Multi-objective optimal probabilistic planning in distribution systems considering load growth

Distribution network planning is critical to meet load growth and ensure the reliability of the network. the load demands of electrical distribution networks is increased gradually over time, which raises active and reactive power losses and lowers bus voltages below allowable levels. The modern power system has experienced significant structural modifications as a result of the annual expansion in load. This paper presents the operation of distribution networks with dispatch able mix of different types of distributed energy resources (DERs) units considering load growth up to planning period based on Multi Variant Differential Evolution algorithm (MVDE). The electric power system is supplied by numerous capacity resources including renewable and non-renewable power resources like photovoltaic system (PV), wind turbine system (WT), fuel cell (FC), and micro-turbine (MT). The main objectives of DERs allocation are to maximize technical, economic and environmental benefits by reducing the power losses, annual cost, and greenhouse gas. The WT, PV, MT, and FC units' capacity is increased by capacity expansion planning in the radial distributed network, which is carried out over a five-year planning horizon. A comprehensive stochastic strategy is offered for a number of uncertainties, such as load increase and output power from renewable energy sources. Two IEEE bus networks are used to illustrate the suggested method's efficacy. The optimization results based on proposed algorithm are compared with some existing algorithms.