Optimization of the Power Generation scheduling in Oil-Rig Platforms using Genetic Algorithm
[Show abstract] [Hide abstract] ABSTRACT: Demand Side Management (DSM) aims to benefit the consumer economically without taking into consideration the losses incurred during inefficient working of generating unit while supplying demand. This paper primarily focuses on generation and distribution parts of the grid. The multiple objectives that are opted for load scheduling are reduction in the electricity cost for the user and maximization of load factor benefitting the user as well as utility. Simulation results show that multi-objective approach proves advantageous in efficient and reliable operation of generating unit while supplying economically affordable electricity to the consumers. Extensive comparison between single objective and multi-objective approach is carried out, which is further justified with two-step and five-step tariff model.0Comments 1Citation
- "However these techniques are not capable of handling such non-linear, multidimensional and complex problems. Evolutionary algorithms such as GA have proved to provide apt results for such problems. Researchers had earlier considered multi-objective approaches as inwhere the objective of cost reduction and fitting to objective load curve are reckoned. "
- [Show abstract] [Hide abstract] ABSTRACT: Harmony Search (HS) algorithm is music based meta-heuristic optimization method which is analogous with the music improvisation process where musician continue to polish the pitches in order to obtain better harmony. The paper focuses on the optimal scheduling of the generators to reduce the fuel consumption in the oil rig platform. The accurate modeling of the specific fuel consumption is significant in this optimization. The specific fuel consumption has been modeled using cubic spline interpolation. The SFC curve is non-linear and discrete in nature, hence conventional methods fail to give optimal solution. HS algorithm has been used for optimal scheduling of the generators of both equal and unequal rating. Furthermore an Improved Harmony Search (INS) method for generating new solution vectors that enhances accuracy and convergence rate of HS has been employed. The paper also focuses on the impacts of constant parameters on Harmony Search algorithm. Numerical results show that the IHS method has good convergence property. Moreover, the fuel consumption for IHS algorithm is lower when compared to HS and other heuristic or deterministic methods and is a powerful search algorithm for various engineering optimization problems.0Comments 27Citations
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