In this paper, bi-level optimization model is proposed for optimal energy trading between microgrids (MGs) and distribution companies (Discos) with consideration of the renewable energies. The first level modelling is maximizing MGs’ profit and the second level is related to maximization of the Discos profit. In proposed system, power trading between MGs and Discos is considered. As well, renewable energies and demand management strategy are modelled in system for optimal energy consumption. The optimization modelling is solved by Particle Swarm Optimization (PSO), and results of the two case studies show optimal solution of prosed strategy in energy optimization.
The significant spread of the single-phase loads in the consumer homes make the distribution network suffering from many dangerous problems like the load unbalancing. This problem comes because the single-phase devices continuously plugged in and out to different phases each time. This paper cared about this problem and solved it efficiently by the new meta-heuristic algorithm called GWO that applied for the first time to solve the load balancing issue. The algorithm has the ability based on the smart meter included swapping mechanism to disconnects the appropriate home phases from their initial connection to specific feeders and reconnected again to other feeders for satisfying the balancing in the secondary distribution network. The algorithm adapted to reaching the balancing with a minimal number of swaps and take care of the online PVs if the consumer likes to buy energy to the national utility. It distributed all the PVs in a manner that not cause a balancing problem or lead to a stability issue. The proposed method has been applied to some unbalanced areas with random data generated in MATLAB to confirm the efficacy of the proposed algorithm.
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