Unit commitment-based load uncertainties based on improved particle swarm optimisation

ABSTRACT

This paper presents an intelligent method based on Improved Particle Swarm Optimisation to solve a unit commitment problem that takes into account the uncertainty in the demand. This uncertainty is included in the optimisation problem as a joint chance constraint that bounds the minimum value of the probability to jointly meet the deterministic power balance constraints. The demand is modelled as a multivariate, normally distributed, random variable and the correlation among different time periods is also considered. To demonstrate the effectiveness and robustness of the proposed algorithm, a system with 10 thermal and wind units with various conditions is simulated. The results and numerical experiments are compared with other methods to provide valuable information for both operational and planning problems.

KEYWORDS:

• Unit commitment
• IPSO
• load uncertainty
• electricity market

Disclosure statement

No potential conflict of interest was reported by the authors.