Day-Ahead Robust Optimal Scheduling of Hydro-Wind-PV-Storage Complementary System Considering the Steadiness of Power Delivery
Guo Yi1, Ming Bo1, Huang Qiang1, Wang Yimin1, Li Yunlong2
1. State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China Xi'an University of Technology Xi'an 710048 China; 2. Power China Northwest Engineering Corporation Limited Xi'an 710065 China
Abstract：Complementary operation and bundled delivery of large-scale hydro-wind-photovoltaic (PV)-storage systems is an important way to promote new energy consumption. The distribution of power sources and load demand is uneven in China, and UHV DC is usually applied to transmit the clean electricity from western regions to the eastern load center. However, decision variables of the optimal scheduling model for traditional complementary systems are generally the power output of adjustable power sources. This makes it difficult to satisfy the steady requirement of UHV DC power delivery, particularly for systems including cascade hydropower plants with complex hydraulic connections. Meanwhile, the day-ahead generation scheduling of the complementary system need to address forecast uncertainties of the wind and PV power. To address these issues, this paper proposes a day-ahead robust generation scheduling approach for hydro-wind-PV-storage complementary systems while considering the steady requirement of power delivery. Firstly, scenario generation (Latin Hypercube Sampling) and scenario reduction (Simultaneous Backward Reduction) methods are used to obtain the representative scenarios of wind and PV power output to characterize their forecast uncertainties. Then, considering the electricity production and peak-shaving performance of the system, a day-ahead multi-objective robust optimization scheduling model for the hydro-wind-PV-storage complementary systems is established. Finally, a two-layer nested optimization framework is developed to solve this model. In the outer layer, an intelligent algorithm based on a two-dimensional encoding strategy is used to optimize the delivered power of the system, which ensure the steadiness of power delivery and reduce the number of the decision variables. In the inner layer, under the given delivered power, discriminant coefficient and relative water storage rate are applied to determine the load dispatch strategies among cascade hydropower plants and state of charge of battery storage plants. In this model, the derived day-ahead generation schedule can ensure the steady requirement of power delivery, and give full play the flexibility of cascade hydropower and battery storage plants and reduce the effects of forecast uncertainties of wind and PV power. “Qinghai-Henan” UHV DC project in clean energy base of the upper Yellow river basin is selected as a case study. Results show that the formulated power delivery curves presents a stair-shape, and the power in each operation stage is steady, which satisfies the steady requirement of power delivery. The output of the complementary system can track the load demand variation as much as possible to enhance the peak shaving performance of the system. The standard deviation of residual load decreases by 44%, 13.3%, 25% and 46% respectively in each typical day. Although the generation schedule with better electricity production and peak-shaving performance can be obtained by deterministic optimization model, it is difficult to cope with the forecast uncertainties of wind and PV power, while robust optimization model can effectively utilize the flexibility of cascade hydropower and battery storage, and avoid the electricity curtailment and power shortage risk of the system. Comparisons of different battery storage configuration ratio show that the operation performance of the complementary system increases with the increase of battery storage configuration ratio, especially for peak-shaving performance. Finally, based on the characteristics of battery storage operation in each season, the joint operation strategy of cascade hydropower and battery storage is proposed to maintain the flexibility of battery storage and the sustainable operation of the hydro-wind-PV-storage complementary system. The following conclusions can be drawn: (1) the proposed day-ahead robust generation scheduling approach for hydro-wind-PV-storage complementarity systems can satisfy the steady requirement of UHV DC power delivery; (2) the proposed approach can effectively cope with the forecast uncertainties of wind and PV power, and avoid the electricity curtailment and power shortage risk of the system; and (3) the proposed joint operation strategy can effectively maintain the flexibility of hydro-wind-PV-storage complementary system.
郭怿, 明波, 黄强, 王义民, 李运龙. 考虑输电功率平稳性的水-风-光-储多能互补日前鲁棒优化调度[J]. 电工技术学报, 2023, 38(9): 2350-2363.
Guo Yi, Ming Bo, Huang Qiang, Wang Yimin, Li Yunlong. Day-Ahead Robust Optimal Scheduling of Hydro-Wind-PV-Storage Complementary System Considering the Steadiness of Power Delivery. Transactions of China Electrotechnical Society, 2023, 38(9): 2350-2363.
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2023, Vol. 38 
