(301e) Operational Planning in Residential Microcogeneration Energy Production Networks

Nowadays, it is evident that the classical Energy Supply Chain (ESC) is rapidly changing to an energy-efficient and low-carbon energy market economy by moving towards more decentralized energy production. There is clearly a distributed energy generation option which could play a vital role within the development of sustainable future energy systems, the energy microgeneration.  Specifically, the most promising microgeneration technology involves the cogeneration (i.e., combined generation) of electrical energy and heat in small-scale energy generation units that can be directly embedded in the buildings wherein the heat and electricity are to be used; also known as microcogeneration (Pehnt et al., 2006).

Indeed, the domestic sector constitutes a key consumer of both electricity and heat, and could benefit from consolidation to meet these demands via micro Combined Heat and Power (microCHP) generators (Hawkes et al., 2006). Today, the principal microCHP technologies are based on Stirling engines or fuel cells. Stirling engines are already available in the market in competitive prices, while fuel cells constitute a still- experimental technology that features high initial capital costs.  Also, there are financial incentives (such as the Feed-In-Tariff support scheme introduced by the UK Government) initiated by many countries in an attempt to encourage the uptake of small-scale microgeneration technologies.

ESCs based on microgeneration have been recently emerged, and they are expected tp grow rapidly. In this new energy environment, the electrical grid (macrogrid) is seen not as a primary power supplier but instead as a back-up of the microgeneration ESC network network. A residential energy microgrid (i.e., a microgeneration ESC) could be formed by connecting several domestic microCHP systems. Importantly, by constructing such a microgrid while integrating various energy alternatives in a residential scale, residents can trade and consume the power flexibly (and more efficiently) with each other. Noticeably, the planning and the overall management of microCHP-based ESC networks result into highly sophisticated decision making problems.

In this work, a mathematical programming framework has been developed for the operational planning of such ESC networks. The minimization of total costs (including microgeneration system's startup and operating costs as well as electricity production revenue, sales, and purchases), under full heat demand satisfaction, constitutes the objective function. Additionally, an alternative microgrid structure that allows the heat interchange within subgroups of the overall microgrid is proposed, and the initial mathematical programming formulation is extended to deal with this new aspect. Afterwards, a number of real-world size case studies, using real data provided from the UK Energy Research Centre, have been solved by the proposed approaches so as to shed light on the potential benefits of the residential microgeneration ESC networks suggested in this study. Finally, some concluding remarks are drawn and potential future research directions are identified.

Acknowledgments

The authors acknowledge the financial support from the Engineering and Physical Sciences Research Council (EPSRC) under the research project EP/G059071/1. Financial support from the European Union's Seventh Programme managed by REA-Research Executive Agency http://ec/europa.eu/rea (FP7/2007-2013) under grant agreement PIRSES-GA-2011-294987 (ESE project) is also gratefully acknowledged.

References

Hawkes, A. D., Aguiar, P., Hernandez-Aramburo, C. A., Leach, M. A., Brandon, N. P., Green, T. C., Adjiman, C. S., 2006. Techno-economic modelling of a solid oxide fuel cell stack for micro combined heat and power. Journal of Power Sources 156 (2), 321-333.

Pehnt, M., Cames, M., Fischer, C., Praetorius, B., Schneider, L., Schumacher, K., Voβ, J., 2006. Micro Cogeneration: Towards Decentralized Energy Systems.Springer, Berlin, Heidelberg, Germany.

UK Department of Energy & Climate Change, June 2011. Microgeneration strategy.

UK Energy Research Centre Energy Data Centre (UKERC-EDC), 2008. Milton Keynes Energy Park Dwellings 1990 dataset.