Two-Stage Optimal Microgrid Operation with a Risk-Based Hybrid Demand Response Program Considering Uncertainty

Ho-Sung Ryu,Mun-Kyeom Kim

doi:10.3390/en13226052

Abstract

Owing to the increasing utilization of renewable energy resources, distributed energy resources (DERs) become inevitably uncertain, and microgrid operators have difficulty in operating the power systems because of this uncertainty. In this study, we propose a two-stage optimization approach with a hybrid demand response program (DRP) considering a risk index for microgrids (MGs) under uncertainty. The risk-based hybrid DRP is presented to reduce both operational costs and uncertainty effect using demand response elasticity. The problem is formulated as a two-stage optimization that considers not only the expected operation costs but also risk expense of uncertainty. To address the optimization problem, an improved multi-layer artificial bee colony (IML-ABC) is incorporated into the MG operation. The effectiveness of the proposed approach is demonstrated through a numerical analysis based on a typical low-voltage grid-connected MG. As a result, the proposed approach can reduce the operation costs which are taken into account uncertainty in MG. Therefore, the two-stage optimal operation considering uncertainty has been sufficiently helpful for microgrid operators (MGOs) to make risk-based decisions.

Highlights

In a smart-grid environment, distributed energy resources (DERs), such as renewable energy, have gained more attention than traditional power generation units owing to the increasing trend to address environmental concerns [1,2]
Value in a day-ahead market with expected scenario. This stage was simulated by considering the hourly average values of load, wind speed, and solar irradiance
In the first-stage, the microgrid operators (MGOs) uses economic demand response (DR) among the RH-demand response program (DRP) to optimize MG operation in a day-ahead market with expected scenario

Summary

Introduction

In a smart-grid environment, distributed energy resources (DERs), such as renewable energy, have gained more attention than traditional power generation units owing to the increasing trend to address environmental concerns [1,2]. Some of the most widely used renewable energy resources are wind turbine (WT) and photovoltaic (PV) systems because of the feasibility of existing related technologies. These forms of DERs are dependent on fluctuations and the unpredictive nature of wind and solar resources. Since the difficulty in managing distributed uncertainties by conventional power systems, microgrids (MGs) that can usefully control DERs have been introduced as a new concept [3]. MGs manage a cluster of loads and DERs, operating as a control to offer power locally. MGOs should be able to confirm the reliability of systems considering uncertain risk indices

Methods

Results

Conclusion