Multi-objective Optimization of Integrated Community Energy and Harvesting (ICE-Harvest) System Based on Marginal Emission Factor

In this study, a detailed optimization framework for optimal design and operation of a smart energy system so-called integrated community energy and harvesting (ICE-Harvest) system is devised. This system consists of a low-temperature single-pipeline network (LT-SPN), generation and storage units, and a set of buildings. Its key features are the capability to perform demand response without affecting the comfort of the occupants by manipulating the network temperature rather than the indoor temperatures. In addition, heating and cooling energy can be mutually beneficial, so that the energy that would otherwise be wasted is harvested. The resultant nonlinear optimization model is linearized, and a multi-criteria approach is utilized considering the total annual cost (TAC) and GHG emissions. The marginal emission factor (MEF) is calculated and used to evaluate the GHG emissions and showcase how dispatchable loads can reduce them. Finally, a Pareto front curve is obtained, the compromise solution is chosen, and its operation is discussed.