Abstract
A solution to reduce the emission and generation cost of conventional fossil-fuel-based power generators is to integrate renewable energy sources into the electrical power system. This paper outlines an efficient hybrid particle swarm gray wolf optimizer (HPS-GWO)-based optimal power flow solution for a system combining solar photovoltaic (SPV) and wind energy (WE) sources with conventional fuel-based thermal generators (TGs). The output power of SPV and WE sources was forecasted using lognormal and Weibull probability density functions (PDFs), respectively. The two conventional fossil-fuel-based TGs are replaced with WE and SPV sources in the existing IEEE-30 bus system, and total generation cost, emission and power losses are considered the three main objective functions for optimization of the optimal power flow problem in each scenario. A carbon tax is imposed on the emission from fossil-fuel-based TGs, which results in a reduction in the emission from TGs. The results were verified on the modified test system that consists of SPV and WE sources. The simulation results confirm the validity and effectiveness of the suggested model and proposed hybrid optimizer. The results confirm the exploitation and exploration capability of the HPS-GWO algorithm. The results achieved from the modified system demonstrate that the use of SPV and WE sources in combination with fossil-fuel-based TGs reduces the total system generation cost and greenhouse emissions of the entire power system.
Highlights
Introduction published maps and institutional affilDue to the rapid increase in energy demand, the impact of optimization in power flow is significant
The adopted system consists of thermal generators and WT and solar photovoltaic (SPV) sources; the total generation cost is the sum of the cost of all these sources, which are described in the subsequent subsections
Two objective functions for optimization were considered in this study: total generation cost with the valve point effect and power losses in the system
Summary
The problem OPF can be formulated as a nonlinear optimization problem. The key purpose of the OPF is to reduce the total generation cost of the system by choosing suitable values of the control variables subjected to various system constraints. Where x represents the control variables while y represents the state variables. Consideration of the state variable is important for the security of the electrical system. The adopted system consists of thermal generators and WT and SPV sources; the total generation cost is the sum of the cost of all these sources, which are described in the subsequent subsections. Replacing thermal generators with RES, the generation at a bus should not breach line capacity constraints; in this research, the same approach of replacing thermal generators with RES was adopted as in References [24,25].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
