Optimization Operation of Integrated Energy Station Coordinating the Interests of Distributed Generation Provider and Load Users

doi:10.11930/j.issn.1004-9649.202503005

Abstract

Abstract:

To promote the utilization of renewable resources and improve economic interests of different subjects, here proposes a method for optimization operation strategy of Integrated Energy Station that coordinating different subject interests. Firstly, some demand response models for various loads were established by considering load uncertainty and time series electricity prices, based on the analysis of energy flow relationship of different subjects and the impact of demand response. Secondly, through introduction of carbon trading, her constructed three objective functions with the maximum net profit of Integrated Energy Station, the new energy consumption rate and the user's satisfaction. Thirdly, according to high dimensional and nonlinear features of the proposed objective, an improved multi-objective decomposition evolution algorithm is proposed by employing penalty function and polynomial mutation strategy. The simulation experiment shows that the proposed optimization model can increase the net revenue of the integrated energy station by 9.39%, the consumption rate of new energy by 8.18%and user satisfaction by 5.81%.

Key words: integrated energy station, decompose multi-objective evolutionary algorithms, load response, distributed generator

JIA Dongli, REN Zhaoying, LIU Keyan, WANG Zezhou, XIE Yifeng, YANG Kaitong, YIN Zhongdong. Optimization Operation of Integrated Energy Station Coordinating the Interests of Distributed Generation Provider and Load Users[J]. Electric Power, 2025, 58(12): 128-136.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202503005

https://www.electricpower.com.cn/EN/Y2025/V58/I12/128

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References 37

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参数	数值	参数	数值
$P_{{\text{GT}}}^{{\text{Eq,min}}}, P_{{\text{GT}}}^{{\text{Eq,max}}}/{\text{kW}}$	0, 600	${a_{\text{E}}}$	0.001 3
$P_{{\text{GB}}}^{{\text{Eq,min}}}, P_{{\text{GB}}}^{{\text{Eq,max}}}/{\text{kW}}$	0, 800	${b_{\text{E}}}$	0.160 0
$P_{{\text{WHB}}}^{{\text{Eq,min}}}, P_{{\text{WHB}}}^{{\text{Eq,max}}}/{\text{kW}}$	0, 930	${c_{\text{E}}}$	0
$ \beta _{}^{{\text{down}}},\beta _{}^{{\text{up}}}/{\text{kW}} $	300, 300	${a_{\text{H}}}$	0.000 5
$P_{}^{{\text{Dis,max}}}, P_{}^{{\text{Chr,max}}}/{\text{kW}}$	250, 250	${b_{\text{H}}}$	0.110 0
$ S_{ \rm OC}^{{\text{min}}}, S_{ \rm OC}^{\max }/{\text{kW}} $	130, 590	${c_{\text{H}}}$	0

参数	数值	参数	数值
$P_{{\text{GT}}}^{{\text{Eq,min}}}, P_{{\text{GT}}}^{{\text{Eq,max}}}/{\text{kW}}$	0, 600	${a_{\text{E}}}$	0.001 3
$P_{{\text{GB}}}^{{\text{Eq,min}}}, P_{{\text{GB}}}^{{\text{Eq,max}}}/{\text{kW}}$	0, 800	${b_{\text{E}}}$	0.160 0
$P_{{\text{WHB}}}^{{\text{Eq,min}}}, P_{{\text{WHB}}}^{{\text{Eq,max}}}/{\text{kW}}$	0, 930	${c_{\text{E}}}$	0
$ \beta _{}^{{\text{down}}},\beta _{}^{{\text{up}}}/{\text{kW}} $	300, 300	${a_{\text{H}}}$	0.000 5
$P_{}^{{\text{Dis,max}}}, P_{}^{{\text{Chr,max}}}/{\text{kW}}$	250, 250	${b_{\text{H}}}$	0.110 0
$ S_{ \rm OC}^{{\text{min}}}, S_{ \rm OC}^{\max }/{\text{kW}} $	130, 590	${c_{\text{H}}}$	0

场景	综合能源站净收益/元	新能源消纳率/%	用户满意度/%	碳排放量/kg
1	7 053.39	83.43	100.00	26 344.21
2	7 479.62	87.01	89.16	24 907.53
3	7 386.90	91.28	92.06	24 370.20

场景	综合能源站净收益/元	新能源消纳率/%	用户满意度/%	碳排放量/kg
1	7 053.39	83.43	100.00	26 344.21
2	7 479.62	87.01	89.16	24 907.53
3	7 386.90	91.28	92.06	24 370.20

算法	综合能源站净收益/元	新能源消纳率/%	用户满意度/%
NSGA-II	6 753.04	83.10	86.25
传统MOEAD	7 273.02	90.57	91.33
IMOEAD	7 386.90	91.28	92.06