Optimal Unit Commitment Methods of Power System (original) (raw)
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Unit Commitment Problem in Electrical Power System: A Literature Review
International Journal of Electrical and Computer Engineering (IJECE), 2018
Unit commitment (UC) is a popular problem in electric power system that aims at minimizing the total cost of power generation in a specific period, by defining an adequate scheduling of the generating units. The UC solution must respect many operational constraints. In the past half century, there was several researches treated the UC problem. Many works have proposed new formulations to the UC problem, others have offered several methodologies and techniques to solve the problem. This paper gives a literature review of UC problem, its mathematical formulation, methods for solving it and Different approaches developed for addressing renewable energy effects and uncertainties.
International journal of engineering research and technology, 2018
This survey paper helps in the area of scheduling inconvenience of various generating units in electrical power system. It shows several common surveys of developments plus research in area of unit commitment centered on published articles and journals. A detailed survey is done in the sphere of unit commitment for finding different hybrid and non-hybrid methods by means of which unit commitment problem can be solved effectively. It will be quite helpful to the scientists, investigators or researchers employed in the region of the unit
SOLUTION APPROACHES FOR UNIT COMMITMENT PROBLEMS – AN ANALYSIS
Unit commitment (UC) problem is an important optimizing task for scheduling the on/off states of generating units in power system operation over a time horizon such that the power generation cost is minimized. Since, increasing the number of generating units makes it difficult to solve in practice, many approaches have been introduced to solve the UC problem. An effort to develop a unit commitment approach capable of handling large power systems consisting of both thermal and hydro generating units offers a large profitable return. In order to be feasible, the method to be developed must be flexible, efficient and reliable. In this paper, various proposed methods have been described along with their strengths and weaknesses. As all of these methods have some sort of weaknesses, a comprehensive algorithm that combines the strengths of different methods and overcomes each other's weaknesses would be a suitable approach for solving industry-grade unit commitment problem.
Solution of Unit Commitment Problem by using Artificial Intelligence Method
International Journal for Innovative Research in Science & Technology, 2018
An important criterion in power system is to meet the power demand at minimum fuel cost using an optimal mix of different power plants. Moreover, in order to supply electric power to customers in a secured and economic manner, unit commitment is considered to be one of the best available options. It is thus recognize that the optimal unit commitment results in a great saving for electric utilities. Unit Commitment is the problem of determining the schedule of generating units subject to device and operating constraints. The unit commitment has been identified for the thesis work. The formulation of unit commitment has been discussed and the solution is obtained by classic Dynamic Programming method, Ant Colony Optimization technique and or by Particle Swarm Optimization method. MATLAB codes have been generated for all the three methods to solve the unit commitment problem. The effectiveness of these methods has been tested on two systems comprising three units and six units and total operating cost is obtained. The results of unit commitment problem by all the three methods are compared for total operating cost and for computation time.
Implementation of Genetic Algorithm for Optimal Unit Commitment in a Power System
2018
The Genetic Algorithms (GA) are general optimization techniques based on principle inspired from the biological evolution. A simple GA algorithm implementation using the standard crossover and mutation operator could locate near optimal solutions but it most cases failed to converge to optimal solution. However, using the varying quality function techniques and adding problem specific operators, satisfactory solution was obtained. Test result, for systems of up to 100 units and comparisons with result obtained using Lagrangian relaxation and Dynamic programming are also reported. In this research, a genetic algorithm was applied to the unit commitment scheduling problem. A genetic It is hoped that the concurrent processing will enable the algorithm to operate within the needed response time of an electric utility power broker. The goal of this research is to determine if a genetic algorithm can be implemented to find good unit commitment schedules.
A Novel Approach for Unit Commitment
—This paper presents a new approach via hybrid particle swarm optimization (HPSO) scheme to solve the unit commitment (UC) problem. HPSO proposed in this paper is a blend of binary particle swarm optimization (BPSO) and real coded particle swarm optimization (RCPSO). The UC problem is handled by BPSO, while RCPSO solves the economic load dispatch problem. Both algorithms are run simultaneously, adjusting their solutions in search of a better solution. Problem formulation of the UC takes into consideration the minimum up and down time constraints, start-up cost, and spinning reserve and is defined as the minimization of the total objective function while satisfying all the associated constraints. Problem formulation, representation , and the simulation results for a ten generator-scheduling problem are presented. Results clearly show that HPSO is very competent in solving the UC problem in comparison to other existing methods. Index Terms—Hybrid particle swarm optimization (HPSO), industrial power system, optimization methods, power generation dispatch.