Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear Programming
The objective of this study is to perform peak load shaving at a virtual power plant (VPP) to maximize the electricity cost-saving for local distribution companies (LDCs) while satisfying the necessary operational constraints. It can be achieved by implementing an efficient algorithm to control the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/21/3610 |
| _version_ | 1797468530916982784 |
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| author | Hossam Mosbah Eduardo Castillo Guerra Julian L. Cardenas Barrera |
| author_facet | Hossam Mosbah Eduardo Castillo Guerra Julian L. Cardenas Barrera |
| author_sort | Hossam Mosbah |
| collection | DOAJ |
| description | The objective of this study is to perform peak load shaving at a virtual power plant (VPP) to maximize the electricity cost-saving for local distribution companies (LDCs) while satisfying the necessary operational constraints. It can be achieved by implementing an efficient algorithm to control the conservation voltage reduction technique (CVR) with embedded energy resources (EERs) to optimize electricity costs during peak hours. EERs consist of distributed energy resources (DERs) such as solar and diesel generators and energy storage systems (ESSs) such as utility-scale and residential batteries. An objective function of mixed integer linear programming is formulated as the electricity cost function. Different operational constraints of EERs are formulated to solve the peak shaving optimization problem. The proposed algorithm is tested using data from a real Australian power distribution network. This paper discusses four cases to demonstrate the performance and economic benefits of the control algorithm. Each of these cases illustrates how EERs contribute differently each year, month, and day. Results showed that the proposed algorithm offers significant cost savings and can shave up to three daily peaks. |
| first_indexed | 2024-03-09T19:07:45Z |
| format | Article |
| id | doaj.art-bf5b13c589004cd5b972d0f035f789ae |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T19:07:45Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-bf5b13c589004cd5b972d0f035f789ae2023-11-24T04:26:42ZengMDPI AGElectronics2079-92922022-11-011121361010.3390/electronics11213610Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear ProgrammingHossam Mosbah0Eduardo Castillo Guerra1Julian L. Cardenas Barrera2Department of Electrical & Computer Engineering, University of New Brunswick (UNB), Fredericton, NB E3B 5A3, CanadaDepartment of Electrical & Computer Engineering, University of New Brunswick (UNB), Fredericton, NB E3B 5A3, CanadaDepartment of Electrical & Computer Engineering, University of New Brunswick (UNB), Fredericton, NB E3B 5A3, CanadaThe objective of this study is to perform peak load shaving at a virtual power plant (VPP) to maximize the electricity cost-saving for local distribution companies (LDCs) while satisfying the necessary operational constraints. It can be achieved by implementing an efficient algorithm to control the conservation voltage reduction technique (CVR) with embedded energy resources (EERs) to optimize electricity costs during peak hours. EERs consist of distributed energy resources (DERs) such as solar and diesel generators and energy storage systems (ESSs) such as utility-scale and residential batteries. An objective function of mixed integer linear programming is formulated as the electricity cost function. Different operational constraints of EERs are formulated to solve the peak shaving optimization problem. The proposed algorithm is tested using data from a real Australian power distribution network. This paper discusses four cases to demonstrate the performance and economic benefits of the control algorithm. Each of these cases illustrates how EERs contribute differently each year, month, and day. Results showed that the proposed algorithm offers significant cost savings and can shave up to three daily peaks.https://www.mdpi.com/2079-9292/11/21/3610energy storage systemdistrusted energy resourcesvirtual power plantoptimizationpeak load shavingpeak load leveling |
| spellingShingle | Hossam Mosbah Eduardo Castillo Guerra Julian L. Cardenas Barrera Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear Programming Electronics energy storage system distrusted energy resources virtual power plant optimization peak load shaving peak load leveling |
| title | Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear Programming |
| title_full | Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear Programming |
| title_fullStr | Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear Programming |
| title_full_unstemmed | Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear Programming |
| title_short | Maximizing the Electricity Cost-Savings for Local Distribution System Using a New Peak-Shaving Approach Based on Mixed Integer Linear Programming |
| title_sort | maximizing the electricity cost savings for local distribution system using a new peak shaving approach based on mixed integer linear programming |
| topic | energy storage system distrusted energy resources virtual power plant optimization peak load shaving peak load leveling |
| url | https://www.mdpi.com/2079-9292/11/21/3610 |
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