A stochastic multi-range robust approach for low carbon technology participation in electricity markets

Ambitious emission reduction targets require fostering more low-carbon technologies (LCTs) in distribution networks. Projections for future energy use predict a significant implementation of these technologies in residential areas. Despite this, individually they cannot effectively participate in electricity markets. This study examines the potential participation of residential LCTs (RLCTs) in multiple electricity markets, including wholesale day-ahead, real-time, and local energy markets (LEM), through the aggregators. We propose a stochastic weighted multi-range robust model to provide a strategy for RLCT aggregators to function as both sellers and buyers in these markets, as price-makers in LEM and price-takers in wholesale markets. The proposed model accounts for the uncertainty associated with the effect of offers/bids on the market clearing price of LEM and the availability patterns of aggregated LCTs. Results of a case study using realistic data reveal that the proposed approach results in higher overall profits compared to both risk-neutral and risk-averse robust methods. Furthermore, the introduced model is resilient to forecast errors, as evidenced by a 12% decrease in profits with the proposed approach compared to a 26% decrease with a risk-neutral strategy when the forecast error was increased by 20%.