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This paper presents a new version of JAYA algorithm to solve the problem of optimal power flow (OPF) incorporating renewable energy sources (RES) with four different objective functions that reflect fuel cost minimization, emission minimization, transmission power loss minimization, and voltage profile improvement. The proposed modified JAYA (MJAYA) algorithm can be derived by modifying the equation that used to update the solutions based on best and worst solutions. The formulation of the OPF problem incorporating RES with four different objective functions is introduced in this paper. Then, the proposed MJAYA is employed to solve this problem by converting it into a single objective function using price and weighting parameters. In addition, the scalability of the proposed MJAYA is tested. To prove the effectiveness of the proposed MJAYA algorithm, it is applied to two different test systems (IEEE 30-bus system and IEEE 118-bus system). The obtained results of different scenarios using the proposed MJAYA algorithm are compared with those obtained using other published methods in the literature. The comparisons with other published methods show the superiority of the proposed MJAYA algorithm over other methods with different complexities. • The modified JAYA algorithm (MJAYA) is proposed in this paper. • The proposed method is used to solve the OPF problem with renewable energy sources. • The OPF considers minimization of cost, emission, power loss and voltage deviation. • The proposed method has been evaluated using two test systems with different cases. • Results of all cases show the superiority of the proposed method over other methods. [ABSTRACT FROM AUTHOR]

In recent years, optimal sizing and location of reactive power resources are drawing much attention to help the operators of the utilities to enhance the power system operations. Therefore, this work presents a new version of grey wolf optimiser (GWO) to solve the problem of optimal reactive power resources sizing for power system operation enhancement. The proposed method which called improved grey wolf optimiser (IGWO) can be derived by modifying the exploration-exploitation balance in the conventional GWO to enhance its rate of convergence. Also, the weighted distance strategy is employed in the proposed IGWO to overcome the drawback of the conventional GWO. Optimal reactive power resources sizing problem is nonlinear and non-convex optimisation problem. To solve this problem, different objective functions are used. These objective functions are minimisation of generating cost, minimisation of transmission power loss and voltage profile improvement. The validity and superiority of the proposed IGWO method are tested using three standard IEEE systems for normal and contingency conditions. Then the results are compared with those obtained from other recently published algorithms. The simulation results show that the proposed IGWO method is more accurate and efficient than other recently published algorithms. [ABSTRACT FROM AUTHOR]