Robust Optimization Based Multi-level Coordinated Scheduling Strategy for Energy Hub in Spot Market

Abstract

Ensuring adequate energy supply and maximizing profitability are essential for energy hub(EH)-based Integrated Energy Service Providers (IESPs), which rely on optimal scheduling strategies for EH. However, multiple uncertainties exist in renewable energy output and multi-energy consumers. In addition, the energy prices in the day-ahead and real-time spot market are different and difficult to forecast, which brings additional uncertainty, making the energy management of EH very complex and difficult. To address this problem, we propose a robust optimization based multi-level coordinated scheduling strategy for energy hub in spot market. The first level is the day-ahead decision-making stage, where accurate information about the uncertainty distribution may not be available, so the strategy considers the worst-case, secures energy supply, and pre-purchases power in the day-ahead market. The subsequent levels are intra-day decision-making stages where multiple uncertainties are gradually revealed. In addition, according to the real-time electricity price, multiple stages within the strategy cooperate with each other, which can not only take into account the future uncertainties, but also offset the real-time uncertainties by adjusting the scheduling decisions made by the previous stages. In addition, the proposed optimal scheduling strategy was applied to a real simulation scenario. Taking the PJM business rules as an example, extensive simulation results demonstrate its effectiveness and advantages.