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A bi-level optimization method for voltage control in distribution networks using batteries and smart inverters with high wind and photovoltaic penetrations.

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Title: A bi-level optimization method for voltage control in distribution networks using batteries and smart inverters with high wind and photovoltaic penetrations.
Authors: Alrashidi, Musaed1 (AUTHOR) malrashidi@qu.edu.sa, Rahman, Saifur2 (AUTHOR)
Source: International Journal of Electrical Power & Energy Systems. Sep2023, Vol. 151, pN.PAG-N.PAG. 1p.
Subjects: Bilevel programming, Voltage control, Metaheuristic algorithms, Battery storage plants, Overvoltage, Storage battery charging, Wind pressure, Grids (Cartography), Wind forecasting
Abstract: • Overvoltage issue is addressed, which is a primary concern in distribution grids with high PV integration. • A coordinated voltage control strategy is presented which integrates the operations of the battery storage and the smart PV inverter. • The algorithm manages the charging and discharging of the storage battery through a network-level optimization. • The solar PV power output forecast is integrated in the proposed voltage management strategy. • Performance and convergence experiments are conducted using the metaheuristic optimization algorithms and results presented. In electrical distribution systems, the voltage quality problem considers the most restrictive issue that hinders high photovoltaic (PV) and wind integration. Therefore, this study aims at providing a reliable control method for the voltage problem in distribution networks embedded with high PV and wind sources. The proposed voltage management strategy consists of two controlling stages. The first stage uses battery energy storage systems (BESS), while the second stage employs the smart PV inverters' reactive power injection capability. For BESS operation, a bi-level optimization method based on metaheuristic optimization algorithms (MOA) is developed to regulate the voltage levels by governing the batteries charging/discharging rates. The bi-level optimization problem aims to maximize PV and wind energy exploitation while improving the voltage profile. In this study, a detailed comparison is conducted between three MOA: Social Spider Optimization, Particle Swarm Optimization, and Cuckoo Search Optimization. In addition, considering the uncertainty associated with PV system generation, a PV generation forecast is embedded in the voltage control strategy to reinforce the decision-making process of BESS operation. The efficacy of the proposed method is deployed on a modified IEEE-34 bus test feeder with real-world load and PV and wind power generation data. Experimental results show the effectiveness of the proposed method and indicate that proper coordination between the BESS and smart PV inverters is beneficial for distribution system operations that seamlessly integrate PV and wind energy. Overall, the proposed voltage management strategy can be used to control the voltage to any desired range at different locations. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:• Overvoltage issue is addressed, which is a primary concern in distribution grids with high PV integration. • A coordinated voltage control strategy is presented which integrates the operations of the battery storage and the smart PV inverter. • The algorithm manages the charging and discharging of the storage battery through a network-level optimization. • The solar PV power output forecast is integrated in the proposed voltage management strategy. • Performance and convergence experiments are conducted using the metaheuristic optimization algorithms and results presented. In electrical distribution systems, the voltage quality problem considers the most restrictive issue that hinders high photovoltaic (PV) and wind integration. Therefore, this study aims at providing a reliable control method for the voltage problem in distribution networks embedded with high PV and wind sources. The proposed voltage management strategy consists of two controlling stages. The first stage uses battery energy storage systems (BESS), while the second stage employs the smart PV inverters' reactive power injection capability. For BESS operation, a bi-level optimization method based on metaheuristic optimization algorithms (MOA) is developed to regulate the voltage levels by governing the batteries charging/discharging rates. The bi-level optimization problem aims to maximize PV and wind energy exploitation while improving the voltage profile. In this study, a detailed comparison is conducted between three MOA: Social Spider Optimization, Particle Swarm Optimization, and Cuckoo Search Optimization. In addition, considering the uncertainty associated with PV system generation, a PV generation forecast is embedded in the voltage control strategy to reinforce the decision-making process of BESS operation. The efficacy of the proposed method is deployed on a modified IEEE-34 bus test feeder with real-world load and PV and wind power generation data. Experimental results show the effectiveness of the proposed method and indicate that proper coordination between the BESS and smart PV inverters is beneficial for distribution system operations that seamlessly integrate PV and wind energy. Overall, the proposed voltage management strategy can be used to control the voltage to any desired range at different locations. [ABSTRACT FROM AUTHOR]
ISSN:01420615
DOI:10.1016/j.ijepes.2023.109217