Design System & Algorithm
R. Effatnejad; H. Aliyari; M. Savaghebi
Abstract
The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize ...
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The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize the power losses of transmission grid and the cost of energy generation and improve the voltage stability and voltage profile, considering environmental issues. Therefore, the OPF problem is a nonlinear optimization problem consisting of continuous and discontinuous variables. To solve it, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and a new hybrid algorithm combining modified Particle Swarm Optimization (PSO) and Genetic algorithm (GA) methods are proposed. In this method, each of the algorithms is performed in its procedure and generates the primary population; then, the populations are ordered and from among them, populations with the highest propriety function are selected. The first population that guesses will enter the two algorithms’ procedures for generating the new population. Note that the inputs of the two algorithms are the same; then, generates a new population. Now, there are three groups of populations: one created by modified GA, one created by modified PSO, and the other is the first initial population, and then sorted with the described sorting method.
Distribution Systems
Soheil Derafshi Beigvand; Hamdi Abdi,
Volume 3, Issue 2 , December 2015, , Pages 102-115
Abstract
This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel ...
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This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel flexible load curtailment cost associated with DLC programs. The load curtailment cost is based on a virtual generator for each load (which participates in DLC program). To implement the load curtailment in the objective function, we consider incentive payments for participants and a load shedding priority list in some events. The proposed OPF methodology is applied to IEEE 14, 30-bus, and 13-node industrial power systems as three examples of the smart grids, respectively. The numerical results of the proposed algorithm are compared with the results obtained by applying MATPOWER to the nominal case by using the DLC programs. It is shown that the suggested approach converges to a better quality solution in an acceptable computation time.
R. Kazemzadeh; M. Moazen; R. Ajabi-Farshbaf; M. Vatanpour
Volume 1, Issue 1 , June 2013, , Pages 1-11
Abstract
In this paper, a combinational optimization algorithm is introduced to obtain the best size and location of Static Compensator (STATCOM) in power systems. Its main contribution is considering contingency analysis where lines outages may lead to infeasible solutions especially at peak loads and it commonly ...
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In this paper, a combinational optimization algorithm is introduced to obtain the best size and location of Static Compensator (STATCOM) in power systems. Its main contribution is considering contingency analysis where lines outages may lead to infeasible solutions especially at peak loads and it commonly can be vanished by load-shedding. The objective of the proposed algorithm is firstly to prevent infeasible power flow solutions without undesired load-shedding, which is critical in contingency analysis; and secondly to mitigate overall power losses and costs. Moreover, active and reactive powers generation costs are considered in the proposed objective function. Since there are various constraints such as lines outages number, cost and their duration that must be taken to account, Bacterial Foraging oriented by Particle Swarm Optimization (BF-PSO) algorithm combined with Optimal Power Flow (OPF) is used to solve and overcome the complexity of this combinational nonlinear problem. In order to validate the accuracy of the proposed method, two test systems, including IEEE 30 bus standard system and Azarbaijan regional power system of Iran, are applied in simulation studies. All obtained optimization results show the effectiveness of the suggested combinational method in loss and cost reduction and preventing load-shedding.
