the ESS schedule obtained using Net Power Based Algorithm.https://ieeexplore.ieee.org/document/9201434/Microgridenergy storage systemdynamic pricingscheduling strategyoptimizationgenetic algorithm |
| spellingShingle | Ajay Raghavan Paarth Maan Ajitha K. B. Shenoy Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm Optimization IEEE Access Microgrid energy storage system dynamic pricing scheduling strategy optimization genetic algorithm |
| title | Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm Optimization |
| title_full | Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm Optimization |
| title_fullStr | Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm Optimization |
| title_full_unstemmed | Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm Optimization |
| title_short | Optimization of Day-Ahead Energy Storage System Scheduling in Microgrid Using Genetic Algorithm and Particle Swarm Optimization |
| title_sort | optimization of day ahead energy storage system scheduling in microgrid using genetic algorithm and particle swarm optimization |
| topic | Microgrid energy storage system dynamic pricing scheduling strategy optimization genetic algorithm |
| url | https://ieeexplore.ieee.org/document/9201434/ |
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