Fuzzy Logic Based Solution to the Unit Commitment Problem (original) (raw)
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Solving the Unit Commitment Problem Using Fuzzy Logic
International Journal of Computer and Electrical Engineering, 2011
This paper presents an application of the fuzzy logic to the unit commitment problem in order to find a generation scheduling such that the total operating cost can be minimized while satisfying a variety of constraints. The optimization algorithm employed to solve the unit commitment problem benefits from the advantages of dynamic programming and the fuzzy logic approaches in the purpose of obtaining preferable unit combinations at each load demand. As a case study, the four-generating unit thermal power plant of Tuncbilek in Turkey is used. The purpose is to show that the fuzzy logic based approach achieves a solution to the unit commitment problem that is logical, feasible and with economical cost of operation which is the main objective of unit commitment. The results obtained by the fuzzy logic are tabulated, graphed and compared with that obtained by the dynamic programming. The outcomes show that the implementation of fuzzy logic provides a feasible solution with significant savings.
Fuzzy-Logic-Based Approach to Solve the Unit-Commitment Problem
2012
This study presents an application ofthe fuzzy-logic to solve the unit commitment problem in general and in particular to find unit combinations and their generation scheduling to bring the total operating cost to a minimum, when subject to a variety of constraints. This approach allows a qualitative description of the behavior of a certain system,the system's characteristics, and the response without the need for exact mathematical formulations. This approach is demonstrated by employing a four-generation-units thermal power plantas a case study. The goal is to show that a fuzzy-logic-basedapproach achieves logical, feasible, and economical operation of the power generation plant, which is the main objective of solving the unit commitment problem. It is worth mentioning that the algorithm in this study benefits from the dynamic programming and fuzzy logic approaches in orderto obtain preferable unit combinations at each time period and the ability of representing the results in...
A new fuzzy unit commitment model and solution
This paper presents a new fuzzy unit commitment problem (UCP) model. The model treats the uncertainties in the load demand and the spinning reserve constraints in a fuzzy logic (FL) frame. The simulated annealing (SA) method is used to solve the combinatorial part of the unit commitment problem, while the nonlinear part of the problem is solved via a quadratic programming routine. A polynomial time cooling schedule is used in the implementation of the SA algorithm. Numerical results show the superiority of the solutions obtained compared to methods with traditional UCP models.
IJERT-Solution of unit commitment problem both in traditional and deregulated environment IJERTV1IS
International Journal of Engineering Research and Technology (IJERT), 2012
https://www.ijert.org/solution-of-unit-commitment-problem-both-in-traditional-and-deregulated-environment https://www.ijert.org/research/solution-of-unit-commitment-problem-both-in-traditional-and-deregulated-environment-IJERTV1IS8534.pdf This project applies modified GA to the UC problem and illustrates details of the performance of Genetic Algorithm. The aim of this work is to propose the suitability of a new approach to the solution of the UC problem in both traditional and deregulated environments. In this approach, the GA maintains a population of highly fit chromosomes or strings and probabilistically modifies the population seeking a near optimal solution to the given task. A program is developed in MATLAB 6.1 for the proposed method for solving the UC problem. MATLAB 6.1 is a high-performance language for technical computing [32]. The name MATLAB stands for matrix laboratory. It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation.
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.
Solution to the unit commitment problem using an artificial neural network
Turkish Journal of …, 2013
This paper proposes a real-time solution to the unit commitment problem by considering different constraints like ramp-up rate, unit operation emissions, next hours load, and minimum down time. In this method, an optimized trade-off between cost and emission has been taken into consideration. The effectiveness of the proposed method was verified by the significant outcomes demonstrated.
IJERT-Thermal unit commitment using fuzzy logic
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/thermal-unit-commitment-using-fuzzy-logic https://www.ijert.org/research/thermal-unit-commitment-using-fuzzy-logic-IJERTV2IS1406.pdf The Unit Commitment Problem is to determine a minimal cost turn-on and turn-off schedule of a set of electrical power generating units to meet a load demand while satisfying a set of operational constraints such as power generation-load balance, spinning reserve, operating constraints, minimum up time & minimum down time, etc. The production cost includes fuel, startup, shutdown, and no-load costs. Several conventional methods are available to solve the unit commitment problem. This paper describes the application of fuzzy logic algorithm for determining short term commitment of thermal units in electrical power generation. This method allows a qualitative description of the behavior of the system, the system characteristics and response without the need for exact mathematical formulations. It is demonstrated through a numerical example that a fuzzy logic based approach achieves a logical and feasible economic cost of operation of the power system, which is the major object of Unit commitment. The results obtained from fuzzy logic based approach are compared with the priority list method solution to unit commitment problem.
Mathematical Problems in Engineering, 2014
Due to the continuous increase of the population and the perpetual progress of industry, the energy management presents nowadays a relevant topic that concerns researchers in electrical engineering. Indeed, in order to establish a good exploitation of the electrical grid, it is necessary to solve technical and economic problems. This can only be done through the resolution of the Unit Commitment Problem. Unit Commitment Problem allows optimizing the combination of the production units’ states and determining their production planning, in order to satisfy the expected consumption with minimal cost during a specified period which varies usually from 24 hours to one week. However, each production unit has some constraints that make this problem complex, combinatorial, and nonlinear. This paper presents a comparative study between a strategy based on hybrid gradient-genetic algorithm method and two strategies based on metaheuristic methods, fuzzy logic, and genetic algorithm, in order t...
A solution to the unit commitment problem—a review
Frontiers in Energy, 2013
Unit commitment (UC) is an optimization problem used to determine the operation schedule of the generating units at every hour interval with varying loads under different constraints and environments. Many algorithms have been invented in the past five decades for optimization of the UC problem, but still researchers are working in this field to find new hybrid algorithms to make the problem more realistic. The importance of UC is increasing with the constantly varying demands. Therefore, there is an urgent need in the power sector to keep track of the latest methodologies to further optimize the working criterions of the generating units. This paper focuses on providing a clear review of the latest techniques employed in optimizing UC problems for both stochastic and deterministic loads, which has been acquired from many peer reviewed published papers. It has been divided into many sections which include various constraints based on profit, security, emission and time. It emphasizes not only on deregulated and regulated environments but also on renewable energy and distributed generating systems. In terms of contributions, the detailed analysis of all the UC algorithms has been discussed for the benefit of new researchers interested in working in this field.