Measurement and verification of energy conservation measures using whole-building electricity data from four identical office towers

Newsham, Guy R.

doi:10.1016/j.apenergy.2019.113882

Cited by 13 publications

(5 citation statements)

References 3 publications

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“…Although not accurate for a broad span of buildings, the author concluded that this approach can be adopted in automated M&V 2.0. Furthermore, the model had similar performance between monthly and hourly data, allowing a reduced cost from hourly data [32].…”

Section: Mandv State Of the Artmentioning

confidence: 96%

Measurement and Verification of Zero Energy Settlements: Lessons Learned from Four Pilot Cases in Europe

et al. 2020

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Measurement and verification (M&V) has become necessary for ensuring intended design performance. Currently, M&V procedures and calculation methods exist for the assessment of Energy Conservation Measures (ECM) for existing buildings, with a focus on reliable baseline model creation and savings estimation, as well as for reducing the computation time, uncertainties, and M&V costs. There is limited application of rigorous M&V procedures in the design, delivery and operation of low/zero energy dwellings and settlements. In the present paper, M&V for four pilot net-zero energy settlements has been designed and implemented. The M&V has been planned, incorporating guidance from existing protocols, linked to the project development phases, and populated with lessons learned through implementation. The resulting framework demonstrates that M&V is not strictly linked to the operational phase of a project but is rather an integral part of the project management and development. Under this scope, M&V is an integrated, iterative process that is accompanied by quality control in every step. Quality control is a significant component of the M&V, and the proposed quality control procedures can support the preparation and implementation of automated M&V. The proposed framework can be useful to project managers for integrating M&V into the project management and development process and explicitly aligning it with the rest of the design and construction procedures.

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Section: Mandv State Of the Artmentioning

confidence: 96%

Measurement and Verification of Zero Energy Settlements: Lessons Learned from Four Pilot Cases in Europe

et al. 2020

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“…Nowadays, automated calibration has gained interest compared to conventional methods due to its faster and more efficient processes such as Bayesian calibration [180], pattern-based calibration [181], and multistage calibration [182]. Furthermore, the revolution of M&V 2.0 has offered new technologies that might lower the cost of M&V, generate quicker findings with greater transparency and confidence, and thus raise the acceptability of the savings projections [183]. More advanced technologies of M&V 2.0 tools that have been commercially available in the market have been discussed in [184].…”

Section: B Measurement and Verifications (Mandv)mentioning

confidence: 99%

A Review on the Applications of PSO-Based Algorithm in Demand Side Management: Challenges and Opportunities

et al. 2023

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The increase in energy consumption, environmental pollution issues, and low-carbon agenda has grown the research area of demand side management (DSM). DSM programs provide feasible solutions and significantly enhance the efficiency and sustainability of electrical distribution systems. This paper classifies and discusses the broad definition of DSM based on the comprehensive literature study considering demand response and energy efficiency. The implementation of Artificial Intelligence algorithms in DSM applications has been employed in many studies to help researchers make optimal decisions and achieve predictions by analyzing the massive amount of historical data. Owing to its simplicity and consistent performance in fast convergence time, Particle Swarm Optimization (PSO) is widely used as a part of the swarm AI algorithm and has become a prominent technique in the optimization process to exploit the full benefit of the demand-side program. The variants of PSO have been developed to overcome the limitations of the original PSO and solve the high complexity and uncertainty in the DSM optimization process. The proposed PSO-based algorithm can optimize consumers' consumption curves, reducing the peak demand and hence minimizing the electricity cost when integrated with the DR programs or EE measures. The research works of the PSO algorithm in DSM have seen an increasing trend in the past decade. Therefore, this paper reviewed the application of the PSO-based algorithm in DSM fields with some constraints and discussed the challenges from the previous work. The potential for new opportunities is identified so that PSO methods can be developed for future research.INDEX TERMS Demand side management (DSM), demand response (DR), energy efficiency (EE), metaheuristic algorithms, particle swarm optimization (PSO), swarm intelligence.

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“…It can be used to derive verifiable future cash flows from savings for reporting, EE financing, performancebased energy services company (ESCo) contracts, or other purposes (Bleyl et al, 2014). Reliable M&V of EEM savings is critical for the financial settlement of utility incentives and energy performance contracts (Newsham, 2019). Evaluating the impacts of EEMs also supports the ongoing success and promotion of EE (Kissock & Eger, 2008).…”

Section: Introductionmentioning

confidence: 99%

Simplified measurement and verification combined with quality assurance instruments: a more practical and accessible method for M&V of energy savings

Bleyl,

Robertson,

Mitchell

et al. 2024

Energy Efficiency

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Energy efficiency (EE) is our “first fuel” and an essential resource in reaching climate goals, reducing dependence on fossil fuels, increasing security of supply, and many other “Multiple Benefits.” However, by their nature, savings are intangible. Demand-side EE measures are typically decentralized, heterogeneous, and small-scale opportunities. The difficulties in measurement and verification (M&V) of “Negawatts” are an important and often overlooked barrier to their greater application. M&V is a prerequisite to assess the performance of any energy, water, or CO2-saving measure, and to quantify the savings into physical and monetary units for reporting, re-financing, GHG accounting, or other purposes. However, in practice, M&V is often perceived (particularly by clients) as cumbersome, incomprehensible, and costly. In the broader context, energy cost savings alone are often not a sufficiently strong project driver because they lack strategic relevance for decision makers. As “Multiple Benefits” of EE become better understood, the value of quantifying savings to a high degree of accuracy may be declining, creating opportunities for more flexible M&V standards. As a new methodology, this conceptual paper proposes to combine simplified M&V (sM&V) for individual EE measures with quality assurance instruments (QAIs) to verify functionality. This “sM&V + QAI” approach is less cumbersome, less costly, and easier to comprehend than standard M&V approaches, particularly by clients, financiers, and other non-M&V experts. It has been reviewed by international experts and successfully tested and evaluated in the field. Multiple case studies are reported to verify its practical feasibility.

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Measurement and verification of energy conservation measures using whole-building electricity data from four identical office towers

Cited by 13 publications

References 3 publications

Measurement and Verification of Zero Energy Settlements: Lessons Learned from Four Pilot Cases in Europe

Measurement and Verification of Zero Energy Settlements: Lessons Learned from Four Pilot Cases in Europe

A Review on the Applications of PSO-Based Algorithm in Demand Side Management: Challenges and Opportunities

Simplified measurement and verification combined with quality assurance instruments: a more practical and accessible method for M&V of energy savings

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