Quantifying value pools for distributed flexible energy assets

Abstract

Flexible energy assets in private households enable many valuable services in the context of a sustainable energy transition. We introduce a combination of a heuristic model and a linear optimization model for the electricity demand of a single-family household with the option to include an electric vehicle. A hybrid model including a heuristic and a Mixed Integer Liner Optimization (MILP) allows to optimize the stacked value across five distinct use cases: (1) maximization of self-consumption; (2) reduction of load peaks; (3) utilization of flexible electricity prices; (4) provision of frequency control reserve (FCR); and (5) reduction of battery aging. We investigate costs and benefits for each use case and, based on data and legislation for Germany, find that several of these use cases result in cost savings of up to €50 per year. Surprisingly, simultaneous investigation of multiple use cases reveals that some combinations show synergetic effects rather than the expected cannibalizing ones. The insights gained are of special importance in the context of designing business models for the aggregation of distributed flexible energy assets, i.e. by an “Energy Supplier 2.0”, with the aim to tap unused flexibility potentials, thus utilizing multiple additional revenue streams.