Development of a Global Energy Management System for non-energy intensive multi-site industrial organisations: A methodology
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Date
2017-01-25Author
Finnerty, Noel
Sterling, Raymond
Coakley, Daniel
Contreras, Sergio
Coffey, Ronan
Keane, Marcus M.
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Finnerty, Noel, Sterling, Raymond, Coakley, Daniel, Contreras, Sergio, Coffey, Ronan, & Keane, Marcus M. Development of a Global Energy Management System for non-energy intensive multi-site industrial organisations: A methodology. Energy. doi: http://dx.doi.org/10.1016/j.energy.2016.10.049
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Abstract
For multi-site organisations, informed decision making on capital investment aimed at improving energy performance and cutting carbon emissions, across a global site base, is a complex problem. This work presents the systematic development and implementation of a novel energy management methodology for multi-site organisations to reach optimal efficiency across their network. The methodology, a Global Energy Management System, is based on the following strategic pillars: (1) Site Characterisation; (2) Performance Evaluation; (3) Energy Strategy; and (4) Shared learnings and dissemination. These pillars are underpinned by essential foundations: (a) Global energy team and communication forum; (b) Knowledge base at site and global level; and (c) Corporate Energy Policy. The methodology incorporates both quantitative performance evaluation using novel key performance indicators and benchmarking, as well as qualitative characterisation using energy management maturity models. The methodology culminates with a systematic, repeatable and scalable decision support framework, underpinned by a multi-criteria decision-making methodology. A detailed case study is presented for a multi-national corporation in the life sciences industry, which resulted in increased awareness of energy and carbon emissions, as well as related impacts on business continuity, corporate sustainability and social responsibility. This triggered increased investment in energy efficiency measures, thus promoting the conditions for continuous improvement towards optimal network performance.
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