Optimization of an Organic Rankine Cycle–Vapor Compression Cycle System for Electricity and Cooling Production from Low-Grade Waste Heat

Łukasz Witanowski ()
Additional contact information
Łukasz Witanowski: Turbine Department, Institute of Fluid-Flow Machinery, Polish Academy of Sciences, 80-231 Gdańsk, Poland

Energies, 2024, vol. 17, issue 22, 1-19

Abstract: In light of the intensifying global climate crisis and the increasing demand for efficient electricity and cooling systems, the exploration of advanced power generation technologies has become crucial. This paper presents a comprehensive analysis of Organic Rankine Cycle–Vapor Compression Cycle (ORC-VCC) systems utilizing low-grade waste heat for the dual purpose of electricity and cooling production. The study focuses on systems that harness waste heat below 90 °C with thermal inputs up to 500 kW. An in-house Python code was developed to calculate cycle parameters and perform multi-objective optimization targeting the maximization of both ORC-VCC efficiency and power output. The optimization was conducted for 10 different cases by evaluating five working fluids across two different ambient temperatures. The analysis reveals that the optimized system achieved an impressive overall cycle efficiency exceeding 90%, demonstrating the significant potential of ORC-VCC technology in waste heat recovery applications. The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective optimization approach was found to be particularly effective at navigating the multi-dimensional solution space and identifying the global optimum. This study provides valuable insights into system performance across a range of operating conditions and design parameters. Sensitivity analyses highlight key factors influencing cycle efficiency and power output. These findings have important implications for the development and deployment of ORC-VCC systems as a sustainable and efficient solution to meet growing energy needs while reducing greenhouse gas emissions.

Keywords: Organic Rankine Cycle; Vapor Compression Cycle; waste heat; multi-objective optimization; Non-Dominated Sorting Genetic Algorithm II (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/22/5566/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/22/5566/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:22:p:5566-:d:1515980

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().