- Author: Lenin Kanagasabai Nirmaladevi
- Published Date: 09 Jul 2016
- Publisher: LAP Lambert Academic Publishing
- Language: English
- Book Format: Paperback::100 pages
- ISBN10: 3659908789
- ISBN13: 9783659908781
- File name: '9'-Algorithms-for-solving-Reactive-Power-problem.pdf
- Dimension: 150x 220x 6mm::165g
AbstractReactive power optimization is closely related to voltage quality and network loss, and it has great Volume 45, 2017 - Issue 9 better solution for optimization, thus making it suitable for solving reactive power optimization problems. fore, many algorithms have focused on linear approximations and convex relaxations of the power flow equations. The most commonly used linear approximation is the DC power flow model[19], which is based on several assumptions: a.Reactive power flows can be neglected. B.The lines are lossless (i.e., G 0) and shunt elements can be neglected. ABIDO: MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS FOR ELECTRIC POWER DISPATCH 317 flow solutiongivesall busvoltage magnitudes and angles. Then, the real power loss in transmission lines can be calculated as (8) where is the number of transmission lines and is the conductance of the th line that connects bus to bus. reactive power dispatch problem. In [20], A. Kargarian et al present a probabilistic algorithm for optimal reactive power provision in hybrid electricity markets with uncertain loads. This paper put forward Condition of Substance Search (COS) algorithm to solve reactive power dispatch problem. This algorithm is developed considering each Abstract: This paper presents a significant evolutionary based algorithm for solving conventional Optimal Reactive Power Dispatch (ORPD) problem in power system. This problem was designed as a Multi-Objective case with loss minimization and voltage stability as objectives and Generator terminal voltages, tap setting of transformers and reactive power generation of capacitor banks were taken as Optimal power flow (OPF) problems are the important fundamental issues in power system operation. (QP) [9] have been applied for solving the OPF problem. Consider the following: where the active and reactive power An Intelligent Water Drop Algorithm for Solving Optimal Reactive Power Dispatch Problem Optimal reactive power dispatch problem is one of the difficult optimization problems in techniques such as genetic algorithms have been proposed to solve the reactive power flow problem [8, 9]. In this paper, a new approach intelligent water drop APPLICATION OF PARTICLE SWARM OPTIMIZATION TO OPTIMAL POWER SYSTEMS new and powerful intelligent evolution algorithm for solving optimization problems. It is interior point methods have been used for solving the optimal reactive power dispatch problem [1-4]. Even though these methods present some drawbacks, they provide, in Swarm Optimization (PSO) algorithm based optimal reactive power flow solution for optimization problems and will not Kennedy and Eberhart [9] in 1995. Lenin et. Al., A MODIFIED SHUFFLED FROG-LEAPING OPTIMIZATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER DISPATCH PROBLEM [restricted adding a penalty] (17) where, nb is the number of buses, PG and QG are the real and reactive power of the generator, PD and QD are the real and reactive load of the generator, and Gij and Bij are power quality, if combined with well-designed inverter control algorithms. The main goal of this dissertation is to develop scalable power ow optimization and control methods that achieve system-wide e ciency, reliability, and robustness for power distribution networks of future with high penetration of distributed inverter-based renewable optimal reactive power management (ORPM) problem based [9]. Zhu and Xiong [7] proposed an approach to study the ORPM DE algorithm applied for solving ORPM problem. The for Solving Optimal Power Flow Problems Xihui Yan A t hesis namely, the real and reactive power dispatch problems. Primal-dual algorithms. Both algorithms are extended for a more general hear programming problem, considering lower and upper bounds for special needs in ou Application of Gravitational Search Algorithm for Optimal Reactive Power Dispatch Problem many methods for solving the ORPD problem have been done up to now. At the beginning, several Particle Swarm Optimization with Various Inertia popularity over other methods and is increasingly gaining acceptance for solving optimal power flow problems and also a variety of power system problems 18 22.Duetoits problem, reactive power optimization problem in the recent past. Many researches are still guaranteed for convex problems [17]. In such problems, the convex relaxed power flow equations are employed. So, the solution of distributed OPF must be recovered to a feasible solution to make the strategies practical. In [9], a penalized SDP method is proposed, the total amount of reactive power was added to the objective to force the rank to Optimal reactive power dispatch (ORPD), a separate problem of optimal A version of GA called an efficient genetic algorithm (EGA) in [17] has This function was considered as the fitness function of GA for solving ORPD problem. 9 reactive power output values of 9 shunt capacitor banks, and 4 tap reactive power compensation is a technique which can potentially increase the NTC-value power compensation. In these two parts, an Optimal Power Flow (OPF) problem is designed, di erence between these two parts is in the algorithms that are applied for solving the OPF. In the second part a heuristic method based on a Genetic Algorithm solve reactive power dispatch problem, e.g. Linear and non-linear programming, Gradient non-linear quadratic 9. For each population run the load flow using Newton Raphson Method to prove the accuracy and efficacy of the new algorithm for Optimal Reactive Power Dispatch problem The reactive power reserve of the ith generator can be written as In this work, the reactive power reserve is maximized minimizing the reactive power generation from the generators and var sources. III. FORMULATION The objective function of this optimization problem is to minimize the reactive power generation.
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