With the increasing application of distributed energy resources and novel information technologies in the electricity infrastructure, innovative possibilities to incorporate the demand side more actively in power system operation are enabled. A promising, controllable, residential distributed generation technology is a microcombined heat and power system (micro-CHP). Micro-CHP is an energy-efficient technology that simultaneously provides heat and electricity to households. In this paper, we investigate to what extent domestic energy costs could be reduced with intelligent, price-based control concepts (demand response). Hereby, first the performance of a standard, so-called heat-led micro-CHP system is analyzed. Then, a model-predictive control (MPC) strategy aimed at demand response is proposed for more intelligent control of micro-CHP systems. Simulation studies illustrate the added value of the proposed intelligent control approach over the standard approach in terms of reduced variable energy costs. Demand response with micro-CHP lowers variable costs for households by about 1%-14%. The cost reductions are highest with the most strongly fluctuating real-time pricing scheme.

Micro cogeneration technology (micro-CHP) is expected to be an important novel residential heating technology for the future in certain countries around the world. The interesting aspect of micro-CHP is that it is a controllable distributed generation technology. This paper provides novel conceptual insight into how micro-CHP systems can be controlled aggregatedly in virtual power plants (VPPs). Cost benefits for VPPs can be achieved through 'economies of intelligence' with the help of intelligent control schemes.

Household level energy conversion, storage and exchange technologies are assumed to pervade the energy infrastructure in the future. These novel technologies will influence the total infrastructure in a bottom-up way; both technically and socially. Not only the physical networks, but also the social actor network consisting of households, network managers, energy suppliers and producers is influenced. This paper describes and conceptualizes a complex systems approach towards energy infrastructures based on a large penetration of decentralized technologies. Households thereby contain an energy hub; an interface between a number of energy sources and loads. Households can interact with each other and with other actors via their hubs. Our approach paves the way for modelling the socio-technical complexity via agent-based modelling (ABM) and for subsequent exploratory simulations.