Scenario-Based Two-Stage Stochastic Scheduling of Microgrid Considered as the Responsible Load

Abstract

This article presents a novel linear programming (LP) based two-stage stochastic approach for microgrids (MGs) under uncertainties. In this regard, the day-ahead programming of dispatchable resources in MG was modeled, considering the uncertainties in demand loads, and upstream network electricity price. Moreover, the inherent stochastic nature of wind and solar resources as well as the environmental aspects were modeled to find a realistic solution. Also, real-time pricing (RTP), demand response (DR) program considering the energy storage system (ESS) as a DR option was implemented on an MG as a smart customer. The extensive form of the two-stage stochastic recourse model was properly implemented for dispatchable and non-dispatchable resources. Furthermore, scenario generation and reduction procedures were realized with autoregressive and moving average (ARMA) model-based time-series (TS), and backward reduction (BR) method by the Kantorovich distance (KD), respectively. The simulations on a grid-connected MG, including micro-turbine (MT), fuel-cell (FC), wind-turbine (WT), photovoltaic module (PV), and ESS were reported in operational cases based on one month of real recorded data for wind speed, solar irradiance, demand load, and upstream network electricity price. The results for the next day in real-time confirmed the accuracy of the developed optimization methodology.

Keywords:

• autoregressive and moving average (ARMA) model
• backward reduction
• demand response
• linear programming
• microgrid
• optimization
• scenario
• Stochastic programming
• two-stage model
• uncertainty

Additional information

Notes on contributors

Kamran Masoudi

Kamran Masoudi was born in Ilam, Iran, in April 1988. He received the B.Sc. degree from Shahid Chamran University, Ahvaz, Iran, in 2010, M.Sc. degree from Tabriz University, Tabriz, Iran, in 2013, and Ph.D. degree from Razi University, Kermanshah, Iran, in 2019, all in electrical engineering. His research interests include power systems operation and optimization, energy efficiency, smart grids, and demand response.

Hamdi Abdi

Hamdi Abdi was born in Paveh, Iran, in July 1973. He received the B.Sc. degree from Tabriz University, Tabriz, Iran, in 1995, and the M.Sc. and Ph.D. degrees from Tarbiat Modares University, Tehran, Iran, in 1999 and 2006, respectively, all in electrical engineering. He is currently an Associate Professor in the Department of Electrical Engineering, Razi University, Kermanshah, Iran. His research interests include power system optimization, operation and planning, smart grids, demand response, multi-carrier energy system, energy hub, load forecasting, and design of electrical and control systems for industrial plant.