Optimal power flow with renewable energy resources using static VAR compensator and grey wolf optimisation

The present paper aims to validate an electrical network study in consisting of conventional fossil fuel generators with the integration of intermittent generation technologies based on renewable energy resources like wind power or solar photovoltaic (PV) are the stochastic power output. By using an optimal power flow (OPF) problem different frameworks are developed for solving that represent various operating requirements, such as minimization of production fuel cost, and preserving generation emission at the lowest levels... etc. The OPF analysis aims to find the optimal solution and is very important for power system operation with satisfying operational constraints, planning and energy management. However, the intermittent combination of solar exacerbates the complexity of the problem. Within the framework of these criteria, this paper is an overview of the application Grey Wolf Optimizer (GWO) algorithm which solves the OPF problem with renewable energy. The algorithm thus combined and constructed gives optimum results satisfying all network constraints. Give an explanation for findings are based thus need to be with the optimum to effectuate of network constraints.

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Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy

Energies ◽

10.3390/en13226066 ◽

2020 ◽

Vol 13 (22) ◽

pp. 6066

Author(s):

Khaled Nusair ◽

Lina Alhmoud

Keyword(s):

Renewable Energy ◽

Power Systems ◽

Power Flow ◽

Optimal Power Flow ◽

Energy Resources ◽

Solar Pv ◽

Renewable Energy Resources ◽

Real Power ◽

Optimal Power ◽

Bus System

In recent decades, the energy market around the world has been reshaped to accommodate the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system is performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior and provides the lowest optimization value in term of electric power generation, real power loss, emission index and voltage deviation.

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