The shift from centralized to decentralized energy provision has created an opportunity for a wide range of distributed energy resources. In deciding how to best serve their long-term energy needs, end consumers face a plethora of investment options together with complex regulatory instruments as well as growing uncertainty regarding, e.g. techno-economic and political developments. Optimization models using linear programming methods are one option to help shed light on possible technology combinations and the economic consequences for end consumers. Yet the existing literature indicates a clear lack of models capable of accounting for high technical, regulatory and economic detail while optimizing investments in multiple future years. Therefore, within this paper, the mixed-integer linear programming model COMODO (Consumer Management of Decentralized Options) is developed to determine the cost-minimal energy provision for end consumers. The model uses its extensive technology catalogue to perform an investment and dispatch optimization for multiple years, minimizing total costs over a long-term time horizon while accounting for developments in techno-economic data, regulatory frameworks and energy market conditions. Furthermore, piecewise-linear functions are created to represent costs and subsidies for different system sizes and for future years. Lastly, this work also presents a novel method of analysing the marginal costs of electricity and heat provision, revealing a strong correlation between the implicit marginal costs of energy provision and the assumptions on retail energy prices. In order to demonstrate the capabilities of the model developed, an exemplary application is presented to investigate the energy provision of two single-family homes in Germany for the years 2025 to 2045. Three scenarios are designed that build upon each other regarding the amount of information available to consumers and their decentralized energy technologies. Fully informed households choose to electrify their heat provision, i.e. installing a heat pump combined with thermal storage, PV and an electric heater. The flexibility achieved impacts the marginal costs observed, which can be lowered below energy retail prices. • MILP model COMODO optimizes investment in and dispatch of DER over multiple years. • Learning rates are used to create piecewise-linear cost functions for future years. • Novel method presented to analyse marginal costs of electricity and heat provision. • Self-consumption of PV electricity reduces marginal costs of energy provision.
Frings et al. (Sat,) studied this question.