This paper models and analyzes the consumption and trading patterns of electrical energy in islanded microgrids when the generation is restricted to renewable resources such as photovoltaic (PV) panels. With the producers and consumers of the grid represented as agents, the impact of the following two scenarios on the agents' utilities as well as the social welfare are investigated during the islanded period: (i) trading with fixed price; (ii) trading with variable price. In order to reflect real-world behavior, Nash equilibrium (NE) in user (agent) behavior is established by means of evolutionary optimization i.e. Genetic Algorithm (GA), such that each user maximizes its individual utility. The users' utilities consider both income from trade as well as the monetary equivalent of satisfaction derived from energy consumption. The latter is sufficiently generalized as it incorporates fixed loads whose utility curves are modeled as saturating nonlinearities, as well as discrete shiftable loads that can be scheduled over any time interval during the isolation period. Simulation results of this study are expected to have widespread ramifications in designing the future distribution systems.
Covariance matrix adaptation evolution strategy with directed target to best perturbation (CMS-ES_DTBP) scheme is applied for determining the optimal hourly schedule of power generation in a hydro-thermal power system. In the proposed approach, a multi-reservoir cascaded hydro-electric system with a nonlinear relationship between water discharge rate, net head and power generation is considered. Constraints such as power balance, water balance, reservoir volume limits and operation limits of hydro and thermal plants are also considered. The feasibility, and effectiveness of the proposed algorithm is demonstrated through a test system, and the obtained results are compared with the existing conventional and evolutionary algorithms. Simulation results reveal that the proposed CMS-ES_DTBP scheme appears to be best in terms of convergence speed and cost compared with other techniques.
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