In this thesis we investigate the problem of energy cost minimization under the real-time pricing model The jobs in our problem are non-interruptible which is different from those examined in prior studies Moreover the future smart grid is capable of integrating distributed energy resources and storage equipment into the energy system We assume that each user is equipped with a photovoltaic panel and a battery Users can purchase energy from the grid to fulfill their energy demands Moreover they can use the renewable energy produced from the photovoltaic panel and the energy drawn from the battery or sell it back to the grid during peak hours in order to lower their electricity bills Because of the difficulty caused by intermittent renewable energy sources conventional optimization techniques cannot produce a reliable solution to the energy cost minimization problem We use a robust optimization approach to solve the problem and the problem is formulated as a two-stage robust optimization model We apply a column-and-constraint generation (C&CG) algorithm to obtain the solution to the problem We also propose a new algorithm called the robust demand side management (RDSM) algorithm The new algorithm consists of two portions: The first portion is a heuristic-based algorithm and is used to produce the appliance schedules for all users The second portion is based on dynamic programming and is used to utilize the photovoltaic panel and the battery According to the simulation results the proposed new algorithm can produce a solution with faster convergence as compared with the C&CG algorithm It can effectively handle the scheduling problem with uncertain renewable energy minimize the energy cost for each user and lower the peak-to-average ratio (PAR) of the energy system

Demand Side Management for Smart Grids with Distributed Uncertain Generation Using Two-Stage Robust Optimization

宇鋒, 徐. (Author). 2016 8月 4

學生論文: Master's Thesis