Virtual Power Plant Operation with Solar Power Forecast Errors and Demand Response

Abstract

Intermittent renewable energy production, determined by weather conditions, is increasing in power markets. Their efficient integration calls for flexible participants in smart power grids. It has been acknowledged that a huge underutilized flexibility resource lies on the electricity consumer-side. The activation of this demand flexibility is, however, a big challenge. Despite the recently risen interest towards demand flexibility, there is a gap in the literature investigating the incentives for consumers to offer their flexibility to power markets. It has been proposed that there needs to be a third-party operator aggregating and controlling this flexibility. In this paper we examine a concept of virtual power plant, which simultaneously optimizes the response of controllable electric hot water heaters to solar power forecast error imbalances. Uncertainty is included in the optimization in terms of solar power day-ahead forecast errors and balancing power market conditions. We show that the virtual power plant can add value from optimizing the combination of these resources. The results indicate that while the total profits are increasing, the marginal revenues are diminishing with the number of participating households. From a policy perspective, our results imply that market efficiency can be increased by allowing the aggregated resources to participate more freely in the markets.