Optimal Power Flow Analysis of IEEE-30 bus System using Genetic Algorithm Techniques
Abstract
This paper is focused at providing a solution to optimal power flow problem in power systems by using Genetic Algorithm approach. The proposed approach finds the optimal setting of OPF control variables which include generator active output, generator bus voltages, transformer tap-setting and shunt devices with the objective function of minimizing the fuel cost. The proposed Genetic Algorithm technique is modelled to be flexible for implementation to any power systems with the given system line, bus data, generator fuel cost parameter and forecasted load demand. Proposed genetic algorithm technique has been analyzed and tested on the standard benchmark IEEE 30-bus system. Results obtained after applying both optimization techniques on American Electric IEEE 30-bus system with the same control variable maximum & minimum limits and system data have been compared and analyzed. Proposed method efficiently optimizes and solves the optimal power flow problem with high efficiency and wide flexibility for implementation and analysis on different power system networks.
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Introduction
The OPF Problem has been discussed since its introduction by Carpentier in 1962. As the OPF is a very large, non-linear mathematical programming problem, it has taken decades to develop efficient algorithm for its solution. Many different mathematical techniques have been employed for its solution. OPF has been applied to regulate generator active power outputs and voltages, shunt capacitors/reactors, transformer tap settings and other controllable variables to minimize the fuel cost, network active power loss, while keeping the load bus voltages, generators reactive power outputs, network power flows and all other state variables in the power system in their operational and secure limit .By considering the maximum / minimum outputs of generator, maximum MVA flows on transmission lines and transformers and bus voltages at their specified values, the primary goal of OPF is to minimize the generation cost for a particular given load demand. The secondary goal or another importance of OPF problem is the determination of marginal cost data. The marginal cost data deals with pricing MW transactions cost of auxiliary equipment that are required for reactive power (MVAr) for voltage support. The third goal of OPF is to monitor system security issues and also carry out necessary corrective actions. For planning studies, Optimal Power Flow is used to determine the maximum stress that a planned transmission system can withstand. To provide a preventive dispatch, the OPF can be set up if the security constraints are incorporated. In case of emergency, when some component of the system is overloaded or a bus is experiencing a voltage violation, the Optimal Power Flow can provide a corrective dispatch, which tells the system’s operators what kind of adjustments can be performed in order to mitigate the overload or voltage violation problems. The calculation of the optimum generation pattern in order to achieve the minimum cost of the generation together while transmission system limitations are not violated. The OPF can be calculated by checking optimum settings for generation voltages, transformers taps and switch-able capacitors or static VAr components (called “Voltage- VAR” optimization) periodically [1].
Conclusion
This paper mainly studied the PSO method and GA method. It is used to provide the solution involving numerical analysis. The PSO method and GA method needs less number of iterations to reach convergence, and is more accurate and not sensitive to the factors. In addition, this project also studied optimal power flow based the IEEE 30 bus system. Optimal power flow is the condition that the cost of overall power system is the lowest. This project concerns a general cost minimization problem to solve the power flow problem based on IEEE 30 bus system.