Power System Expansion Planning Model and Solution Algorithm Based on Load Feasible Region and Reliability Tracking

doi:10.16183/j.cnki.jsjtu.2024.048

Abstract

Abstract:

Power system reliability evaluation is a high-dimensional nonlinear problem, which is difficult to be nested into the power system expansion planning model. This paper proposes a power system expansion planning model and its solution algorithm based on load feasible region model and reliability tracking. First, it proposes an approximate distance model based on load feasible region, which transforms the optimization problem of load shedding calculation required into an equation solving. Based on this, it obtains the analytical expression of reliability sensitivity to components’ capacity and the reliability tracking oriented to capacity. Then, it proposes a reliability-oriented capacity expansion planning model, and a solution algorithm based on reliability tracking and greedy algorithm. The results show that the approximate distance model can effectively reduce the computational complexity of reliability evaluation, while the sensitivity model can accurately reflect the influence of equipment capacity on system reliability, and the capacity expansion planning model and algorithm can achieve optimal system capacity expansion planning results.

Key words: expansion planning, reliability tracking, load feasible region, approximate distance model, greedy algorithm

CLC Number:

TM715

LI Xuan, XIE Kaigui, SHAO Changzheng, HU Bo. Power System Expansion Planning Model and Solution Algorithm Based on Load Feasible Region and Reliability Tracking[J]. Journal of Shanghai Jiao Tong University, 2026, 60(2): 200-210.

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测试系统	方法	LOLP/%	EENS/ (GW·h^-1)	评估时间/s
RBTS	最优潮流模型	0.98	1.06	733
	负荷可行域模型	0.98	1.06	151
	近似距离模型	0.98	1.09	71
RTS-79	最优潮流模型	8.48	127	690
	负荷可行域模型	8.48	127	64
	近似距离模型	8.48	129	18
RTS-96	最优潮流模型	1.38	24.8	1116
	负荷可行域模型	1.38	24.8	24
	近似距离模型	1.38	25.2	15

基准方法	方法	EENS/(GW·h^-1)	误差/%
最优潮流模型	最优潮流模型	24.5	—
	灵敏度模型	24.4	-0.8
近似距离模型	近似距离模型	24.7	—
	灵敏度模型	24.7	0

序号	容量/ MW	所在节点	灵敏度	可靠性跟踪结果/ (MW·h^-1)
1	40	1	-39.31	65.94
2	10	1	-70.74	118.67
3	20	1	-54.50	91.42
4	40	1	-39.22	65.79
5	5	2	-72.61	121.81
6	5	2	-72.64	121.86
7	20	2	-62.90	105.52
8	20	2	-62.71	105.19
9	20	2	-62.94	105.58
10	20	2	-63.16	105.95
11	40	2	-49.03	82.25

排序	考虑峰值负荷		考虑全场景
排序	机组	可靠性跟踪结果/ (MW·h^-1)	机组	可靠性跟踪结果/ (MW·h^-1)
1	94	273.84	60	284.63
2	62	271.83	90	281.45
3	92	271.57	91	281.28
4	60	271.43	93	281.15
5	61	271.43	94	281.14
︙	︙	︙	︙	︙
95	24	149.01	56	97.80
96	57	147.82	22	97.71
97	89	147.37	55	97.12
98	56	146.88	88	97.06
99	90	144.73	23	96.51

序号	起始节点	终止节点	灵敏度	可靠性跟踪结果/ (MW·h^-1)
1	1	2	-3.03×10^-2	0.051
2	1	3	-3.54×10^-2	0.059
3	1	3	-3.54×10^-2	0.059
4	2	4	-1.38	2.305
5	2	4	-1.38	2.305
6	3	4	0	0
7	3	5	0	0
8	4	5	0	0
9	5	6	0	0