Two-Stage Stochastic Optimal Voltage Control of High-Proportional Photovoltaic Distribution Networks Considering Auxiliary Power to Hydrogen

doi:10.11930/j.issn.1004-9649.202307084

Abstract

Abstract:

To address the problems such as limited regulation resources, high regulation costs, and slow response speed in traditional distribution network voltage control methods, a two-stage stochastic optimal control strategy with participations of power-to-hydrogen (P2H) devices is investigated. Firstly, voltage regulation device operation constraints and distribution network line constraints are modeled. Then a two-stage day-ahead and intra-day voltage optimal control model is developed considering electrolytic gas production revenue. Secondly, to deal with the voltage fluctuations or even over-limitation problem caused by short-term disturbances of renewables and load demands, typical operation scenarios of distribution networks are constructed by adopting Latin hypercube sampling and Kantorovich distance reduction techniques. Then the voltage control strategy is solved by minimizing the expectation of intraday-stage objective functions under all scenarios. Finally, case studies have shown that compared with the traditional voltage methods without considering P2H participations, the voltage over-limitation can be effectively avoided and the total regulation costs can be reduced by over 26.43% by using the proposed method.

Key words: power to hydrogen, distribution network, coordinated voltage control, stochastic optimization, uncertainties

Yajian ZHANG, Ci CHEN, Fei XUE, Li MA, Min ZHENG. Two-Stage Stochastic Optimal Voltage Control of High-Proportional Photovoltaic Distribution Networks Considering Auxiliary Power to Hydrogen[J]. Electric Power, 2024, 57(8): 23-35.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202307084

https://www.electricpower.com.cn/EN/Y2024/V57/I8/23

Figures/Tables 17

Fig.1 Power to hydrogen schematic

Fig.2 Overall architecture of two-stage distribution network voltage control

Fig.3 Flowchart of proposed two-stage voltage control strategy

Fig.4 IEEE 33-node distribution network topology

Fig.5 Day-ahead forecasted data

Fig.6 Voltage profiles in different scenarios

Fig.7 Positions of OLTC in different scenarios

Fig.8 Switching number of CB in different scenarios

Fig.9 Power consumptions of P2H in different scenarios

Fig.10 SOC performances of ESSs in different scenarios

Table 1 Control costs for day-ahead optimization 单位：元

场景	总成本	网损成本	动作成本	电压越限成本	ESS调节成本	PV调节成本	弃光成本	P2H成本	氢气收益	氧气收益
1	648.2304	474.7340	11.96	3.9781	57.9824	30.5732	69.0027	0	0	0
2	571.3278	404.1624	6.46	0	34.5929	30.0528	69.0027	125.0945	98.0375	0
3	476.8993	415.8795	0.96	0	28.2351	30.0528	69.0027	219.5796	172.0863	114.7242

Fig.11 Voltage profiles using single-stage control method without considering P2H[8]

Fig.12 Voltage profiles using two-stage control method without considering P2H[9]

Fig.13 Voltage profiles using proposed method in this paper considering P2H

Fig.14 Voltage profiles under 40% PV penetrations

Table 2 Control costs of different methods 单位：元

控制方法	总成本	网损成本	动作成本	电压越限成本	ESS调节成本	PV调节成本	弃光成本	P2H成本	氢气收益	氧气收益
1	1997.7420	1855.6314	17.46	0	131.2100	40.7963	305.7374	1153.2174	903.7681	602.5121
2	2469.3280	1817.6913	17.46	0	142.3366	40.7963	305.7374	671.8061	526.4997	0
3	2827.6092	2270.4256	11.96	1.3876	186.3669	51.7318	305.7374	0	0	0

Fig.15 Voltage profiles considering wind curtailment costs

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