Semi‐empirical development of a novel and versatile multiobjective optimization tool for co/trigeneration energy system design

Abstract

Summary This article describes a novel and implemented optimization routine for the analysis of combined cooling, heat, and power generation. The optimization model is briefly described both in terms of logic and operation and in terms of mathematical formalization. The model is able to optimize energy systems with different technologies used for the cogeneration unit, namely, SOFC and PEM fuel cells, internal combustion engines (ICEs), and micro‐gas turbines (MGTs). The validation is performed both in terms of energy efficiency curves and in terms of unit costs, for all components within the energy system, including energy storage systems, heat pumps, and auxiliary boilers. The main key performance indicators included in the technical analysis of the CCHP units are the nominal electric and overall efficiency as a function of installed size and during a partial load operation, as well as the power‐to‐heat factor in dependence upon the nominal capacity/power. Two main storage technologies have been included, namely lithium‐ion batteries (Li‐ion BES) and lead‐acid batteries (LA BES). The heat pump portfolio allows the choice between compression gas heat pumps (CGHPs) and absorption heat pumps (ABHPs), with their COP and EER described as a function of the external temperature and of a partial load operation. The validation of the modeled curves is performed in comparison with data of existing commercial units, presenting a correlation factor over 95% for most of the technologies. Highlights Presentation of a multiphysical design tool for CCHP systems; Economic, technical, and environmental analysis and optimization; PEMFC and SOFC are included in the tool technology portfolio; The model is based on validated and semi‐empirical correlations; Evaluation of different energy storage systems and heat pump technologies. The present article describes the validation of an innovative multiobjective model aiming to optimize both the operating strategy of the plant and the sizing of the main equipment in a correlated way. The article focuses on the validation of the proposed model and, as a further novelty, includes a broad technological portfolio in terms of cogeneration units and describes the semi‐empirical validation of the model by comparing the cost and performance curves modeled with existing market elements or literature data.