Waleed Fadel

This study tackles high power generation costs and emissions in power systems with Line Commutated Converter-based High Voltage Direct Current (LCC-HVDC) integration. Although LCC-HVDC reduces costs and emissions, it demands substantial reactive power support. To address this, three shunt capacitors (SCs) are added to lower costs and improve performance. An optimization model minimizes generation costs and emissions under varying load levels using the Backtracking Search Algorithm (BSA) for its robust global search and constraint-handling capabilities. The IEEE 30-bus system is used under three different load levels to evaluate performance. The study examines three cases: the base system, the system with HVDC, and the system with HVDC and SCs. Results show that integrating HVDC and SCs reduces generation costs and emissions considerably. For nominal load, the cost dropped by 15.28% with HVDC and SCs. The BSA was more efficient in optimization than the Artificial Bee Colony (ABC) algorithm.

In this paper, it is proposed that a two-terminal high voltage direct current (HVDC) be integrated into the power system. Line-commutated converter (LCC)-HVDC is used because of its ability to reduce line losses, which improves overall system efficiency. Shunt capacitors also aid in voltage maintenance by compensating for the reactive power demand. In essence, limiting voltage drops in electrical networks promotes a more efficient power transmission and distribution by lowering resistive losses. In power system investigations, it was discovered that the HVDC link and SCB exist separately. So, for the first time, the backtracking search algorithm (BSA) is used to solve the optimal reactive power flow (ORPF) of a power system with a HVDC link and shunt capacitor banks (SCB). Although BSA simulations on a modified IEEE 30 bus yielded successful results, ABC was also utilized for comparing the outcomes of different methods. Overall, three separate cases of the modified IEEE 30 bus system were examined. When the acquired results are compared to other methods, the suggested algorithm is found to be better at concerning effectiveness as well as performance.

: Distributed generation (DG) sources are becoming more important in electrical networks due to the increase of electrical energy demands. However, DG sources can have a profound effect on network power loss. Hence, optimal placement and size of DGs are extremely important. This study presents a backtracking search algorithm (BSA) based on optimal placement and size of multiple DGs within distribution systems so to reduce power loss. The BSA is a new heuristic algorithm. Two main DGs, photovoltaic and synchronous compensator, were used in the selected systems. To demonstrate the effectiveness of the proposed method, the results obtained by BSA are compared with a genetic algorithm (GA) as well as other results in the literature.