Microgrid Optimal Energy Scheduling with Risk Analysis

TL;DR

This paper introduces a risk-aware optimization framework for microgrid energy scheduling, enhancing resilience during grid disconnections by integrating renewable sources and storage.

Contribution

It develops a conditional value at risk (cVaR) based approach for microgrid scheduling, incorporating renewable energy and storage to improve resilience during outages.

Findings

Microgrid scheduling with cVaR improves power reliability.

Renewable energy integration reduces operational costs.

Resilience against outages is significantly enhanced.

Abstract

Risk analysis is currently not quantified in microgrid resource scheduling optimization. This paper conducts a conditional value at risk (cVaR) analysis on a grid-disconnected residential microgrid with distributed energy resources (DER). We assume the infrastructure to set up an ad-hoc microgrid is already in place for a residential neighborhood with power sources such as photovoltaic (PV), diesel, and battery energy storage system (BESS). With this scenario in mind, we solve day-ahead scheduling to optimally allocate various resources to match demand in scenarios where neighborhoods, especially residential, are disconnected from the overall grid such as in flooding, hurricanes, winter storms, or operational failures. The goal is to provide an alternative framework to optimize power availability for priority customers and strengthen the overall grid against dips in power outside of normal operating considerations. The focus of this paper will be taking in renewable energy sources from PV combined with diesel and BESS while minimizing cost. Case studies demonstrate that with the proposed energy management system, microgrids can be implemented to be more resilient against new challenges.