Reactive Power Planning Based on Genetic Algorithms (original) (raw)
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Improved Genetic Algorithms ( IGA ) for Optimal Reactive Power Planning in Loss Minimisation Scheme
2004
The increasing demand of electrical power has caused the system network to be in stressed condition which led to transmission loss in the system. Consequently, voltage profile of the system decays accordingly leading to unpredictable voltage instability phenomenon. The issue of loss minimisation has been progressively investigated in the power system environment. Many techniques have been developed in the past in order to minimise transmission loss towards the improvement of voltage profile. This paper presents the application of Improved Genetic Algorithms (IGA) in order to optimise the reactive power planning (RPP) for loss minimisation in power system. In this study, an IGA engine is developed in order to implement the optimisation for the combination of reactive power dispatch and transformer tap changer setting. Two selection techniques namely the anchor spin and population spin were explored in order to investigate the merit of each technique. The selection technique is a vari...
IEEE Transactions on Power Systems, 1999
A hybrid methodology is presented for the solution of the problem of the optimal allocation of reactive power sources. The technique is based upon a modified genetic algorithm (G.A.), which is applied at an upper level stage, and a successive linear program at a lower level stage. The objective is the minimization of the total cost associated to the installation of the new sources. The genetic algorithm is devoted to defining the location of the new reactive power sources, and therefore to handle the combinatorial nature of the fixed costs problem. At the lower level, the variable cost problem is solved by, calculating the magnitude of the sources to be installed at the previously determined locations by means of a linear prngram iterated successively with a fast decoupled load flow. Results are presented for the application of the proposed methodology when applied to the Venezuelan electric network.
Application of Genetic Algorithm for Reactive Power Disptach with Voltage Stability Constraints
This paper presents a Genetic Algorithm (GA) - based approach for solving optimal Reactive Power Dispatch (RPD) including voltage stability limit in power systems. The monitoring methodology for voltage stability is based on the L-index of load buses. Bus voltage magnitudes, transformer tap settings and reactive power generation of capacitor banks are the control variables. A binary-coded GA with tournament selection, two point crossover and bit-wise mutation is used to solve this complex optimization problem. The proposed algorithm has been applied to the IEEE 30-bus system to find the optimal reactive power control variables while keeping the system under safe voltage stability limit, and found to be more effective for this task.
Bulletin of Electrical Engineering and Informatics
In this paper power quality of 3-bus solar-based hybrid system has been presented (where one or more than one distribution generator unit is connected to the grid). The injection of solar power into grid-connected systems creates power quality problems such as current consistency, electrical fluctuations, and inefficient power demand. A power quality control strategy based on a real-time self-regulation method for autonomous microgrid operation has been presented. In this paper solar farm design and satisfactory performance tests such as PV-static synchronous compensator (STATCOM) to improve the power quality of grid-based systems have been presented using the MATLAB/Simulink environment. Pulse width modulator (PWM) with proportional-integral derivative (PID) controller used for frequency control, reactive var compensation is used to control voltage profile. Multi-objective genetic algorithm (MOGA) for reactive power planning (RPP) with the objective of reactive power minimization i...
2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491)
In this paper, the application of a novel and computationally enhanced genetic algorithm (CA) for solving the reactive power dispatch problem is presented. In order to attain a significant reduction in the computational time of GA, a systematic procedure of reactive power control device preselection mechanism is herein proposed to choose a-priori subsets of the available control devices, which maximally influence buses experiencing voltage limit violations. The GA reactive power dispatch module then accesses such judiciously pre-selected control device candidates to determine their optimal settings. A pragmatic scheme aimed at further curtailing the number of the final control actions entertained is also set forth. The farreaching simulation results obtained for two case study scenarios using the proposed algorithmic procedures on a German utility network of Duisburg, replicated on an operator-training simulator, are presented and fully discussed in depth.
