ENERGY, COST, AND CARBON-DIOXIDE OPTIMIZATION OF DISAGGREGATED, REGIONAL ENERGY-SUPPLY SYSTEMS

Energy conservation and greenhouse warming mitigation can be supported by cogeneration of heat and power and by heat recovery via heat exchangers and via the upgrading of environmental and waste heat by heat pumps. Fuel switching, the use of solar thermal energy, and the removal and disposal of CO, may complement these measures. In order to determine the optimum combination of these options with conventional energy-conversion technologies for regional energy-supply systems with disaggregated, fluctuating energy-exergy demand profiles, we have developed stochastic and quasi-dynamic vector-optimization models which can be used as computerized planning tools. The application of the stochastic optimization model ECCO to a south German model city shows that the primary energy input into the system and the CO2 emissions may be reduced by about 25% and 30%, respectively. These figures change as the average ambient temperature deviates from 10 degrees C. The quasi-dynamic optimization model ECCO-Solar, applied to an army facility which served as a pilot project with well documented energy and weather data, yields savings of primary energy and CO, emissions which vary between 20% and 50%, depending upon the scenario. Both models show that the optimum combination of technologies depends very sensitively on the details of the demand situation. Computing the costs and reducing them interactively, one finds that nearly all of the considered energy conservation and emission reduction strategies will become economical only at energy prices which are considerably higher than the present ones.