Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building Services Engineering | en_US |
| dc.creator | Wong, Kar-fai Timothy | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/5870 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Electricity demand optimizer for buildings in Hong Kong | en_US |
| dcterms.abstract | Energy is one of the main resources to support human life, economic and industrial growth nowadays. Fossil fuel is dominant to the electrical power supply industry. However, the by-product from power generation using petroleum is carbon dioxide. Increasing carbon dioxide concentration leads to greenhouse effect which causes the atmospheric temperature growing every year, and affecting the ice sheet melt and sea level increase, which is harmful to human body, animal, plant and the earth. Carbon dioxide emissions in Hong Kong are primarily produced by power generation that is about 55% to 64%. Therefore, energy saving can reduce the impact of greenhouse effect and the environment inevitably. There exists many different theories and approaches regarding energy saving for buildings but involve the participation of all people inside that building. It is difficult to ensure all people to play effort and cooperation. The tariff charging schemes for the power supply companies in Hong Kong are aiming to ensure all power consumer to use power with consistent profile, but most of the users consume power from 9:00am to 9:00pm, while consume very little power during night time and general holidays. This situation will cause the power generation and transmission facilities operating in low efficiency. In order to "penalty" the consumers using power fluctuating, the large-consuming tariff schemes are divided into two major parts. They are energy charge (based on the energy consumption in kWh), and demand charge (based on the maximum power demand of the billing month in kVA). If the user use low total energy value but with sudden-high-peak power demand, the power demand charge is to "penalty" the consumer. Different approaches to flatten power demand profile will be discussed. Electrical system is different from other building services system , which is one of the input resources to support other building services equipments, such as air-conditioning, fire services, pump and etc. Therefore, the electricity flow or map is very important for all energy management plans. Furthermore, energy budget play another important role for energy management planning which can reflect the effectiveness of energy usage. The phase VI of The Hong Kong Polytechnic University was used as case study in which the electrical data in the Building Management System in 2007 were retrieved for study. The analysis produced a simulation of power demand model for Jan to Dec 2007 for the prediction of future maximum power demand. The simulated model for Jun-2007 was used to predict the maximum power demand for Jun-2008, and accuracy of the simulation is subject to the accuracies of input parameters such as occupancies numbers and outdoor temperature. The prediction results make the Facility Management Office knowing how to setup the short-time (15 - 30mins.) measures and procedure to reduce the peak demand at predicted date and time. Successful implementation can result a tariff cost saving as shown in the conclusions. | en_US |
| dcterms.extent | xii, 144, [50] p. : ill. ; 31 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2008 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.LCSH | Electric power consumption -- China -- Hong Kong -- Case study | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b2356491x.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 44.1 MB | Adobe PDF | View/Open |
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