Reliability Evaluation of Multi-Energy Generation and Transmission System With Offshore Wind Power-Photovoltaic-Energy Storage

doi:10.12096/j.2096-4528.pgt.22037

Abstract

Abstract:

The wind-solar-load correlation model is the basis for accurately evaluating the reliability of offshore wind power-photovoltaic-energy storage grid connected system. To solve the problem of high-dimensional wind-solar-load correlation modeling, a hybrid time-varying Copula model based on vine structure was proposed. By combining the actual wind farm output, photovoltaic power station output and grid load data, eight wind-solar-load combined Copula models were established, and the proposed model had more advantages than other models by using two common evaluation criteria of optimal model. Taking the measured data of wind farms and photovoltaic stations in Shandong province as examples, eight groups of models were analyzed and compared in IEEE-RTS79 system with wind farms and photovoltaic stations. The results show that the proposed Copula function model can more accurately describe the multi-dimensional wind-solar-load correlation. However, other existing models underestimate the impact of the wind-solar-load correlation on system reliability. After adding the energy storage device to the test system, other models also have deviations in the selection of the optimal wind-solar installed capacity ratio, the selection of storage power station capacity and the evaluation of power fluctuation.

Key words: offshore wind power, wind-solar-storage system, reliability evaluation, vine structure, mixed time-varying Copula function

CLC Number:

TK 019

Xiaotong GAO, Zhilong QIN, Xinyu GAO. Reliability Evaluation of Multi-Energy Generation and Transmission System With Offshore Wind Power-Photovoltaic-Energy Storage[J]. Power Generation Technology, 2022, 43(4): 626-635.

Figures/Tables 7

Fig. 1 Logic diagram of C-vine structure

Fig. 2 Flowchart of wind-solar-storage power station integrated generation and transmission systems

Tab. 1 Comparison of fitting effects of different models

序号	模型	AIC	BIC
1	单一静态Copula(Gumbel)	-6 584.33	-5 969.10
2	单一时变Copula(时变Gumbel)	-6 710.96	-6 054.15
3	混合静态Copula(Clayton+Gumbel+t)	-6 715.26	-6 079.12
4	混合时变Copula(时变Clayton+时变Gumbel+时变t)	-6 796.75	-6 111.11
5	基于C藤结构的单一静态Copula(Gumbel)	-6 740.26	-6 023.35
6	基于C藤结构的单一时变Copula(时变Gumbel)	-6 814.26	-6 181.22
7	基于C藤结构的混合静态Copula(Clayton+Gumbel+t)	-6 878.35	-6 211.31
8	基于C藤结构的混合时变Copula(时变Rotated Gumbel+时变SJC+时变t)	-6 963.10	-6 277.64

Tab. 2 Reliability index of IEEE-RTS79 system with wind and photovoltaic power stations

模型	PLC	EENS/(MW⋅h/a)
1	0.000 63	663.27
2	0.000 64	670.12
3	0.000 65	673.22
4	0.000 65	681.46
5	0.000 66	688.13
6	0.000 67	702.32
7	0.000 67	691.98
8	0.000 69	722.39

Tab. 3 Influence of different correlation characteristics among wind, solar and load on system reliability

情景	PLC	EENS/(MW⋅h/a)
1	0.000 69	722.35
2	0.000 67	691.64
3	0.000 88	980.23
4	0.000 41	441.56
5	0.000 61	612.35

Tab. 4 Optimal wind-solar installed capacity ratio

模型	最优风光装机容量比例
1	22∶5
2	4∶1
3	17∶4
4	14∶3
5	13∶3
6	18∶5
7	11∶3
8	10∶3

Tab. 5 Risk assessment results of wind-solar-storage system

模型	PLC	EENS/(MW⋅h/a)	$ξ$	$φ$
1	0.000 52	537.3	244	31.8
2	0.000 53	542.3	177	32.3
3	0.000 52	536.1	228	31.9
4	0.000 54	547.2	167	30.7
5	0.000 56	556.8	185	28.8
6	0.000 57	562.4	162	27.5
7	0.000 58	569.2	144	26.3
8	0.000 59	577.6	137	25.2

Tab. 5 Risk assessment results of wind-solar-storage system

模型	PLC	EENS/(MW⋅h/a)	$ξ$	$φ$
1	0.000 52	537.3	244	31.8
2	0.000 53	542.3	177	32.3
3	0.000 52	536.1	228	31.9
4	0.000 54	547.2	167	30.7
5	0.000 56	556.8	185	28.8
6	0.000 57	562.4	162	27.5
7	0.000 58	569.2	144	26.3
8	0.000 59	577.6	137	25.2

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