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Articles by D.P. Kothari
Total Records ( 4 ) for D.P. Kothari
  S.K. Bath , J.S. Dhillon and D.P. Kothari
  This stidy explores the use of genetic algorithm and Hooke-Jeeves search methods to search for the optimum active power generation schedule of thermal power systems, so as to obtain the best compromised solution, in the multi-objective framework. The multi-objective problem is formulated to minimize non-commensurable objectives viz. operating cost, NO emission and variance of active power generation with x explicit recognition of statistical uncertainties in the thermal power generation cost coefficients, emission coefficients, power demands and hence power generations and bus voltages, which are considered random variables. Inequality constraint to maintain security of transmission lines with respect to active power flow and equality constraint of active power balance are considered in the form of objective functions to be optimized. The objectives are quantified by defining their membership functions using fuzzy set theory The solution set of such formulated problems is non-inferior due to contradictions among the objectives taken. Active power generations are searched by genetic algorithm and Hooke-Jeeves search methods in the non-inferior domain. Among the generated set of non-inferior solutions of power generation schedules, system operator chooses the set that provides maximum satisfaction level of the most under achieved objective in terms of membership function and is termed as fitness function. The validity of the proposed methods is demonstrated and results are compared for an IEEE system comprising of 25-nodes, 35-lines and 5-generators.
  S. Jarnail Dhillon , J.S. Dhillon and D.P. Kothari
  This study deals with decision making methodology based on fuzzy set theory to determine the optimal generation schedule of multi-objective problem with due consideration of uncertainties in system input data and system load. The stochastic models are converted into their deterministic equivalent by taking their expected values. To determine trade-off relationship between conflicting objectives in the non-inferior domain, the weighting method is exploited. In this method, the multiobjective problem is first converted into a scalar optimization problem and then weights are searched in a systematic manner. A new interactive search technique based on binary successive approximation method is devised to search weights assigned to the objectives and incremental cost to obtain the non-inferior solution. Binary coded strings are used to represent weights assigned to the objectives as well as the incremental cost and the continuous values are obtained to represent a point in the search space through mapping. Once the trade-off has been obtained, fuzzy set theory helps the Decision Maker (DM) to choose the optimal operating point over the trade-off curve and adjust the generation schedule in the most preferred economic manner. This method has shown improvement because the weights are searched for more significant digits in fixed number of iterations. The validity of the proposed method has been examined on a sample system and the results are compared with the efficient method to solve the scalar objective problem and weight pattern is searched by evolutionary search method.
  Jarnail S. Dhillon , J.S. Dhillon and D.P. Kothari
  A new heuristic search technique based on binary successive approximation method is applied to the problem of determining the optimal schedule of power generation in a hydro thermal power system The main objective for hydrothermal operation is not only to minimize the total system operating cost, represented by the fuel cost required for system’s thermal generation subject to the operating constraints of hydro and thermal plants, over the optimization interval but also to consider the environmental and system security objectives. Normally, the decision making input system data were assumed to be well behaved and deterministic. But in practical situations the input system data cannot be predicted and estimated with hundred percent certainties. It is bound to vary depending upon the uncertainties, load changes, load forecasting errors, ageing of equipment etc. It is worthwhile to assume the system data as variable and uncertain for more realistic approach. In this study an attempt has been made to solve fixed head short-term hydro-thermal generation scheduling problem in the multi objective framework by taking into account the statistical variation of various system parameters such as variance of cost and emission coefficients of generators, variance of power, generation mismatch etc.
  Jarnail S. Dhillon , J.S. Dhillon and D.P. Kothari
  This study presents the application of the decision making methodology based on fuzzy set theory to determine the optimal generation schedule of multi-objective problem with due consideration of uncertainties in system input data and system load. The stochastic models are converted into their deterministic equivalent by taking their expected values. To determine trade-off relationship between conflicting objectives in the non-inferior domain, the weighting method is exploited. A new heuristic search technique based on binary successive approximation method is devised to search weights assigned to the objectives and incremental cost to obtain the non-inferior solution. Binary coded strings are used to represent weights assigned to the objectives as well as the incremental cost and the continuous values are obtained to represent a point in the search space through mapping. Once the trade-off has been obtained, fuzzy set theory helps The Decision Maker (DM) to choose the optimal operating point over the trade-off curve and adjust the generation schedule in the most preferred economic manner. This method has shown improvement because the weights are searched for more significant digits in fixed number of iterations. The validity of the proposed method has been examined on a sample system and the results are compared with the similar existing methods.
 
 
 
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