A review of meta-heuristic algorithms for reactive power planning problem <s> The fuzzy goal programming approach <s> This paper presents a new formulation of multi-objective reactive power and voltage control for power system. The objectives are active power loss, voltage deviation and the voltage stability index of the system. The load constrains and operational constrains are also taken into consideration. The multi-objective formulation of the problem requires a global performance index of the problem. A pseudogoal function derived on the basis of the fuzzy sets theory gives a unique expression for the global objective function, eliminating the use of weighing coefficients or penalty terms. Both objective functions and constraints are evaluated by membership functions. The inequality constrains are embedded into the fitness function by pseudogoal function which guarantees that the searched optimal solution is feasible. Moreover, a new type of evolutionary algorithm, particle swarm optimization (PSO), has been adopted and improved for this problem. To improve the performance of PSO, a fuzzy adaptive PSO (FAPSO) is proposed. A fuzzy system is employed to adaptively adjust the parameters of PSO, such as the inertia weight and learning factors, during the evolutionary process. The proposed approach has been examined and tested with promising numerical results of the IEEE 30-bus and IEEE 118-bus power systems. <s> BIB001 </s> A review of meta-heuristic algorithms for reactive power planning problem <s> The fuzzy goal programming approach <s> Abstract Reactive power dispatch (RPD) is one of the major issues of modern energy management system. This article presents an efficient genetic algorithm (GA) approach for modelling and solving RPD problem of power system in the framework of fuzzy goal programming (FGP) in uncertain environment. In the proposed approach, the objectives of the problem concerned with RPD problem are fuzzily described. In the solution process, the proposed GA method is used in the framework of FGP model in an iterative manner to reach a satisfactory decision. The proposed approach is tested on the standard IEEE 6-Generator 30-Bus System and compared with the solutions obtained in previous study. <s> BIB002 </s> A review of meta-heuristic algorithms for reactive power planning problem <s> The fuzzy goal programming approach <s> This study proposes a multi-objective fuzzy-based procedure for solving reactive power management in competitive environment. The proposed procedure incorporates both economical and technical aspects of reactive power support. The economical aspect aims to minimise the total costs of reactive power purchase from service providers as primary objective function, whereas the technical aspect is taken care of through the secondary objective function that minimises the total transmission losses. The proposed procedure achieves security constraints such as the bus voltage limits, reactive power capability limits and transmission line reactive transfer limits. The proposed procedure is applied to the west-delta region system as a part of the Egyptian Unified network. The numerical results show that the proposed procedure achieves a minimum real power loss with maximal reactive reserve for power systems for different operating conditions. <s> BIB003 </s> A review of meta-heuristic algorithms for reactive power planning problem <s> The fuzzy goal programming approach <s> Reactive power optimization is one of the efficient ways of improving power system reliability and efficiency which is beneficial in power planning studies. ORPD problems are best solved using different algorithms to achieve optimization. This paper deals a comparative study of three algorithms PSO, GSA and hybrid PSOGSA algorithm. The ORPD multiobjective problem is tested over standard IEEE system. The test is performed under two conditions with and without penalty function added to the objective function. And all results obtained are summarized and best optimal solution is obtained from the hybrid PSOGSA algorithm. <s> BIB004
Fuzzy Goal Programming (FGP) has been presented in BIB002 BIB001 for solving the problem of reactive power and voltage control. The active power loss, voltage deviation and the voltage stability index (L-index) have been converted into a single-objective optimization problem. In BIB002 , GA has been employed as a solution tool to the FGP formulation to minimize the weighted sum of membership goals. Fuzzy adaptive particle swarm optimization (FAPSO) approach has been implemented based on the maximumminimum value of all membership functions of the objectives and constraints BIB001 . The main advantage of the FGP formulation is treating the multi-objective as a single objective optimization problem effectively without selecting weights or thresholds as in the weighted sum or econstraint methods, respectively. BIB003 . In  , this procedure has been applied for preparing different preventive control actions to overcome any emergency condition and to restore the system to the normal state Linear approximation using sensitivity parameters based on a modified model of fast decoupled load flow BIB004 A hybridization of PSO and GSA has been introduced to solve the ORPD problem to minimize the losses and the voltage deviations. Both objectives are treated using the weight factors This hybrid PSOGSA has better convergence rate compared to PSO and GSA