Research On Contract Decision Model For Load Aggregators Considering Uncertainty Of User

With the increasingly serious energy and environmental crisis, as well as smart grid and electricity market developing, the small user of demand response resources is increasingly becoming an important way to respond to energy and environmental crisis in the further development and utilization of the world. Under the traditional model, small and medium users generally had been dispersed, independently on the market price-based demand response incentives to respond, because of its demand response behavior have been greater dispersion and uncertainty, it is difficult to directly participate in the electricity market in the trading of its demand responsiveness. With the advance of the electricity market, the user-side resources have more choices and ways to participate in market transactions, so there are a new class of transactions subject-load aggregators (LA). Load aggregators of demand response is a professional resource aggregation and authorized agencies, it gives the small user guide to the best way to participate in the market, however, the small user demand response uncertainties for load aggregators become a difficult problem facing operational decisions.Thesis combines theory and practice about the LA at home and abroad, introduce the some basic concepts of LA, including LA’s development, classification, operation mode, the key issue trading decisions. For the LA participation which enter ancillary services market level and alternate trading business contract decision-making problems, Author establish the cost-benefit analysis model to carry out the contracts traded;and focus on small and medium-considered response to aggregated user behavior of the uncertainty, with stochastic programming theory, author consider the uncertainty causing by Small User response behavior and LA opportunity costs and liquidated damages costs and other factors, and establish the LA contract optimization model, and the model is further considering the uncertainty and purchasing determine response resources to reducing risks. Author uses genetic algorithms embedded user responsiveness of small stochastic Monte Carlo simulation model to solve. Finally, design an example, and simulation about the small user response is closely related to the uncertainty of resource requirements for user responsiveness, LA compliance service levels and the compensation costs for uncertain demand response and other factors in decision-making mechanism of the LA contracts, give to verify the feasibility and rationality of the decision-making model.