Hussein Swbahi Department of Computer Science Faculty of Mathematical and Computer Sciences, University of Gezira, Wadmadani, Sudan [email protected] Abusfian Elgelany Department of Computer Science, Faculty of Computer Studies Information Technology University of Garden City, Khartoum, Sudan [email protected] Awadallah M. Ahmed Department of Computer Science, Faculty of Mathematical and Computer Sciences, University of Gezira, Wadmadani, Sudan [email protected] is a dramatic increase in electricity consumption in many countries specifically in the residential sector.
In Sudan, residential buildings responsible for 54 of the total electricity consumption and still in growth. There is a lack of energy efficiency studies and knowledge to be provided for consumers. Most people dont know how much electricity they are consuming for different reasons and they are unaware of potential electrical consumption reduction level they could make by changing their behaviours or investing in new efficient technology. Feedback, on electricity consumption may provide a tool for consumers for better control their consumption and ultimately giving them useful indicators for saving electricity. Therefore, this paper comes to enhance the ability of consumers to reduce their electricity consumption by developing an interactive analysis tool to help the consumers to collect and analyse their electricity consumption data. The remarkable point is that the results generated by the ECA tool have been presented in texts, graphs, and tables in order to be more effective and clear for the users.
The interactive tool has been evaluated using Technology Acceptance Model (TAM), which is one of the most widely accepted models in the adoption of new technologies. The evaluation results show that the users in terms of perceived usefulness and perceived ease of use accepted the interactive electricity analysis tool. Keywordselectricity feedback saving electricity Technology Acceptance Model (TAM). Introduction Nowadays, there is a dramatic increase in electricity consumption in many countries specifically in the residential sector, in Sudan, residential buildings responsible for 54 of the total consumption and still in growthADDIN CSL_CITATION citationItems id ITEM-1, itemData author dropping-particle , family Forum-hamburg, given Energy, non-dropping-particle , parse-names false, suffix , id ITEM-1, issued date-parts 2017 , title What kind of energy production do we need to industrialize Sudan , type article-journal , uris http//www.mendeley.com/documents/uuid05c339d5-8cb3-4c38-bbf5-d50c4e53c590 , mendeley formattedCitation 1, plainTextFormattedCitation 1, previouslyFormattedCitation 1 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 1, where the power sector in Sudan is facing hard times and has a lot of challenges due to the lack of capacity with respect to the increasing demand for electricity.
That leads to electricity cut at certain times during the day. Electricity has become a scarce and expensive resource. People are unaware of their consumptions which lead to waste this energy because of the lack of consumers awareness of their electricity consumption. In Sudan, there is a lack in both energy efficiency studies and knowledge provided to consumers, which can help in improving energy efficiency as well as saving money and electricity, which means give other people who do not access electricity a chance to access and without a better understanding of electricity consumption, efficiency improvements will be difficult or impossibleADDIN CSL_CITATION citationItems id ITEM-1, itemData author dropping-particle , family Kollmuss, Anja, given and Julian Agyeman, non-dropping-particle , parse-names false, suffix , container-title international conference on Ubiquitous computing, id ITEM-1, issued date-parts 2009 , page 255-264, title Its not all about green Energy use in low-inco me co mmunit ies, type article-journal , uris http//www.mendeley.com/documents/uuid839a4bac-0271-4c53-aa90-b8d6a250a521 , mendeley formattedCitation 2, plainTextFormattedCitation 2, previouslyFormattedCitation 2 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 2. Numerous studies have found that provide users with better data and better feedback may result in reduced electricity consumption over various periods of timeADDIN CSL_CITATION citationItems id ITEM-1, itemData DOI 10.1007/s12053-008-9009-7, author dropping-particle , family Fischer, given Corinna, non-dropping-particle , parse-names false, suffix , dropping-particle , family Fischer, given Corinna, non-dropping-particle , parse-names false, suffix , id ITEM-1, issue March, issued date-parts 2015 , title Feedback on household electricity consumption A tool for saving energy a tool for saving energy , type article-journal , uris http//www.mendeley.com/documents/uuide7b5b986-3bdb-4593-8361-b1ab34d6ac38 , mendeley formattedCitation 3, plainTextFormattedCitation 3, previouslyFormattedCitation 3 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 3.
