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The integration of several renewable energy sources (RESs), such as photovoltaic generation (PVG) and wind turbine generation (WTG), introduces a significant amount of uncertainty for the optimal planning of the electrical power systems. The optimal power flow (OPF) problem became more difficult to solve when RESs uncertainties were taken into account. In this research, the stochastic OPF problem is solved using an Adaptive Lightning Attachment Procedure Optimizer (ALAPO) with the integration of RESs. The ALAPO is proposed in this study to improve both the exploration and exploitation process of the conventional Lightning Attachment Procedure Optimizer (LAPO). In order to create a number of scenarios that account for the uncertainties associated with load demand, wind speed, and solar irradiation, the scenario based reduction method is utilized. Further, to determine the optimal setting of active power of generators, tap setting of the transformers, reactive power of the capacitor banks, and the voltage profile at the generator buses for each scenario of RESs the objective function considered in this study is to minimize the power loss, voltage deviation, and voltage stability index of the power system. The effectiveness of the proposed algorithm is tested on IEEE 57-bus system. The results in this study show that the proposed ALAPO is superior for solving the OPF with the integration of RESs compared to the conventional methods like LAPO, Particle Swarm Optimization (PSO), Sand Cat Swarm Optimizer (SCSO), Gray Wolf Optimizer (GOW), Whale Optimization Algorithm (WOA), Black Widow Optimization Algorithm (BWO), and Capuchin Search Algorithm (CapSA). [Display omitted] • Integration of several renewable energy. • Optimal power flow (OPF) problem. • Adaptive Lightning Attachment Procedure Optimizer (ALAPO). • Voltage profile at the generator buses is the objective function considered. [ABSTRACT FROM AUTHOR]

• Efficient distribution of power among generating units while considering various constraints. • To minimize the overall operating cost of the power system and enhance its efficiency. • The global optimum solution poses a significant challenge. • Enhanced social network search (ESNS) algorithm. The primary objective of Economic Load Dispatch (ELD) is to determine the most efficient distribution of power among generating units while considering various constraints, such as minimum and maximum power output, transmission line capacity, and reserve requirements. By solving the ELD problem, power system operators can minimize the overall operating cost of the power system and enhance its efficiency, which has far-reaching implications for sustainable energy management and resource allocation. However, because of the non-convex nature of the ELD problem, finding the global optimum solution poses a significant challenge. Consequently, several optimization techniques, such as metaheuristics, have been developed in order to address this type of problems. By iteratively exploring the solution space, metaheuristics offer a higher likelihood of finding near-optimal solutions, even in the presence of multiple local optima. This research introduces an enhanced social network search (ESNS) algorithm as an improvement over the existing social network search (SNS) algorithm, aiming to achieve the aforementioned objectives. The core of the SNS algorithm is driven by the social network users' dialogue, imitation, creativity, and disputation moods. The proposed ESNS algorithm builds upon the SNS approach by enhancing its search capability, particularly around the best potential solution. The primary goal is to improve the algorithm's ability to explore global search possibilities while avoiding being trapped in locally optimal solutions. The performance of ESNS has been tested in the 23 benchmark test suits, and its superiority against SNS and other recent algorithms has been verified. Moreover, To evaluate the effectiveness of the proposed ESNS algorithm, it is applied to four standard test systems comprising 11-, 15-, 40-, and 110-unit test systems. The results demonstrate that the ESNS algorithm outperforms other optimization algorithms in terms of solution quality and convergence speed. These findings suggest that the ESNS algorithm holds significant promise as a valuable tool for researchers and power system operators in addressing the economic dispatch problem. Overall, the ESNS technique presents a promising result to this complex challenges. Its capability to handle multiple constraints and its superior performance compared to other recent algorithms make it a valuable addition to the existing set of tools available for solving ELD. [ABSTRACT FROM AUTHOR]