IASA-Based Capacity Allocation Optimization Study for a Hydro–Pumped Storage–Photovoltaic–Wind Complementary Clean Energy Base

As a new type of flexible regulation resource, energy storage systems not only smooth out the fluctuation of new energy generation but also track the generation scheduling combined with new energy power to enhance the reliability of new energy system operations. In recent years, installing energy storage for new on-grid energy power stations has become a basic requirement in China, but there is still a lack of relevant assessment strategies and techno-economic evaluation of the size determination of energy storage systems from the perspective of new energy power stations. Therefore, this paper starts from summarizing the role and configuration method of energy storage in new energy power stations and then proposes multidimensional evaluation indicators, including the solar curtailment rate, forecasting accuracy, and economics, which are taken as the optimization targets for configuring energy storage systems in PV power stations. Lastly, taking the operational data of a 4000 MWPV plant in Belgium, for example, we develop six scenarios with different ratios of energy storage capacity and further explore the impact of energy storage size on the solar curtailment rate, PV curtailment power, and economics. The method proposed in this paper is effective for the performance evaluation of large PV power stations with annual operating data, realizes the automatic analysis on the optimal size determination of energy storage system for PV power stations, and verifies the rationality of the principle for configuring energy storage for PV power stations in some regions of China.

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Capacity Optimization of Pumped–Hydro–Wind–Photovoltaic Hybrid System Based on Normal Boundary Intersection Method

Wang,

Li,

et al. 2024

Sustainability

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Introducing pumped storage to retrofit existing cascade hydropower plants into hybrid pumped storage hydropower plants (HPSPs) could increase the regulating capacity of hydropower. From this perspective, a capacity configuration optimization method for a multi-energy complementary power generation system comprising hydro, wind, and photovoltaic power is developed. Firstly, to address the uncertainty of wind and photovoltaic power outputs, the K-means clustering algorithm is applied to deal with historical data on load and photovoltaic, wind, and water inflow within a specific region over the past year. This process helps reduce the number of scenarios, resulting in 12 representative scenarios and their corresponding probabilities. Secondly, with the aim of enhancing outbound transmission channel utilization and decreasing the peak–valley difference for the receiving-end power grid’s load curve, a multi-objective optimization model based on the normal boundary intersection (NBI) algorithm is developed for the capacity optimization of the multi-energy complementary power generation system. The result shows that retrofitting cascade hydropower plants with pumped storage units to construct HPSPs enhances their ability to accommodate wind and photovoltaic power. The optimal capacity of wind and photovoltaic power is increased, the utilization rate of the system’s transmission channel is improved, and the peak-to-valley difference for the residual load of the receiving-end power grid is reduced.

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IASA-Based Capacity Allocation Optimization Study for a Hydro–Pumped Storage–Photovoltaic–Wind Complementary Clean Energy Base

Cited by 3 publications

References 24 publications

Power Systems Optimization Challenges and Applications: An Overview

Power Systems Optimization Challenges and Applications: An Overview

An optimal energy storage system sizing determination for improving the utilization and forecasting accuracy of photovoltaic (PV) power stations

Capacity Optimization of Pumped–Hydro–Wind–Photovoltaic Hybrid System Based on Normal Boundary Intersection Method

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