## 1 Introduction
CSSO is a cost-effective approach for allocating renewable energy sources (RESs), particularly wind, solar PV, and energy storage systems (ESSs), in electrical distribution networks to reduce costs and active power losses. The method is needed to figure out how many possible and ideal sites there are for the hybrid RES-ESS [10]. A method for solving the optimal reactive power management (ORPM) problem involves using a multi-objective function and a modified differential evolution algorithm (MDEA). Through the solution of the ORPM issue, MDEA is being examined for its ability to improve the voltage profile as well as minimize active power losses [11]. To reduce transmission power losses and voltage deviation while considering system restrictions, the ORPM objective function is proposed as a power sharing control approach based on adaptive drooping. The major goal is to govern the distribution of active power transmitted via a high-voltage direct current network based on a multi-terminal voltage-source converter among numerous onshore alternating current grids or offshore loads depending on the required percentage share [12]. The shared electricity is produced by distant generating units or is offered as a surplus by alternating current (AC) power systems. The system operator optimizes the desired percentage shares of active power to meet the active power needs of the linked grids and reach goals such as supporting energy sufficiency, increasing the use of renewable energy, and preventing losses. Figure 1 shows a detailed diagram of the inner current loop controller used to implement this concept. This controller is the main part of the system that contains the programming executable steps of the proposed GWO. Contrasting with disconnected designs, a unique framework for buildings-to-distribution network (B2 DN) integration has  
been developed that decreases distribution network active power losses and increases voltage management while also decreasing building energy expenditures and ensuring occupant comfort [13; 14]. A probabilistic multi-objective optimization approach has been used to determine the optimal sizes and locations of static variable compensators and thyristor-controlled series capacitors (TCSCs) in a power transmission network with a high penetration level of wind generation. This approach has been proven to be successful [15]. As a component of the Egyptian distribution network, the West Delta Network (WDN) has been thoroughly examined, factoring in a 30% increase in system loading. It was found that an oscillatory particle swarm optimization (OPSO) technique could be used to find the best places and sizes for a single or multiple distribution grids to achieve the goals of minimizing total active power losses and system voltage regulation as a single and multi-objective optimization problem in a distribution network [16]. The most efficient way to connect unbalanced hybrid AC/DC micro-grids to the grid is to use a hierarchical power routing method. A three-phase, four-leg inter-linking converter is used to distribute electric vehicles (EVs) between charging stations (CSs) in the micro-grid while they are en route. The ICs dynamically route power between the three phases of the alternating current system to reduce active power losses and the power imbalance factor (PIF) at the point of common coupling (PCC), which is where the EVs are charged [17]. Electric vehicle chargers can be coordinated with other voltage/voltage control devices using a three-stage method described in [18]. This method can be used on both medium-term and long-term power lines. As shown by the numbers, this optimization method is better than others at finding the best way to allocate SCBs to cut network power losses, improve voltage profiles, and save money [19]. Electric power providers have been  
Figure 1: Detailed diagram of the inner current loop controller. paying a lot of attention recently to the best places and sizes for various types of renewable energy production systems in their distribution networks.