Whole building energy simulation (BES) models play a significant role in the design and optimisation of buildings. Simulation models may be used to compare the cost-effectiveness of energy-conservation measures (ECMs) in the design stage as well as assessing various performance optimisation measures during the operational stage. However, due to the complexity of the built environment and prevalence of large numbers of independent interacting variables, it is difficult to achieve an accurate representation of real-world building operation. Therefore, by reconciling model outputs with measured data, we can achieve more accurate and reliable results. This reconciliation of model outputs with measured data is known as calibration. This paper presents a detailed review of current approaches to model development and calibration, highlighting the importance of uncertainty in the calibration process. This is accompanied by a detailed assessment of the various analytical and mathematical/statistical tools employed by practitioners to date, as well as a discussion on both the problems and the merits of the presented approaches.
For multi-site organisations, informed decision making on capital investment aimed closing the energy efficiency gap, cutting carbon emissions and improving network performance across a global site base is a complex problem. This paper presents the systematic development and implementation of a novel methodology to reach optimal energy efficiency in multi-site organisations across their network whilst reducing carbon footprint. The methodology, a Global Energy Management System, is based on the following strategic pillars: (1) Site Characterization (2) Performance Evaluation via key performance indicators and energy benchmarking (3) Energy Strategy (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 culminates with a simplified, understandable, systematic, repeatable and scalable decision support framework addressing the complexities unique to decision-making on capital investments in global multi-site organisation. A case study is presented for a multi-national corporation in the life sciences industry. The proposed approach increased the visibility of energy and related carbon emissions issues and triggered unprecedented levels of funding and support for energy efficiency measures, leading to entering the energy efficiency continuous improvement journey towards optimal network performance.
Literature reviewed suggests energy maturity models are in their infancy in the energy management sector, with little practical guidance for their implementation in multi-site organisations. In addressing this gap, this paper presents the development and implementation of an Energy Management Maturity Model for multi-site industrial organisations with a global presence, considered as a fundamental step towards continuous improvement and optimal energy efficiency. The developed maturity model provides a global view of the overall network readiness for engaging in energy efficiency by adapting and enhancing existing 'site focused' maturity models to cater for multi-site industrial an organisation. The model enables two-way communication between global and local energy management teams; not only are the individual sites benchmark but the global energy management team gets feedback and a gap analysis on their performance from the network of sites perspective. The evaluation framework created around the maturity model supports automated prioritization of elements with larger deviations. In parallel it provides the global energy management team with direction on where the organisation needs to focus central efforts to support the sites. The maturity model enables the evaluation of key not technical aspects of energy management required for continuous improvement on a multi-site and global scale.
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