Profit optimization of sustainable low-to-medium temperature waste heat recovering management

Abstract

Purpose Responding to natural resource depletion and carbon dioxide (CO2) emission problems, and also the stricter government’s energy regulations, the purpose of this paper is to develop a sustainable waste heat recovery optimal-profit-oriented management model especially targeting on the easily forgotten low- and medium-temperature waste heat in the industry. In the paper, a system is constructed to facilitate converting the low- and medium-grade waste heat in factories into electricity, and yields optimal profit. Design/methodology/approach This paper integrates an efficient Organic Rankine Cycle (ORC) system from both sustainable energy reservation and cost effectiveness approaches with an optimization model that adopts particle swarm optimization (PSO) algorithm to determine proper installation locations and feasible generator sets. The system is constructed to facilitate converting the low- and medium-grade waste heat in factories into electricity, and yields optimal profit. The model considers the environmental factors: temperature, heat amount, equipment configuration of the number of ORC sets, and detailed investment cost constraints. Findings The results show that annual investment return rate, annual increase in electricity, power generation efficiency, and annual CO2 emission reduction are all highly improved, and investment recovery period is shortened. Also, the larger scale of the waste heat emission, the better the performance is achieved. Finally, the study also completes a sensitivity test under dynamic conditions of electricity price, generator sales price and factory budget constraints, and the results are consistently robust. More valuably, this paper demonstrates applications on two different manufacturing industries with various waste heat emission scales to prove the accountability. Originality/value The main contributions are in three aspects. First, it proves that applying PSO to a nonlinear mathematical model can help determine the optimal number and style configuration of generators for waste heat sources. Second, different from the prior research works focusing on power generation, this paper also deliberates the cost factors, cost of generators, costs of numerous peripheral components and future maintenance costs to ensure the factories not conflict with the financial limitations. Third, it is not only successfully applied in two industries with different scales, but also robust with various economic tests, electricity price change, generator sales price change, and investment budget adjustments.

Evaluating the sustainability of big data centers using the analytic network process and fuzzy TOPSIS

“…Furthermore, because most of the electrical supply of data center servers is dissipated as thermal energy, the management of the energy conversion process has become a new and crucial aspect for achieving data center sustainability (Jones and Fleischer 2014 ). Ideally, waste heat can be used to offset heating costs (Haywood et al 2012 ), and heating facilities in cold regions can partly meet energy demands through the intermittent generation of renewable energy (Woodruff et al 2014 ; Lin 2018 ; Kwon 2020 ). The main challenge involved in consolidating data center resources for achieving energy efficiency is that maximizing the quality of services conflicts with minimizing the energy consumption of the data center.…”

Responsible consumption and production (RCP) in corporate decision-making models using soft computation

“…As we have seen in some of the previous papers in this SI, technologies, core to ecological modernization theory, are major enablers to RCP in business. Within this context, Lin et al (2017), the final paper in this SI, evaluated an efficient Organic Rankine Cycle system from both sustainable energy reservation and cost effectiveness approaches using particle swarm optimization algorithm. In their evaluation, they sought to determine proper installation locations and feasible generator sets for this technology.…”