Multi Objective Reactive Power Planning Using Particle Swarm Optimization Technique
2011
This paper addresses an optimal Reactive Power Planning (RPP) of power system. The Static Var Compensator (SVC) is introduced into power system in order to reactive power support and voltage control. The locations and the outputs of SVCs are determined using our proposed optimal reactive power planning model. The proposed method optimizes several objective functions at the same time within one general objective. The optimized objectives are minimization of total investment in reactive power support, average voltage deviation and minimization of total system loss. These objective functions are one of the most important objectives for every transmission and distribution systems. Particle Swarm Optimization technique (PSO) is used to solve the optimization problem. The validity of the proposed method is tested on a typical power system.
Reactive Power Planning for Loss Minimization Using Simulated Annealing
2011
This paper addresses an optimal Reactive Power Planning (RPP) of power system. The Static Var Compensator (SVC) is introduced into power system in order to reactive power support and voltage control. The locations and the outputs of SVCs are determined using our proposed optimal reactive power planning model. The proposed method optimizes several objective functions at the same time within one general objective. The optimized objectives are minimization of total investment in reactive power support, average voltage deviation and minimization of total system loss. These objective functions are one of the most important objectives for every transmission and distribution systems. Simulated Annealing technique (SA) is used to solve the optimization problem. The validity of the proposed method is tested on a typical power system.
A new reactive power planning procedure for Iranian Power Grid
Electric Power Systems Research, 2004
Reactive power planning has received considerably attention during the last few years. Allocation of reactive power resources of both static (ex. switchable capacitors and/or reactors) and dynamic (ex. static VAr compensators, or SVCs) types can have major impacts on voltage security (i.e. voltage profile and stability) and active power losses. They, however, impose costs so that the planning procedure is, indeed, an optimization problem in which the resources should be so allocated and sized that optimum performance, in terms of voltage profile and stability and minimum active power losses are achieved while, at the same time, minimum reactive power resource costs are imposed.
Reactive Power Planning Using a New Hybrid Technique
Voltage deviation and stability constrained VAr planning or Reactive Power Planning (RPP) is an important challenging issue in power systems. This paper presents a new hybrid technique for modeling and solving RPP problem taking into account the static voltage stability constraint. First, the uncertain fuzzy clustering theory is employed to select new candidate VAr source locations. Then, modified Gray code is applied and used to represent a series of non-uniform VAr capacity intervals at different candidate buses. Based on the new ordering of the VAr capacity intervals, a simplified piecewise linear function between the Total Transfer Capability (TTC) and new VAr capacity is derived and applied as static voltage stability constraint in RPP problem. Lastly, the RPP optimization problem is solved by a self adaptive Fuzzy Chaotic Interactive Honey Bee Mating Optimization (FCIHBMO) technique taking advantage of the modified Gray code. In the FCIHBMO algorithm, a modified definition of the updating factors on generation solution is proposed. In the case study, uncertain fuzzy clustering mechanism, the modified Gray code, and the modified HBMO are applied to the IEEE 118-bus and IEEE 300-bus systems. Test results conclude that the proposed hybrid technique is a simplified and effective approach for voltage stability constrained VAr planning with contingency considered.
Enhancement of Voltage Stability in the Power System Using Genetic Algorithm
Journal of applied engineering, technology and management, 2022
The power system should ensure safe and consistent power to the customer. For secure operation, the voltage should be within the desired limits, or else it will result in voltage collapse and power losses. The power system will be more competent, economic, reliable, and reduce power losses if the voltage stability is enhanced. Since the voltage stability is determined by the reactive power of the network, a reactive power source should be provided to safeguard the stability of the power system. This paper presents the enhancement of voltage stability in the power system using a Genetic Algorithm (GA). The GA approach is used to find the optimal value of control variables such as generator bus voltage, shunt capacitance, and transformer tap setting which are the source of reactive power. The GA was executed via MATLAB programming with MATPOWER. The propounded method was tested on the western grid of Bhutan to minimize the real power losses. The results demonstrate improved voltage stability in the power system and a significant reduction in power losses. The results will help Power System Operators to make a better decision while encountering voltage issues in their power lines. Moreover, this research will guide future research in dealing with similar research especially in calculating the optimal location of FACT devices for reactive power compensation.