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    Wyświetlanie 1-3 z 3
    Tytuł:
    Energy storage systems: power grid and energy market use cases
    Autorzy:
    Komarnicki, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/141507.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    storage technologies
    storage system sizing
    storage system operation
    storage system management
    storage system use case scenarios
    storage system integration
    Opis:
    Current power grid and market development, characterized by large growth of distributed energy sources in recent years, especially in Europa, are according energy storage systems an increasingly larger field of implementation. Existing storage technologies, e.g. pumped-storage power plants, have to be upgraded and extended by new but not yet commercially viable technologies (e.g. batteries or adiabatic compressed air energy storage) that meet expected demands. Optimal sizing of storage systems and technically and economically optimal operating strategies are the major challenges to the integration of such systems in the future smart grid. This paper surveys firstly the literature on the latest niche applications. Then, potential new use case and operating scenarios for energy storage systems in smart grids, which have been field tested, are presented and discussed and subsequently assessed technically and economically.
    Źródło:
    Archives of Electrical Engineering; 2016, 65, 3; 495-511
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Short-term optimal energy management in stand-alone microgrid with battery energy storage
    Autorzy:
    Paliwal, N. K.
    Singh, A. K.
    Singh, N. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/140998.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony
    battery energy storage
    clean energy sources
    optimal energy management
    stand-alone microgrid
    Opis:
    The optimal energy management (OEM) in a stand-alone microgrid (SMG) is a challenging job because of uncertain and intermittent behavior of clean energy sources (CESs) such as a photovoltaic (PV), wind turbine (WT). This paper presents the effective role of battery energy storage (BES) in optimal scheduling of generation sources to fulfill the load demand in an SMG under the intermittency of theWT and PV power. The OEM is performed by minimizing the operational cost of the SMG for the chosen moderate weather profile using an artificial bee colony algorithm (ABC) in four different cases, i.e. without the BES and with the BES having a various level of initial capacity. The results show the efficient role of the BES in keeping the reliability of the SMG with the reduction in carbon-emissions and uncertainty of the CES power. Also, prove that the ABC provides better cost values compared to particle swarm optimization (PSO) and a genetic algorithm (GA). Further, the robustness of system reliability using the BES is tested for the mean data of the considered weather profile.
    Źródło:
    Archives of Electrical Engineering; 2018, 67, 3; 499--513
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Smart control of energy storage system in residential photovoltaic systems for economic and technical efficiency
    Autorzy:
    Kaczorowska, Dominika
    Rezmer, Jacek
    Janik, Przemysław
    Sikorski, Tomasz
    Powiązania:
    https://bibliotekanauki.pl/articles/2202548.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    economic efficiency
    energy storage system ESS
    microgrid management
    optimal power flow
    OPF
    particle swarm optimisation PSO
    Opis:
    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.
    Źródło:
    Archives of Electrical Engineering; 2023, 72, 1; 81--102
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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