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OPTIMAL BATTERY STORAGE LOCATION AND CONTROL IN DISTRIBUTION NETWORK
The paper discusses the problem of the energy losses reduction in electrical networks using a battery energy storage system. One of the main research interests is to define the optimal battery location and control, for the given battery characteristics (battery size, maximum charge / discharge power, discharge depth, etc.), network configuration, network load, and daily load diagram. Battery management involves determining the state of the battery over one period (whether charging or discharging) and with what power it operates. Optimization techniques were used, which were applied to the model described in the paper. The model consists of a fitness function and a constraint. The fitness function is the dependence of the power losses in the network on the current battery power, and it is suggested that the function be fit by a n - order power function. The constraints apply to the very characteristics of the battery for storing electricity. At any time interval, the maximum power that the battery can receive or inject must be met. At any time, the stored energy in the battery must not exceed certain limits. The power of losses in the network is represented as the power of injection into the nodes of the network. The optimization problem was successfully solved by applying a genetic algorithm (GA), when determining optimal battery management. Finally, the optimal battery management algorithm is implemented on the test network. The results of the simulations are presented and discussed.
OPTIMAL BATTERY STORAGE LOCATION AND CONTROL IN DISTRIBUTION NETWORK
The paper discusses the problem of the energy losses reduction in electrical networks using a battery energy storage system. One of the main research interests is to define the optimal battery location and control, for the given battery characteristics (battery size, maximum charge / discharge power, discharge depth, etc.), network configuration, network load, and daily load diagram. Battery management involves determining the state of the battery over one period (whether charging or discharging) and with what power it operates. Optimization techniques were used, which were applied to the model described in the paper. The model consists of a fitness function and a constraint. The fitness function is the dependence of the power losses in the network on the current battery power, and it is suggested that the function be fit by a n - order power function. The constraints apply to the very characteristics of the battery for storing electricity. At any time interval, the maximum power that the battery can receive or inject must be met. At any time, the stored energy in the battery must not exceed certain limits. The power of losses in the network is represented as the power of injection into the nodes of the network. The optimization problem was successfully solved by applying a genetic algorithm (GA), when determining optimal battery management. Finally, the optimal battery management algorithm is implemented on the test network. The results of the simulations are presented and discussed.
OPTIMAL BATTERY STORAGE LOCATION AND CONTROL IN DISTRIBUTION NETWORK
Stevanović, Miloš (author) / Janjic, Aleksandar (author) / Stojanović, Sreten (author) / Tasić, Dragan (author) / This work has been supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia, Program for financing scientific research work, ev. no. 451-03-68 / 2020-14 / 200133.
2022-03-25
doi:10.2298/fuee20221121-136%x
Facta Universitatis, Series: Electronics and Energetics; Vol 35, No 1 (2022); 121-136 ; 2217-5997 ; 0353-3670
Article (Journal)
Electronic Resource
English
DDC:
690
Optimal integration of mobile battery energy storage in distribution system with renewables
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