Determination of Stochastic-Based Short Term Optimal Strategy for Retailer

This paper proposes a decision-making framework, based on stochastic programming for an electricity retailer operating in a competitive electricity market environment. The operations framework is a two-stage model in which at the first stage, the retailer plans its operation in a day-ahead horizon. This stage is modeled as a stochastic mathematical optimization. The objective of this model is cost minimization, and the model has been solved as a mixed integer nonlinear stochastic programming. Solving this problem, the retailer's operational decisions on grid purchase, scheduling of distributed generation (DG) units owned by retailer, and decision for interruptible load (IL) would be determined. These decisions are imposed as boundary constraints in the second stage. The second deals with retailer's activities in hourly-ahead market. The retailer seeks to maximize its short-term profit keeping in mind its day-ahead decisions. In hour-ahead stage, he/she determines the power purchase from the grid, ILs contract and the production level of each DG units; both in the energy and reserve market. Dayahead stage employs roulette wheel mechanism and Lattice Monte Carlo Simulation (LMCS) for random adaptive oneday scenario generation wherein the stochastic procedure is converted into its respective deterministic equivalents. A case study is illustrated to demonstrate the capability of the proposed method

کلیدواژه ها:

Retailer ، distributed generation ، interruptible load ، stochastic programming