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In this paper, an algorithm for energy management system (EMS) based on multilayer ant colony optimization (EMS-MACO) is presented to find energy scheduling in Microgrid (MG). The aim of study is to figure out the optimum operation of microsources for decreasing the electricity production cost by hourly day-ahead and real time scheduling. The proposed algorithm is based on ant colony optimization (ACO) method and is able to analyze the technical and economic time dependent constraints. This algorithm attempts to meet the required load demand with minimum energy cost in a local energy market (LEM) structure. Performance of MACO is compared with modified conventional EMS (MCEMS) and particle swarm optimization (PSO) based EMS. Analysis of obtained results demonstrates that the system performance is improved also the energy cost is reduced about 20% and 5% by applying MACO in comparison with MCEMS and PSO, respectively. Furthermore, the plug and play capability in real time applications is investigated by using different scenarios and the system adequate performance is validated experimentally too.

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Both performance optimization and scheduling of the distributed generation (DG) are relevant implementing an energy management system (EMS) within Microgrid (MG). Furthermore, optimization methods need to be applied to achieve maximum efficiency, improve economic dispatch as well as acquiring the best performance. This paper proposes an optimization method based on gravitational search algorithm to solve such problem in a MG including different types of DG units with particular attention to the technical constraints. This algorithm includes the implementation of some variation in load consumption model considering accessibility to the energy storage (ES) and demand response (DR). The proposed method is validated experimentally. Obtained results show the improved performance of the proposed algorithm in the isolated MG, in comparison with conventional EMS. Moreover, this algorithm which is feasible from computational viewpoint, has many advantages as peak consumption reduction, electricity generation cost minimization among other. non-responsive load (NRL) demand (kW) SOC t battery SOC in MCEMS (%) SOC t battery SOC in EMS-MGSA (%) P, P limit of power (kW) E, E limit of energy (kWh) SOC maximum SOC (%) SOC minimum SOC (%) ∆t time step

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The continuing increase of wind energy penetration in power systems, in combination with the retirement of conventional generation, raises new challenges for the maintenance of power system stability. This paper presents a comprehensive review of wind power plant capabilities to provide frequency support and the corresponding methods available in the published literature are thoroughly analysed and compared. The topic is covered from different perspectives giving a comprehensive overview of the work carried out in this field. In addition, the integration of energy storage technologies and dispatching of wind farms during frequency deviations are investigated. Finally, technical challenges, future research lines and general recommendations are provided.

In this paper, a general framework for implementing a retail energy market based on the Nikaido-Isoda/relaxation algorithm is proposed as an electricity market structure with large distributed energy resources (DERs) penetration and demand side management (DSM) of consumers. Moreover, the consumers are able to participate in the market as prosumers (i.e., producer and consumer at the same time). By considering the related uncertainties, the DERs can maximize their expected payoff or profit by undertaking strategies through the price bidding strategy, based on the proposed structure, considering Nash equilibrium. The results show the effectiveness and accuracy of the proposed framework in determining the optimal power set-points of players participating in the market to achieve the objectives.

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