A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage

Abstract

Cogeneration systems are widely acknowledged as a viable solution to reduce energy consumption and costs, and CO2 emissions. Nonetheless, their performance is highly dependent on their capacity and operational strategy, and optimization methods are required to fully exploit their potential. Among the available technical possibilities to maximize their performance, the integration of thermal energy storage is recognized as one of the most effective solutions. The introduction of a storage device further complicates the identification of the optimal equipment capacity and operation. This work presents a cutting-edge methodology for the optimal design and operation of cogeneration systems with thermal energy storage. A two-level algorithm is proposed to reap the benefits of the mixed integer linear programming formulation for the optimal operation problem, while overcoming its main drawbacks by means of a genetic algorithm at the design level. Part-load effects on nominal efficiency, variation of the unitary cost of the components in relation to their size, and the effect of the storage volume on its thermal losses are considered. Moreover, a novel formulation of the optimization problem is proposed to better characterize the heat losses and operation of the thermal energy storage. A rolling-horizon technique is implemented to reduce the computational time required for the optimization, without affecting the quality of the results. Furthermore, the proposed methodology is adopted to design a cogeneration system for a secondary school in San Francisco, California, which is optimized in terms of the equivalent annual cost. The results show that the optimally sized cogeneration unit directly meets around 70% of both the electric and thermal demands, while the thermal energy storage additionally covers 16% of the heat demands.

Multi-Energy School System for Seasonal Use in the Mediterranean Area

“…However, their performance depends heavily on their sizing and operational strategy, especially if coupled with renewable energy plants [14]. Therefore, optimization methods are needed to exploit their full potential [55] because the over sizing or under sizing of the CHP plant could completely compromise the achievable energy saving potential [56].…”

System Design and Optimisation Study on a Novel CCHP System Integrated with a Hybrid Energy Storage System and an ORC

“…In a similar system, a dynamic programming operation strategy was developed to distribute the generated energy which brings 19% efficiency improvement [12]. For solving this problem, integration of energy storage units is proposed to improve part load efficiency and operation flexibility [13]. A distributed power generation system (DPGS) with an electric energy storage (EES) system has a similar idea with the current study.…”

Optimum Choice of Energy System Configuration and Storages for a Proper Match between Energy Conversion and Demands

“…Urbanucci et al [3] present a methodology for the optimal design and operation of cogeneration systems with thermal energy storage. A two-level algorithm is proposed, which utilizes a genetic algorithm at the design level (upper level) to identify the components that are to be included in the energy system and their capacities, and combines it with a mixed-integer linear programming (MILP) formulation for the search of the optimal operation (lower level).…”