Optimising DERs in energy service networks: a case study

Poor energy performance of existing buildings worldwide has led to a crucial need to retrofit existing buildings to minimise energy consumption. Among the existing buildings, hotels use as much as 50% of their total expenses on energy and offer significant opportunities for energy efficiency improvement. Yet, comparatively the level of implementation of energy retrofits found to be low, which has attributed to, inter alia, the absence of a clearly defined process for ensuring the delivery of energy retrofit projects and lack of proactive guidance for project teams to ensure that they make the right decisions at the right time to achieve the desired outcomes. Since many energy retrofit projects in existing hotels are carried out with the involvement of an external contractor, or an Energy Service Company (ESCO), this study focuses on investigating the decision-making process in implementing energy retrofits when the project is outsourced to an external party. An in-depth case study is used to obtain insights into the critical decisions to be taken and key activities to be performed throughout the decision-making process. The findings are used to propose a step-by-step decision-making process comprising of three key phases: i.e., pre-retrofit, retrofit implementation and post-retrofit. It is hoped that the decision-making process developed in this study will serve as a roadmap for the effective adoption and implementation of energy retrofits in existing hotel buildings when an external contractor is involved.

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A case study in the design of service networks for reverse logistics

2008 International Conference on Service Systems and Service Management ◽

10.1109/icsssm.2008.4598559 ◽

2008 ◽

Cited By ~ 1

Author(s):

Rajesh Piplani ◽

Ashish Saraswat ◽

Hafidza Binte Othman

Keyword(s):

Reverse Logistics ◽

Service Networks

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A Case Study on Power Outage Impacts from Future Hurricane Sandy Scenarios

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0408.1 ◽

2018 ◽

Vol 57 (1) ◽

pp. 51-79 ◽

Cited By ~ 15

Author(s):

D. W. Wanik ◽

E. N. Anagnostou ◽

M. Astitha ◽

B. M. Hartman ◽

G. M. Lackmann ◽

...

Keyword(s):

Large Scale ◽

Prediction Models ◽

Hurricane Sandy ◽

Model Fit ◽

Power Outage ◽

Cyclone Intensity ◽

Electric Distribution Network ◽

Energy Service ◽

Ipcc Ar4

AbstractHurricane Sandy (2012, referred to as Current Sandy) was among the most devastating storms to impact Connecticut’s overhead electric distribution network, resulting in over 15 000 outage locations that affected more than 500 000 customers. In this paper, the severity of tree-caused outages in Connecticut is estimated under future-climate Hurricane Sandy simulations, each exhibiting strengthened winds and heavier rain accumulation over the study area from large-scale thermodynamic changes in the atmosphere and track changes in the year ~2100 (referred to as Future Sandy). Three machine-learning models used five weather simulations and the ensemble mean of Current and Future Sandy, along with land-use and overhead utility infrastructure data, to predict the severity and spatial distribution of outages across the Eversource Energy service territory in Connecticut. To assess the influence of increased precipitation from Future Sandy, two approaches were compared: an outage model fit with a full set of variables accounting for both wind and precipitation, and a reduced set with only wind. Future Sandy displayed an outage increase of 42%–64% when using the ensemble of WRF simulations fit with three different outage prediction models. This study is a proof of concept for the assessment of increased outage risk resulting from potential changes in tropical cyclone intensity associated with late-century thermodynamic changes driven by the IPCC AR4 A2 emissions scenario.

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