Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources
Abstract The virtual power plant integrating the flexible resources in the distribution network can provide additional adjustment capacity for the auxiliary services of distribution network. However, the actual internal situation of distribution network including insufficient adjustable capacity of...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-12-01
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| Series: | IET Renewable Power Generation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/rpg2.13127 |
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| _version_ | 1832579824791584768 |
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| author | Zejian Qiu Xin Zhang Zhanyuan Han Fengchao Chen Yuxin Luo Kuan Zhang |
| author_facet | Zejian Qiu Xin Zhang Zhanyuan Han Fengchao Chen Yuxin Luo Kuan Zhang |
| author_sort | Zejian Qiu |
| collection | DOAJ |
| description | Abstract The virtual power plant integrating the flexible resources in the distribution network can provide additional adjustment capacity for the auxiliary services of distribution network. However, the actual internal situation of distribution network including insufficient adjustable capacity of energy storage, unreasonable power allocation, and voltage overrun leads to the difficulties in optimization scheduling. Therefore, this paper proposes a power allocation optimization strategy of distributed electricity‐H2 virtual power plants (EHVPPs) with aggregated flexible resources. Specifically, a distributed EHVPP division method based on the granular K‐medoids clustering algorithm is proposed to realize the independent autonomy and coordinated interaction between EHVPPs, and in order to quantify the operation and regulation capacity of distributed EHVPPs, an aggregation approach of regulating feasible domains of flexibility resources based on the improved zonotope approximations is developed. Moreover, a power allocation strategy based on the flexibility weight factor is proposed to handle the calculated minimum deviation between the total active output of PV and the dispatching power command, realizing the self‐consistency of distributed EHVPPs. Comparative studies have demonstrated the superior performance of the proposed methodology in economic merits and self‐consistency efficiency. |
| format | Article |
| id | doaj-art-bb5d9aeab8c74f39a03ba00f4a7d03fa |
| institution | Kabale University |
| issn | 1752-1416 1752-1424 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Renewable Power Generation |
| spelling | doaj-art-bb5d9aeab8c74f39a03ba00f4a7d03fa2025-01-30T12:15:54ZengWileyIET Renewable Power Generation1752-14161752-14242024-12-0118164034404610.1049/rpg2.13127Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resourcesZejian Qiu0Xin Zhang1Zhanyuan Han2Fengchao Chen3Yuxin Luo4Kuan Zhang5Guangdong Power Grid Corp Dongguan Power Supply Bureau Dongguan Guangdong ChinaGuangdong Power Grid Corp Dongguan Power Supply Bureau Dongguan Guangdong ChinaGuangdong Power Grid Corp Dongguan Power Supply Bureau Dongguan Guangdong ChinaGuangdong Power Grid Corp Dongguan Power Supply Bureau Dongguan Guangdong ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing ChinaAbstract The virtual power plant integrating the flexible resources in the distribution network can provide additional adjustment capacity for the auxiliary services of distribution network. However, the actual internal situation of distribution network including insufficient adjustable capacity of energy storage, unreasonable power allocation, and voltage overrun leads to the difficulties in optimization scheduling. Therefore, this paper proposes a power allocation optimization strategy of distributed electricity‐H2 virtual power plants (EHVPPs) with aggregated flexible resources. Specifically, a distributed EHVPP division method based on the granular K‐medoids clustering algorithm is proposed to realize the independent autonomy and coordinated interaction between EHVPPs, and in order to quantify the operation and regulation capacity of distributed EHVPPs, an aggregation approach of regulating feasible domains of flexibility resources based on the improved zonotope approximations is developed. Moreover, a power allocation strategy based on the flexibility weight factor is proposed to handle the calculated minimum deviation between the total active output of PV and the dispatching power command, realizing the self‐consistency of distributed EHVPPs. Comparative studies have demonstrated the superior performance of the proposed methodology in economic merits and self‐consistency efficiency.https://doi.org/10.1049/rpg2.13127electric power generationenergy consumption |
| spellingShingle | Zejian Qiu Xin Zhang Zhanyuan Han Fengchao Chen Yuxin Luo Kuan Zhang Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources IET Renewable Power Generation electric power generation energy consumption |
| title | Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources |
| title_full | Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources |
| title_fullStr | Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources |
| title_full_unstemmed | Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources |
| title_short | Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources |
| title_sort | power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources |
| topic | electric power generation energy consumption |
| url | https://doi.org/10.1049/rpg2.13127 |
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