Abstract
The problem of voltage collapse in power systems due to increased loads can be solved by adding renewable energy sources like wind and photovoltaic (PV) to some bus-bars. This option can reduce the cost of the generated energy and increase the system efficiency and reliability. In this paper, a modified smart technique using particle swarm optimization (PSO) has been introduced to select the hourly optimal load flow with renewable distributed generation (DG) integration under different operating conditions in the 30-bus IEEE system. Solar PV and wind power plants have been introduced to selected buses to evaluate theirs benefits as DG. Different solar radiation and wind speeds for the Dammam site in Saudi Arabia have been used as an example to study the feasibility of renewable energy integration and its effect on power system operation. Sensitivity analysis to the load and the other input data has been carried out to predict the sensitivity of the results to any deviation in the input data of the system. The obtained results from the proposed system prove that using of renewable energy sources as a DG reduces the generation and operation cost of the overall power system.
Highlights
Optimal power flow (OPF) studies aim to optimize specific objectives by adjusting some power system variables, provided that all equality and inequality constraints of the system are satisfied.Based on its energy management capability, OPF became one of the most important areas of study in the electric power field
The wind power generation has its peak amplitude between the hours 12 and 13
The integration of renewable energy in existing power systems in the form of distributed generation (DG) was addressed in this study
Summary
Optimal power flow (OPF) studies aim to optimize specific objectives by adjusting some power system variables, provided that all equality and inequality constraints of the system are satisfied.Based on its energy management capability, OPF became one of the most important areas of study in the electric power field. Optimal power flow (OPF) studies aim to optimize specific objectives by adjusting some power system variables, provided that all equality and inequality constraints of the system are satisfied. OPF is a highly constrained and nonlinear problem with continuous and discrete variables. Deterministic methods include linear [2] and nonlinear programming (LP) [3], quadratic programming (QP) [4], and interior point method (IM) [5]. These methods have a problem in handling many local minima due to the non-convexity of OPF problems. Due to the limitations of deterministic methods, evolutionary methods were introduced to remedy these
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