No abstract

No abstract

No abstract

Economic load dispatch problem is a popular optimization problem in electrical power system field, which has been so far tackled by various mathematical and metaheuristic approaches including Lagrangian relaxation, branch and bound method, genetic algorithm, tabu search, particle swarm optimization, harmony search, and Taguchi method. On top of these techniques, this study proposes a novel memetic algorithm scheme combining metaheuristic algorithm and gradient-based technique to find better solutions for an economic load dispatch problem with valve-point loading. Because metaheuristic algorithms have the strength in global search and gradient-based techniques have the strength in local search, the combination approach obtains better results than those of any single approach. A bench-mark example of 40 generating-unit economic load dispatch problem demonstrates that the memetic approach can further improve the existing best solutions from the literature.

This paper investigates the demand function for diesel in Korea covering the period 1986-2011. The short-run and long-run elasticities of diesel demand with respect to price and income are empirically examined using a co-integration and error-correction model. The short-run and long-run price elasticities are estimated to be −0.357 and −0.547, respectively. The short-run and long-run income elasticities are computed to be 1.589 and 1.478, respectively. Thus, diesel demand is relatively inelastic to price change and elastic to income change in both the short-run and long-run. Therefore, a demand-side management through raising the price of diesel will be ineffective and tightening the regulation of using diesel more efficiently appears to be more effective in Korea. The demand for diesel is expected to continuously increase as the economy grows.