Abstract
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.
Highlights
IntroductionThe urgent need for reducing the fuel cost of the conventional power generation units and minimizing the greenhouse gases emitted from the thermal power generators have led various electric power companies to go toward utilizing renewable energy resources
Aiming to fill the gap in the literature, this paper investigates the impact of the presence of only wind or only solar PV or both of them on enhancing the objective functions of the optimal power flow (OPF) problem
Its performance and effectiveness were evaluated on four power system, namely: IEEE 30-bus system, wind integrated IEEE
Summary
The urgent need for reducing the fuel cost of the conventional power generation units and minimizing the greenhouse gases emitted from the thermal power generators have led various electric power companies to go toward utilizing renewable energy resources. The advanced technologies of renewable energy resources have contributed significantly to them becoming the most. Energies 2020, 13, 6066 inexpensive and environmentally friendly resources. Integrating wind and solar PV in proper locations and appropriate settings of the variables of the conventional power networks may have a significant impact on the performance of power system control and operation. To make the modeling of wind and solar PV more accurate and realistic, the Weibull probability distribution function was used to forecast the wind speed [1,2], whereas lognormal probability distribution function was used to mimic the intermittent nature of solar irradiance in [3,4]
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