However, there still few studies have been conducted in this area despite the powerful of the computerized feedback toward the energy efficiency. Energy efficiency means doing more with less energy, which leads to numerous benefits to the consumer, country, and the world. The outcomes of energy efficiency are numerous such as saving money, improving the economy, also the energy efficiency is good for the environment and has become an important targeted policy. Currently, many research efforts helped in making visualization highly exhibiting and technologically sound, the electricity tracking started moving towards bringing the sustainable behaviour through the human computer interaction (HCI)ADDIN CSL_CITATION citationItems id ITEM-1, itemData author dropping-particle , family Murugesan, given Latha Karthigaa, non-dropping-particle , parse-names false, suffix , dropping-particle , family Hoda, given Rashina, non-dropping-particle , parse-names false, suffix , dropping-particle , family Salcic, given Zoran, non-dropping-particle , parse-names false, suffix , id ITEM-1, issue 3, issued date-parts 2014 , page 2725-2729, title Visualization of Electricity Consumption Software Prototype through Literature, type article-journal, volume 3 , uris http//www.mendeley.com/documents/uuidefff65d6-d988-4cff-b057-a2b60052412f , mendeley formattedCitation 4, plainTextFormattedCitation 4, previouslyFormattedCitation 4 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 4 Therefore, an analysis tool is needed to help the consumers be aware of the electricity consumption of their home in order to use the electricity in a good way as well as saving electricity and money for them. Therefore, the main objective of this paper is to develop an interactive tool that enables users to collect and analyze their personal electricity consumption data to reduce wasteful electricity, which leads to achieving the following sub objectives Make the consumers more aware of their own electricity usage Development of electricity efficiency in the residential sector Create a dataset on long-term, which can help researchers to analyse residential energy performance issues Related Works In ADDIN CSL_CITATION citationItems id ITEM-1, itemData author dropping-particle , family Education, given Energy, non-dropping-particle , parse-names false, suffix , dropping-particle , family Rolland, given Module, non-dropping-particle , parse-names false, suffix , dropping-particle , family Chang, given Mai Sue, non-dropping-particle , parse-names false, suffix , dropping-particle , family Marienthal, given Eli, non-dropping-particle , parse-names false, suffix , dropping-particle , family Programming, given Fortran, non-dropping-particle , parse-names false, suffix , dropping-particle , family Coughlin, given Katie, non-dropping-particle , parse-names false, suffix , dropping-particle , family Homan, given Gregory, non-dropping-particle , parse-names false, suffix , dropping-particle , family Brinkman, given Jordan, non-dropping-particle , parse-names false, suffix , dropping-particle , family Homan, given Gregory, non-dropping-particle , parse-names false, suffix , id ITEM-1, issue July 2005, issued date-parts 2008 , title The Home Energy Saver and Infrastructure, type article-journal , uris http//www.mendeley.com/documents/uuide35ea4bc-1c2c-4f99-8940-56530978140c , mendeley formattedCitation 5, plainTextFormattedCitation 5, previouslyFormattedCitation 5 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 5 an interactive website was designed to help residential consumers make decisions about energy usage in their homes the website called Home Energy Saver (HES, http//HomeEnergySaver.lbl.gov).
Its aim is to increase consumer interest in energy efficiency furthermore, the interactive website tool used for analysing residential energy performance. In ADDIN CSL_CITATION citationItems id ITEM-1, itemData author dropping-particle , family ZURICH, given ETH, non-dropping-particle , parse-names false, suffix , id ITEM-1, issue 21143, issued date-parts 2013 , title MOTIVATING ENERGY-EFFICIENT BEHAVIOR WITH INFORMATION SYSTEMS UNDERSTANDING THE IMPACT OF PERSONALIZATION AND REWARDS ON USER BEHAVIOR, type thesis , uris http//www.mendeley.com/documents/uuid0e8507fd-5729-420c-b220-a2d44c256d9d , mendeley formattedCitation 6, plainTextFormattedCitation 6, previouslyFormattedCitation 6 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 6 the author empirically examines the role of information systems in motivating energy-efficient behaviour in households by providing users with feedback and advices about electricity consumption through a web portal named Oscar. The study found that the Oscar is a powerful and cost effective tool for electricity conservation. In ADDIN CSL_CITATION citationItems id ITEM-1, itemData author dropping-particle , family Zenebe, given Merkebu Degefa, non-dropping-particle , parse-names false, suffix , id ITEM-1, issued date-parts 2010 , title INTERACTIVE WEB-BASED GUIDELINE FOR THE EFFICIENCY OF HOUSEHOLD ELECTRIC POWER CONSUMPTION Establishing the web-based application, type article-journal , uris http//www.mendeley.com/documents/uuidae0afe87-b466-4fa1-bb25-9e79a54b2606 , mendeley formattedCitation 7, plainTextFormattedCitation 7, previouslyFormattedCitation 7 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 7 the author has designed an interactive web-based guidelines to incorporate personalized saving potential calculation results with the delivery of feedback to householders.
The personalized feedback is based on user input information with consideration of combinational effects of individual appliances. Data collection process is divided into two stages firstly, the data used in the tool design and specifications. The data for this stage have been collected from the literature review and related works. The second stage concerns with the data about the home description to create a baseline for the tool to work, through a public online survey called SurveyPlanet.
system design This section includes system context and functional requirements defining. System context ECA Tool has been designed to help consumers gain more understanding on their electricity consumptions by allowing them to collect and analysis their own electricity usage. ECA provides end-user with information, which leads to reduce the electricity consumption and achieve energy efficiency. Table 1 lists the critical functional requirements of the ECA Tool. Table 1 ECA Tool Functional Requirements (FR) IDFunctional RequirementsFR1The ECA Tool provides the home rating (good, Fair, bad). FR2The ECA Tool provides possible electricity saving in kw.FR3The ECA Tool provides possible cost saving in SDG.FR4The ECA Tool provides a list of recommendations to save eelectricity.
