TY - JOUR
T1 - Industrial cluster energy systems integration and management tool
AU - Ngwaka, Ugochukwu
AU - Khalid, Yousaf
AU - Ling-Chin, Janie
AU - Counsell, John
AU - Siddiqui, Faisal
AU - Pinedo-Cuenca, Ruben
AU - Dawood, Huda
AU - Smallbone, Andrew
AU - Dawood, Nashwan
AU - Roskilly, Anthony Paul
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Critical for achieving the United Kingdom's net-zero targets, decarbonising industrial clusters would require robust tools to assess the feasibility of decarbonisation technologies and investment solutions. This paper presents an integrated energy system planning tool for decarbonising industrial clusters. The adoption of the transfer functions method enables the development of individual component models for technologies, networks, and loads, facilitating the control and simulation of complex dynamics in multi-energy system operation, as demonstrated in a case study investigating heat and power demands of a dynamic hybrid cluster, with evaluation of decarbonisation implications including heat electrification, renewables, and fuel switching in both grid-connected and island modes to establish potential pathways for decarbonisation. With the implementation of these decarbonisation measures in the case study cluster, primary energy demand, costs, emissions, and energy losses were reduced by 42%, 71%, 53%, and 72% in grid mode and by 40%, 70%, 53%, and 63% in island mode, and higher losses in island mode is due to excess heat production by electric boilers intended to consume all available power. While outcomes might differ among various clusters due to their specific features, the study cluster, characterised by substantial heat demand compared to electricity and significant electricity exports, achieves significant emission reduction via heat electrification compared to other individual decarbonisation technology. Moreover, this tool will be instrumental in helping industrial clusters formulate comprehensive decarbonisation roadmaps based on informed decisions.
AB - Critical for achieving the United Kingdom's net-zero targets, decarbonising industrial clusters would require robust tools to assess the feasibility of decarbonisation technologies and investment solutions. This paper presents an integrated energy system planning tool for decarbonising industrial clusters. The adoption of the transfer functions method enables the development of individual component models for technologies, networks, and loads, facilitating the control and simulation of complex dynamics in multi-energy system operation, as demonstrated in a case study investigating heat and power demands of a dynamic hybrid cluster, with evaluation of decarbonisation implications including heat electrification, renewables, and fuel switching in both grid-connected and island modes to establish potential pathways for decarbonisation. With the implementation of these decarbonisation measures in the case study cluster, primary energy demand, costs, emissions, and energy losses were reduced by 42%, 71%, 53%, and 72% in grid mode and by 40%, 70%, 53%, and 63% in island mode, and higher losses in island mode is due to excess heat production by electric boilers intended to consume all available power. While outcomes might differ among various clusters due to their specific features, the study cluster, characterised by substantial heat demand compared to electricity and significant electricity exports, achieves significant emission reduction via heat electrification compared to other individual decarbonisation technology. Moreover, this tool will be instrumental in helping industrial clusters formulate comprehensive decarbonisation roadmaps based on informed decisions.
UR - http://www.scopus.com/inward/record.url?scp=85173523859&partnerID=8YFLogxK
U2 - 10.1016/j.enconman.2023.117731
DO - 10.1016/j.enconman.2023.117731
M3 - Article
SN - 0196-8904
VL - 297
JO - Energy Conversion & Management
JF - Energy Conversion & Management
M1 - 117731
ER -