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Smart control of energy storage system in residential photovoltaic systems for economic and technical efficiency

Kaczorowska Dominika, Rezmer Jacek, Janik Przemysław, Sikorski Tomasz

Archives of Electrical Engineering

2023

Vol. 72, nr 1

81--102

In recent years, due to the increasing number of renewable energy sources, which are characterised by the stochastic nature of the generated power, interest in energy storage has increased. Commercial installations use simple deterministic methods with low economic efficiency. Hence, there is a need for intelligent algorithms that combine technical and economic aspects. Methods based on computational intelligence (CI) could be a solution. The paper presents an algorithm for optimising power flow in microgrids by using computational intelligence methods. This approach ensures technical and economic efficiency by combining multiple aspects in a single objective function with minimal numerical complexity. It is scalable to any industrial or residential microgrid system. The method uses load and generation forecasts at any time horizon and resolution and the actual specifications of the energy storage systems, ensuring that technological constraints are maintained. The paper presents selected calculation results for a typical residential microgrid supplied with a photovoltaic system. The results of the proposed algorithm are compared with the outcomes provided by a deterministic management system. The computational intelligence method allows the objective function to be adjusted to find the optimal balance of economic and technical effects. Initially, the authors tested the invented algorithm for technical effects, minimising the power exchanged with the distribution system. The application of the algorithm resulted in financial losses, €12.78 for the deterministic algorithm and €8.68 for the algorithm using computational intelligence. Thus, in the next step, a control favouring economic goals was checked using the CI algorithm. The case where charging the storage system from the grid was disabled resulted in a financial benefit of €10.02, whereas when the storage system was allowed to charge from the grid, €437.69. Despite the financial benefits, the application of the algorithm resulted in up to 1560 discharge cycles. Thus, a new unconventional case was considered in which technical and economic objectives were combined, leading to an optimum benefit of €255.17 with 560 discharge cycles per year. Further research of the algorithm will focus on the development of a fitness function coupled to the power system model.

Balancing electric power in a microgrid via programmable agents auctions

Pałka P., Radziszewska W., Nahorski Z.

Control and Cybernetics

2012

Vol. 41, no. 4

777--797

The paper presents an application of an auction algorithm in a multi-agent computer system for managing the unbalanced energy in a microgrid. The main goal of the system is to control and minimize the deviations of the current energy dem and from the actual energy production, using an auction algorithm. Distributed generation is assumed in the microgrid, with renewable power sources. The energy storages and the controllable power sources improve the system operation. The differences between the actual demand and produced energy are caused by unpredictable level of electric power generation by uncontrolled sources, like wind turbines or solar panels, and/or randomness of power utilization. The system will tend to balance out these differences on-line in short time intervals (less than one minute) to follow-up varying levels of local power generation and loads.