Optimization of an integrated combined cooling, heat, and power system with solar and wind contribution for buildings located in tropical areas

Abstract

Summary Combined cooling, heat, and power systems present higher energy efficiency and consequent financial benefits due to the reduced consumption of energy resources. In addition, there is the possibility of combining renewable and non‐renewable energy resources. This study develops an economic optimization to identify the optimal configuration and operation for an energy supply system. The optimal configuration is a subset of the available equipment, which includes solar collectors, fuel lines, electric grid, photovoltaic panels, wind turbines, gas boilers, engine‐generator sets, recovery boilers, and absorption and compression chillers. The optimization method consists of four steps: pre‐selection of the set of equipment to be evaluated, generation of all possible equipment combinations, optimization of the operation of each configuration based on a linear programming model, and exhaustive search to identify the lowest Net Present Value (objective function). A sensitivity analysis verified the optimal system in different β values, where β is a multiplier of the fuel (βfuel) and electricity (βele) tariffs. By systematically varying the β value, it is possible to identify the optimal system for different fuel and electricity tariffs. For example, for an optimization with βele = 1 and βfuel = 1.2, this assumes that the electricity tariff has not changed and the fuel tariff has increased by 20%. The optimal system (optimization with βfuel = 1 and βele = 1) meets the electricity and chilled water demands with electricity from the electric grid. A gas boiler meets the hot water demand. Due to the dependence on the electric grid, the optimizations with different β values result in systems with different configurations. For βele > 1.03 the solution is based on photovoltaic panels, when βele > 1.2 the solution is based on wind turbines and photovoltaic panels, and for βele > 1.33 the solution includes all equipment initially available. For βfuel < 0.48 the solution is constituted by an engine‐generator set, recovery boiler, absorption and compression chiller, and a gas boiler. The optimal system obtained in the optimization with βele = 1 and βfuel = 1 showed a high risk of investment in the resilience analysis, indicating that other systems can be installed, bringing satisfactory results in the long term.

Combined financial and environmental optimization of a trigeneration system

“…This occurs because the Brazilian electricity mix is comprised mostly of hydroelectricity, with low associated GHG emissions. The great variation in the equipment selected in the optimization process highlights the importance of including all possible energy conversion technologies, other works, such as Mohammadi et al [29], and also Melo et al [30] emphasizes this.…”