Probabalistic load modelling of electrical demand of residential water heating

[摘要] ENGLISH ABSTRACT:Energy efficiency and the move to renewable energy resources are of vital importance ingrowing profitable and sustainable economies. In recent years, greater emphasis has been placedon institutions, companies and individuals to reduce their electrical energy demand throughenergy management. In an attempt to reduce the demand, the electrical power utility in SouthAfrica, Eskom, has introduced Demand Side Management programs and substantial increases inelectricity tariffs. In addition to these, tax incentives have been offered to help off-set the capitalcosts associated with the investments made in replacing old electrical equipment with newelectrically efficient equipment. Thus the need for accurate Measurement and Verification ofelectrical energy demand reduction, to substantiate fiscal claims, has become imperative. Themain purpose of Measurement and Verification is to investigate the actual monetary performanceof an energy savings project. Energy savings assessments, based on purely deterministicbaseline demand, do not adequately represent the statistical nature of the savings impacts ofmany practical load systems, as disclosed in a reporting period. This thesis presents thedevelopment of a generic probabilistic methodology to determine the demand profiles of preandpost-Energy Conservation Measures (ECMs) for practical load systems. The differencebetween the simulated demand of the pre- and post-ECMs for a particular set of variablesrepresent the electrical demand impact. The electrical demand of the pre- and post-ECMs isdefined in terms of Probability Density Functions, and derived using a multivariate kerneldensity estimation algorithm. The approach is tested using a simulation model of a waterheatinggeyser implemented in MATLAB. Three different ECMs are simulated using the geysermodel and demand density estimation. The results of the demand impacts of the ECMs arepresented and evaluated. With regards to possible future research this methodology could beapplied to the evaluation of the demand impacts of heat pump technologies and solar waterheaters.

[发布机构] Stellenbosch University