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Using an ANFIS based short term load forecasting model for the optimization of micro-CHP operating strategies in domestic households

Schönfelder, Martin; Jochem, Patrick; Fichtner, Wolf ORCID iD icon


This paper presents a comprehensive concept for the development of an auto-adaptive optimization model seeking to determine optimal operating strategies of micro combined heat and power (CHP) units in domestic households with special respect to the energy-economic framework conditions in Germany. The methods proposed to be applied are an adaptive network based fuzzy inference sys-tem (ANFIS [1]) coupled with mixed-integer-linear programming (MIP).
Nowadays, most of micro-CHP units are driven heat led, due to their limited tech-nical ability of following the electric load profile (especially in case of fuel cell micro-CHP). However, the consumption-rate of locally self-generated electricity is crucial for the economics of micro-CHP systems. Therefore, the aim of this paper is to provide an economically optimized operating strategy which requires information about the household’s future load situation and therefore an appropriate individual short term load forecast (STLF). Furthermore, the concept described considers battery and hybrid electric vehicles as additional consumers of electric energy which enforces the necessity of optimized operation. ... mehr

Postprint §
DOI: 10.5445/IR/1000077459
Veröffentlicht am 10.09.2018
Cover der Publikation
Zugehörige Institution(en) am KIT Karlsruhe Service Research Institute (KSRI)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2012
Sprache Englisch
Identifikator urn:nbn:de:swb:90-774596
KITopen-ID: 1000077459
Erschienen in Proceedings of the 2nd Stochastic Modeling Techniques and Data Analysis International Conference, SMTDA 2012, Crete, Greece, 5th - 8th June 2012
Seiten 675-684
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