A Multicriteria Approach for the Integration of Renewable Energy Technologies and Thermal Energy Storage to Support Building Trigeneration Systems
Abstract
Trigeneration systems benefit from process integration to achieve primary energy savings, reduction of pollutant emissions, and reduction of unit costs relative to conventional separate production. Achieving such benefits requires an appropriate design procedure. The issue is that finding the best configuration that minimizes total annual cost is not enough anymore, as the environmental concern has become an ever-present theme in the design and synthesis of energy systems. The minimization of costs is often contradictory to the minimization of environmental impact. Multiobjective optimization tackles the issue of conflicting objectives by providing a set of trade-off solutions, or Pareto solutions, that can be examined by the decision maker, so that the best configuration can be selected for a given scenario. This paper proposes a mixed integer linear programming model (MILP) to determine the optimal configuration and hourly operation of trigeneration systems considering the effects of thermal energy storage (TES) and hourly variations of solar radiation, energy supply prices, energy demands, and CO2 emissions. The objective functions to be minimized are the total annual costs and the total annual CO2 emissions. Initially, the objective functions were evaluated separately. Then, the Pareto curve was obtained for the minimization of total annual cost subject to CO2 emissions restrictions. The trade-off solutions were analyzed and the preferred solutions were selected, achieving results close to the optimal solutions with reasonable sacrifices for both objectives.