Uncertainty modeling in optimal operation of energy hub in presence of wind, storage and demand response

Abstract

Renewable energy based Distributed Energy Resources (DERs) are essential of coping with greenhouse gases emission and growing energy needs. Combined Heat and Power (CHP), Wind, Energy Storage technologies (ES) and Demand Response programs (DR) have been confirmed the valuable resources. In this paper, Energy Hub (EH) as a super node in electrical distribution network receives various energy carriers; gas, electricity and wind in its input, and then after conversion, storage, direct connection or shifting demands provides hub required demands; electricity, heat, gas and water. The hub is optimally operated based on objective function considering economic, greenhouse gases emission, reliability and efficiency terms in predicted and stochastic environment of wind, electricity demand and Real Time Pricing (RTP) market. A Monte Carlo simulation is employed to generate scenarios tree based predicted RTP, wind and electricity demand. GAMS; high level algebraic modeling software is employed to reduce and read scenarios for Stochastic Programming in Mixed Integer Linear Programming (MILP) model of proposed approach to endorse when and what technologies should be optimally operated to achieve minimum operation costs and maximum reliability improvement with comparison of nine different cases (wind, price and electricity demand certainties and uncertainties) to satisfy a commercial load. Impact of DERs and effect of wind, price and demand uncertainties are investigated on total hub operation costs and hub reliability and also on which technology most be operated.