Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant
Due to market price uncertainty and volatility, electricity sales companies today are facing greater risks in regard to the day-ahead market and the real-time market. Along with introducing the Time of Use (TOU) price for the customer as a type of balancing resource to avoid market risk, electricity...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-01-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/12/1/145 |
| _version_ | 1817996714459529216 |
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| author | Guan Wang Zhongfu Tan Hongyu Lin Qingkun Tan Shenbo Yang Liwei Ju Zhongrui Ren |
| author_facet | Guan Wang Zhongfu Tan Hongyu Lin Qingkun Tan Shenbo Yang Liwei Ju Zhongrui Ren |
| author_sort | Guan Wang |
| collection | DOAJ |
| description | Due to market price uncertainty and volatility, electricity sales companies today are facing greater risks in regard to the day-ahead market and the real-time market. Along with introducing the Time of Use (TOU) price for the customer as a type of balancing resource to avoid market risk, electricity sales companies should adopt the market risk-aversion method to reduce the high cost of ancillary services in the real-time market by using multi-level market transactions, as well as to provide a reference for the profits of power companies. In this paper, we establish a non-linear mathematical model based on stochastic programming by using conditional value-at-risk (CVaR) to measure transaction strategy risk. For the market price and consumer electricity load as the uncertain factors of multi-level market transactions of electricity sales companies, the optimal objective was to maximize the revenue of electricity sales companies and minimize the peak-valley differences in the system, which is solved by using mixed-integer linear programming (MILP). Finally, we provide an example to analyze the effect of the fluctuation degree of customer load and market price on the profit of electricity sales companies under different confidence coefficients. |
| first_indexed | 2024-04-14T02:26:18Z |
| format | Article |
| id | doaj.art-35eb96e8bd604d329d988d08faa5e16a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T02:26:18Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-35eb96e8bd604d329d988d08faa5e16a2022-12-22T02:17:52ZengMDPI AGEnergies1996-10732019-01-0112114510.3390/en12010145en12010145Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage PlantGuan Wang0Zhongfu Tan1Hongyu Lin2Qingkun Tan3Shenbo Yang4Liwei Ju5Zhongrui Ren6School of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaDue to market price uncertainty and volatility, electricity sales companies today are facing greater risks in regard to the day-ahead market and the real-time market. Along with introducing the Time of Use (TOU) price for the customer as a type of balancing resource to avoid market risk, electricity sales companies should adopt the market risk-aversion method to reduce the high cost of ancillary services in the real-time market by using multi-level market transactions, as well as to provide a reference for the profits of power companies. In this paper, we establish a non-linear mathematical model based on stochastic programming by using conditional value-at-risk (CVaR) to measure transaction strategy risk. For the market price and consumer electricity load as the uncertain factors of multi-level market transactions of electricity sales companies, the optimal objective was to maximize the revenue of electricity sales companies and minimize the peak-valley differences in the system, which is solved by using mixed-integer linear programming (MILP). Finally, we provide an example to analyze the effect of the fluctuation degree of customer load and market price on the profit of electricity sales companies under different confidence coefficients.http://www.mdpi.com/1996-1073/12/1/145multi-level marketelectricity sales companyenergy storage plantCVaR |
| spellingShingle | Guan Wang Zhongfu Tan Hongyu Lin Qingkun Tan Shenbo Yang Liwei Ju Zhongrui Ren Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant Energies multi-level market electricity sales company energy storage plant CVaR |
| title | Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant |
| title_full | Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant |
| title_fullStr | Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant |
| title_full_unstemmed | Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant |
| title_short | Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant |
| title_sort | multi level market transaction optimization model for electricity sales companies with energy storage plant |
| topic | multi-level market electricity sales company energy storage plant CVaR |
| url | http://www.mdpi.com/1996-1073/12/1/145 |
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