Tool and Methodology for Electric Vehicles Power Train Efficiency Optimization

Abstract

This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a dayahead market. The thermal unit commitment model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modeling of non-convex variable cost, nonlinear start-up cost, ramp rate limits and minimum up and down time constraints for thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous and self-dual interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the thermal generation schedule is demonstrated through the case study with detailed discussion.