Financial Risk-Based Scheduling of Microgrids Accompanied by Surveying the Influence of the Demand Response Program

TL;DR

This paper develops a mixed-integer programming approach to optimize microgrid profit while managing risk, considering demand response programs and uncertainties in renewable sources and loads, with simulation validation.

Contribution

Introduces a novel optimization framework that balances profit maximization and risk minimization in microgrids under demand response and uncertainty.

Findings

Implementing demand response increases profit but also risk.

Considering downside risk constraints reduces risk with minimal profit loss.

Simulation confirms effectiveness of the proposed risk management approach.

Abstract

This paper presents an optimization approach based on the mixed-integer programming (MIP) to maximize the profit of the Microgrid (MG) while minimizing the risk in profit (RIP) in the presence of demand response program (DRP). RIP is defined as the risk of gaining less profit from the desired profit values. The uncertainties associated with the RESs and loads are modeled using normal, Beta, and Weibull distribution functions. The simulation studies are performed in GAMS and MATLAB for 5 random days in a year. The simulation results show that RIP is reduced when downside risk constraint (DRC) is considered and DRP is implemented. Although DRP increases the total profit of the MG, it also notably increases the risk. On the other hand, considering DRC significantly reduces the percentage of the risk with a slight decrease in the profit.