Belkacem Mahdad

Reactive power dispatch based on static synchronous compensator (STATCOM) and photovoltaic (PV) sources in coordination with reconfiguration strategy is vital task to ensure reliable operation of modern radial distribution (RD) systems. This paper introduces a novel tree seed algorithm (TSA) to improve the performance of modern RD power systems. A variant of TSA based on intelligent and flexible mechanism search is proposed to create an interactive equilibrium between exploration and exploitation during the search process to improve the global solution. Two objective functions, the total power loss and the margin reserve security are optimized under normal condition and critical load growth. To obtain reliable operation of the distribution system under critical situations, a reactive power dispatch based STATCOM devices is managed in coordination with the reconfiguration stage to find the best combination of sectionalizing switches and tie switches to be operated. The efficiency and particularity of the proposed distribution-planning strategy validated on two test systems, the radial 33 buses and the practical radial 250 buses (30 kV) of Sonelgaz Company located in Biskra in the south of Algeria. This radial electric network designed principally to deliver energy to several small and important agricultural consumers. Results obtained based on various test cases and scenarios using the proposed new planning strategy confirm the efficiency of the proposed planning strategy in terms of reduction of the total power loss, improvement voltage magnitude and enhancement of margin reserve.

Optimal reactive power planning is an important task for experts and industrials to ensure the reliability of modern power systems. Actually, the structure of practical power systems becomes dynamic and characterised by uncertainty in load and non‐linear characteristic of various elements of power systems such as constraints associated to thermal units, constraints associated with FACTS devices and renewable sources. This study introduces an intelligent strategy based new metaheuristic named Salp swarm algorithm (SSA) to improve the solution of reactive power dispatch by optimising the total power loss, the total voltage deviation individually and simultaneously considering static VAR compensators (SVCs). To improve the efficiency of the original algorithm in solving large test systems, a sub SSA is formed to optimise the various objective functions based on a grouped control variable. In this study, four grouped swarms named SSA_PG for active power, SSA_VG for voltages, SSA_Ti for Tap transformers, and SSA_SVC for SVCs are formed to operate in a flexible structure to minimise a specified objective function. The proposed intelligent planning strategy validated on the IEEE 30 bus and to the large electrical test system 114 Bus of the Algerian network at normal condition and considering critical situations such as margin loading stability and contingency. Results found using the proposed strategy compared to those cited recently in the literature proves its particularity in terms of solution quality and convergence characteristics.

Application of a Novel Modified Hybrid Algorithm for Solving Dynamic Economic Dispatch Problem with Practical Constraints

This paper focuses on the solution of the optimal power flow (OPF) problem considering load growth using a novel metaheuristic optimization algorithm called Whale Optimization Algorithm (WOA). An interactive partitioning procedure is proposed to achieve a better solution and to improve search space diversity. In this study the new variant named partitioning WOA is applied to improve the security optimal power flow (SOPF) by minimization the total production cost with different complexities and constraints such as valve point effect and prohibited zones, total power loss and total voltage deviation considering critical load growth. The efficiency of the proposed algorithm has been validated on the IEEE 30-Bus, the Algerian 59-bus power system and to the large test system IEEE 118-Bus for various standard objective functions. For the test system IEEE-30 Bus, a competitive optimized quadratic cost (798.9225 $) is achieved compared to many recent techniques; also significant amounts of power loss and voltage deviation have been reduced for all test systems without affecting security constraints in particular for the IEEE 118-Bus, the total loss being reduced from 132.86 MW at base case (without optimization) to a competitive value 8.6099 MW. The proposed strategy proves its remarkable ability in solving the practical security constrained OPF for modern large power systems.