6,174 research outputs found

    Screening of energy efficient technologies for industrial buildings' retrofit

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    This chapter discusses screening of energy efficient technologies for industrial buildings' retrofit

    Impact analysis of electric vehicle demand on demand profile, electricity charges and system emissions of Rochester Institute of Technology

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    In view of growing concerns of greenhouse gas emissions, electrification in the transportation fleet is expected to increase globally. To accommodate the incoming increase in energy demand from vehicle charging, the existing electrical network should be managed in a way that the load is operated with no electrical instability. Peak demand occurrences which could be measured daily, annually, weekly, monthly or annually should be avoided in order to maintain the health of the electrical network and reduce demand charges billed to the end energy user. Moreover, depending on the emissions factor of the fuel mix used in a region for energy generation the amount of emissions is influenced by the overall network’s demand through different times of the day. This thesis addresses the effects of increasing levels of electric vehicle demand on Rochester Institute of Technology’s circuit demand profile, electricity charges and system emissions. The thesis will inform the reader about the potential changes in peak demand behavior, peak months, peak times and peak days as electric vehicle usage increases across campus. In addition, the electric vehicle penetration levels and times at which changes in overall peak demand behavior, electricity charge trend and max emissions through the day occur, will be presented in this thesis paper. The results obtained through the impact analyses suggested that overall changes in circuit behavior start to become noticeable when electric vehicle users reach 50 times the current number of users on campus. In addition, impacts of electric vehicle demand on the overall circuit’s peak occurrences are observed to shift from afternoon to morning hours as fleet electrification increases on campus. Potential electric vehicle charging times to manage the increasing demand on campus and maintaining a leveled overall demand profile, reducing electricity charges and system emissions will be suggested in this paper

    Variation of household electricity consumption and potential impact of outdoor PM2.5 concentration: a comparison between Singapore and Shanghai

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    The auto-regressive distributed lag (ARDL) bound testing approach was used to study the relationships between the monthly household electricity consumption and outdoor PM2.5 concentration with the consideration of ambient temperature and the number of rainy days for Singapore and Shanghai. It is shown that there are significant long-run relationships between the household electricity consumption and the regressors for both Singapore and Shanghai. For Singapore, a 20% increase in the PM2.5 concentration of a single month is in the long-run significantly related to a 0.8% increase in the household electricity consumption. This corresponds to an electricity overconsumption of 5.0 GWh, a total of 0.7–1.0 million USD in electricity cost, and 2.1 kilotons of CO2 emission associated with electricity generation. For Shanghai, a 20% decrease in the PM2.5 concentration of a single month is in the long-run significantly related to a 2.2% decrease in the household electricity consumption. This corresponds to a 35.0 GWh decrease in the overall household electricity consumption, 1.6–5.1 million USD decrease in electricity cost, and 17.5 kilotons of CO2 emission. The results suggest that the cost of electricity consumption should be included in the economic cost analysis of PM2.5 pollution in the future. A 1 °C increase in the monthly temperature is in the long-run significantly related to a 13.6% increase in the monthly electricity consumption for Singapore, while a 30 degree days increase in heating & cooling days (HCDD) is in the long-run significantly related to a 24.9% increase in the monthly electricity consumption for Shanghai. A 5-day increase in the number of rainy days per month is in the long-run significantly related to a 3.0% and 5.8% increase in the monthly electricity consumption for Singapore and Shanghai, respectively

    Mining typical load profiles in buildings to support energy management in the smart city context

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    Mining typical load profiles in buildings to drive energy management strategies is a fundamental task to be addressed in a smart city environment. In this work, a general framework on load profiles characterisation in buildings based on the recent scientific literature is proposed . The process relies on the combination of different pattern recognition and classification algorithms in order to provide a robust insight of the energy usage patterns at different level s and at different scales (from single building to stock of buildings). Several im plications related to energy profiling in buildings, including tariff design, demand side management and advanced energy diagnos is are discussed. Moreover, a robust methodology to mine typical energy patterns to support advanced energy diagnosis in buildin gs is introduced by analysing the monitored energy consumption of a cooling/heating mechanical room

    Chalmers Campus as a Testbed for Intelligent Grids and Local Energy Systems

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    This paper presents an overview of a testbed for intelligent distribution grids, local energy systems, and energy flexible buildings, which is being developed at the campus of Chalmers University of Technology in Gothenburg, Sweden. It describes the test sites, the functionalities, and the planned demonstration activities within the scope of on-going research projects. The proposed demonstrations include a local energy market platform, energy management solutions for microgrids and smart buildings, as well as voltage control in distribution grids. The paper aims to show how the physical energy supply systems of the university are being adapted to integrate the communication and control set-ups that provide the technical requirements for smart grid interoperability. As an example, the on-site implementation of remote battery control is presented, where initial results show the feasibility and potential benefits of the external control. Finally, challenges and lessons learned during the development of the testbed are highlighted
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