Abstract:The strategies of distribution network reconfiguration are applicable for minimizing power loss and saving electrical energy in the distribution system. Network reconfiguration is usually represented by constant load demand so ignoring the variability of load demand causes uncertainty and misleading results in the minimization of power loss. This paper consists of two parts: first, the reconfiguration was accomplished using an optimization framework based on constant load to find sets of optimal switches. The minimization of active power loss was taken as an objective function while bus voltage, branch current and system radiality were taken as system constraints. The study was applied to a 33-bus test distribution network, which is exceedingly used as test examples for solving reconfiguration problems. Second, lists of the configurations set obtained from the first part, as well as other different optimization methods proposed earlier under constant load demand were taken as test switches. Additionally, the network in the presence of distributed generators was taken to analyze the reconfiguration under an active network. Two types of load demands; the variable load and voltage-dependent load, are proposed to represent the practical load demands. This paper presents a new method for good analysis as it defines the effect of loading levels and loading patterns on a distribution system performance for passive and active networks. The proposed approach tries to find the actual power loss under different characteristics of loads. Therefore, the probable benefit of this approach is the contribution to providing more flexibility for electrical utilities in terms of distribution system operation, while also opening new prospects in the automation of smart distribution systems.
Technical and technological advances in alternative energy sources have led many countries to add green energy to their power plants to reduce carbon emissions and air pollution. At present, many electricity companies are looking to use alternative sources of energy because of high electrical energy prices. Wind energy is more useful than many renewable energies such as solar, heat, biomass, etc. The Wind Energy Conversion System (WECS) is a system that converts the kinetic energy of the wind into electrical energy to feed the known loads. WECS can be found in a variety of technology. Climate change and load demand are essential determinants of WECS optimization modelling. In this paper, proposed a strategy focused primarily on economic analysis WECS. The strategy based on a weather change to find the optimal designing and modelling for four different types of WECS using HOMER software. Finally, several criteria were used to determine which type of WECS was the most profitable investment and less payback period.
Economic dispatch issues in power system aim to try getting an optimal plan for the power generators to minimize the fuel cost (FC) in parallel with satisfying system constraints. This paper proposes a new enhancement based on particle swarm optimization (PSO) algorithm called multiple inertia weight PSO (MIW-PSO) to solve the combined economic and emission load dispatch (CEELD) issues in the modern electrical power systems. Two electrical test systems are investigated in this study to validate the competence of the proposed algorithm. The obtained results for CEELD case using MIW-PSO compared with MOCPSO indicate a promising performance in terms of minimizing FC and pollutant emission (PE) are reduced 84.96 $/h and 12.01 kg/h for the first test system. As well as, for the second test system, compared with NSGA-RL are reduced 0.241 $/h and 3.15 kg/h. Moreover, the proposed algorithm has more accuracy, better convergence time, and higher quality solutions for the minimum CEELD compared with other methods.
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