Capacity optimization of wind–solar–storage multi-power microgrid based on two-layer model and an improved snake optimization algorithm




HIGHLIGHTS
  • What: Taking a microgrid in South China as an application scenario the model is solved and the optimal allocation scheme of the microgrid is obtained. The study aimed to address the supply and demand uncertainties brought about by the high penetration rate of electric vehicles, thereby ensuring the security of the power system. The approach was designed to minimize the total opimportance of microgrids in the sustainable development of cities and communities and erating costs of microgrids under high-dimensional uncertainties such as generators, load proposed a novel two-layer model. The flow chart of the two-layer optimization model used in this paper and the relationship between the upper and lower models are shown in Figure 3.
  • Who: Mintong Zhao and collaborators from the Department of Mechanical Engineering, North China Electric Power University, Baoding, China have published the research work: Capacity Optimization of Wind-Solar-Storage Multi-Power Microgrid Based on Two-Layer Model and an Improved Snake Optimization Algorithm, in the Journal: Electronics 2024, 13, x FOR PEER REVIEW of /2024/
  • How: The approach was designed to minimize the total demands and planned outages. operating costs of microgrids under high-dimensional uncertainties such as generators Although and the above literature load demands planned outages.has achieved significant results there are still many problems in the development of microgrids in the context of energythere transformation. To enhance the search ability of SOA for global optimization and speed up the convergence of the algorithm the following ISOA is proposed. This paper introduces Tent chaotic mapping to initialize the position of the snake colony.
  • Future: Future research could extend the application of this model to other types of new energy power generation systems thereby facilitating the systematic and orderly advancement of energy transformation efforts. Balancing the enhancement of the algorithm`s global search ability with a reasonable computational load will be a meaningful direction for future research.
SUMMARY

    For complex models of power grids, the two-layer optimization model can address the optimization problems efficiently and reliably. Aiming at the medium- and long-term operationthe of optimal allocation problem optimal optimal scheduling, and proposes ISOA to optimize microgrids, this paper adoptswith a two-layer allocation method,an which combines the the capacity of microgrids. A microgrid is mainly composed of wind turbines, photovoltaic arrays, energy storA microgrid is mainly composed of wind turbines, photovoltaic arrays, energy storage age devices, converters and local loads, which are connected to the upper power grid. devices, converters and local loads, which are connected to the upper power grid. When when there is a power shortage in the system, power is purchased from the upper power there is a power shortage in the system, power is purchased from the upper power grid to grid to ensure the reliability of the system. The fluctuations in the power ofofthe the grid gradually become higher.ItItcannot cannotmeet meet the the fluctuation thethe grid willwill gradually become higher. fluctuationrequirements requirementsofof power of the grid, resulting in significant underutilization of solar and wind power. power of the grid, resulting in significant underutilization of solar and wind power. Operation cost 33,697 33,553 33,177 (thousand CNY)the capacity of grid-connected microgrids through a This paper aims to optimize double-layer optimization model to improve the consumption rate of new energy and reduce carbon emissions. This study shows that optimizing the capacity of wind-solar-storage systems based on a two-layer optimization model effectively resolves the intricate coupling between capacity and scheduling optimization. @@

LAY DEFINITIONS
  • Algorithm: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.
  • demand response: Demand response is a change in the power consumption of an electric utility customer to better match the demand for power with the supply. Until recently electric energy could not be easily stored, so utilities have traditionally matched demand and supply by throttling the production rate of their power plants, taking generating units on or off line, or importing power from other utilities
  • Snake: Limbless REPTILES of the suborder Serpentes.

Licence: cc-by

Site reference: https://www.mdpi.com/2079-9292/13/21/4315/pdf?version=1730540138

DOI reference: https://www.doi.org/10.3390/electronics13214315

Summary powered by SciencePOD SUMMSci Version version 5.5 (C) 2023 Context powered by www.wikipedia.org

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source https://magazine.sciencepod.net/capacity-optimization-of-wind-solar-storage-multi-power-microgrid-based-on-two-layer-model-and-an-improved-snake-optimization-algorithm/

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