Chance-Constrained Economic Dispatch with Flexible Loads and RES

TL;DR

This paper introduces a chance-constrained economic dispatch model incorporating multi-dimensional flexibility of loads to reduce renewable energy uncertainty impacts and stabilize electricity prices in day-ahead markets.

Contribution

It proposes a novel integration of flexible load bidding into a chance-constrained dispatch framework, enhancing market stability and efficiency with renewable energy sources.

Findings

MDF reduces locational marginal price volatility.

Flexible load bidding improves market efficiency.

Insights into the value of different flexibilities in MDF.

Abstract

With the increasing penetration of intermittent renewable energy sources (RESs), it becomes increasingly challenging to maintain the supply-demand balance of power systems by solely relying on the generation side. To combat the volatility led by the uncertain RESs, demand-side management by leveraging the multi-dimensional flexibility (MDF) has been recognized as an economic and efficient approach. Thus, it is important to integrate MDF into existing power systems. In this paper, we propose an enhanced day-ahead energy market, where the MDFs of aggregate loads are traded to minimize the generation cost and mitigate the volatility of locational marginal prices (LMPs) in the transmission network. We first explicitly capture the negative impact of the uncertainty from RESs on the day-ahead market by a chance-constrained economic dispatch problem (CEDP). Then, we propose a bidding mechanism for the MDF of the aggregate loads and combine this mechanism into the CEDP for the day-ahead market. Through multiple case studies, we show that MDF from load aggregators can reduce the volatility of LMPs. In addition, we identify the values of the different flexibilities in the MDF bids, which provide useful insights into the design of more complex MDF markets.