ENERGY LOAD PREDICTIONS FOR BUILDINGS BASED ON A TOTAL DEMAND PERSPECTIVE

The outline of this work was to develop models for single family build ings, based on a total energy demand perspective, i.e., building-clima te-inhabitants. The building-climate part was included by using a comm ercial dynamic energy simulation software. Whereas the influence from the inhabitants was implemented in terms of a predicted load for domes tic equipment and hot water preparation, based on a reference building . The estimations were processed with neural network techniques. All m odels were based on access to measured diurnal data from a limited tim e period, ranging from 10 to 35 days. The annual energy predictions we re found to be improved, compared to models based on only a building-c limate perspective, when the domestic load was included. For periods w ith a small heating demand, i.e., May-September, the average accuracy was 7% and 4% for the heating and total energy load, respectively, whe reas for the rest of the year the accuracy was on average 3% for both heating and total energy load. (C) 1998 Elsevier Science S.A. All righ ts reserved.