چكيده به لاتين
This thesis presents an energy management strategy (EMS) for balanced or unbalanced multi-microgrids (MGs and UMGs) in the presence of active and reactive sources and active loads (ALs) to improve operation, reliability, emissions, and economic indices simultaneously. The proposed scheme is formulated as a four-objective optimization problem, in which the first to fourth functions represent the expected operating cost of balanced MGs (UMGs) and sources, expected emission level, expected energy not-supplied (EENS), and voltage deviation function, respectively. In balanced MGs, the problem is subject to AC optimal power flow equations, reliability limits of networks, formulation of sources, and various ALs. But, in UMGs, limits of unbalance mode are added to the mentioned constraints. Stochastic planning is utilized to model uncertainties of load, energy price, power generation of renewable energy sources (RESs), the energy of some ALs as electric vehicles (EVs) parking lot, and availability of network equipment. Then, the proposed multi-objective problem is converted into a single-objective formula using the Pareto optimization method based on the -constraint or the weighted sum. Furthermore, the hybrid algorithm based on teaching-learning-based optimization (TLBO) and grey wolf optimizer (GWO) algorithms is employed. Eventually, by implementing the suggested scheme on a sample test system, the obtained numerical results prove the capability of the scheme in improving the technical and economic situations of balanced MGs and UMGs. So that in the proposed scheme, operation cost, pollution, EENS and VDF in the point of compromise are approximately 14%, 15% 10.5%, and 3.4%, respectively, farther away from their minimum point. Besides, the proposed algorithm succeeds to achieve these results in the shortest possible time with a low standard deviation compared to other non-hybrid evolutionary algorithms. It is also observed that distribution system operator and MGs operator can employ the proposed scheme to enhance energy losses, voltage deviations, EENS, emission level, and operating cost and improved the technical and economic situations of the system.