FR5The ECA Tool provides a visual graph that present Neighborhood comparison feedbackFR6The ECA Tool provides a visual graph that presents historical months comparison. System functionalities ECA Tool provides its users with several functionalities, such as neighbourhood comparison feedback, energy-efficiency rating feedback, and saving tips. The following subsections describe and illustrate these functionalities in details. Neighborhood comparison feedback ECA Tool provided the consumers with a neighbourhood comparison feedback. The comparison consists of a scale comparing the users monthly electricity consumption to the average electricity consumption of the users neighbourhood and to the best practice neighbourhood.
This type of comparison is called normative descriptive feedback. It helps the users to assess how well they are performing in relation to their peers. In order to have access to the neighbourhood comparison feedback, the users have to enter their location and the number of household in their homes. Energy-efficiency rating feedback ECA Tool provides the consumers with feedback regarding their energy-efficiency.
Firstly, the consumer defines their household profile by entering the following inputs that describe his/her house in the registration step, such as household size in meter square ( QUOTE ), number of persons live in the households and so on, hence the house information will be added the dataset, which will be built accumulatively, so that will have a big dataset over long time. Then the ECA Tool ranks the users according to their energy-efficiency rates, which are calculated based on their inputs and electricity consumption on a rating (good, fair, bad). This type of feedback is called the injunctive feedback. ECA Tool re-assess the users efficiency every month just by entering consumption of that month to help them track their efficiency rating improvement.
Saving tips The aim of ECA tool is to increase the consumers knowledge regarding electricity consumption and improve their ability to conserve electricity and to achieve this goal, ECA tool provides their users with a list of recommendations to save electricity. Structural models for ECA Tool Figure 1 shows the structural model for ECA Tool. The following sections describe each component of the model in detail. Figure 1 Structural models for ECA Tool Input model This model identify all the data inputs required as follows Home description Household location Household size (Gross Floor Area) The Total Gross floor area of the building Number of residents in the building Month consumption gathering the electricity consumption information from utility bills every month.
Processing model Specific metric, key performance indicators (KPIs), and benchmarking technique that will be applied. Energy Use Intensity (EUI) Metric The widely accepted metric, EUI expressed in kW/ QUOTE month for evaluation of building energy efficiencyADDIN CSL_CITATION citationItems id ITEM-1, itemData author dropping-particle , family Selvacanabady, given A, non-dropping-particle , parse-names false, suffix , id ITEM-1, issued date-parts 2017 , number-of-pages 40, title The Influence of Occupancy on Building Energy Use Intensity and the Utility of an Occupancy-Adjusted Performance Metric, type report , uris http//www.mendeley.com/documents/uuida6960a2f-bdd9-4ae6-9c1d-fe483daf7144 , mendeley formattedCitation 9, plainTextFormattedCitation 9, previouslyFormattedCitation 9 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 9. Key Performance Indicators (KPIs) The KPIs that will be used here based on selected indicators on existing buildings for monitoring consumers building performance and setting priorities for energy conservation measures, by comparing against other buildings or historical performance. This kind of data may also be entered by policy makers and stakeholders to monitor the building stock and progress towards meeting national targets.
Electricity saving kWh Difference between measured and reference data. Cost savings Difference between measured and reference data multiplied by price. Benchmarking The electricity performance metric plays a key role in energy benchmarking of buildings (also known as energy efficiency indicators). The most common performance metric for whole building energy consumption is Energy Performance Indicator (EPI) or Energy Use Intensity (EUI). Benchmarking consists of a comparison of the EPI or EUI of a building with a sample of similar buildings or with the best-practice building.
A common EPI or EUI used for many building types is annual energy use normalized with floor area. Which leads to energy audits and assesses saving opportunities by comparing with existing references (benchmark) of average (typical), above average (good), and excellent (best) practice. ADDIN CSL_CITATION citationItems id ITEM-1, itemData DOI 10.1007/978-3-319-21798-7, ISBN 9783319217987, author dropping-particle , family Kolokotsa, given Dionysia, non-dropping-particle , parse-names false, suffix , dropping-particle , family Environments, given Managing Indoor, non-dropping-particle , parse-names false, suffix , dropping-particle , family Energy, given Green, non-dropping-particle , parse-names false, suffix , id ITEM-1, issued date-parts 2011 , page 13-32, title Review and State of the Art on Methodologies of Buildings u2019 Energy-Ef fi ciency Classi fi cation, type article-journal , uris http//www.mendeley.com/documents/uuid8b94de3f-0a79-4c86-9b2d-1354cb8db4e2 , mendeley formattedCitation 10, plainTextFormattedCitation 10, previouslyFormattedCitation 10 , properties noteIndex 0 , schema https//github.com/citation-style-language/schema/raw/master/csl-citation.json 10. Output model The home rating (Good, Fair, Bad) List of recommendations Cost saving Electricity saving in KW Energy-efficiency score calculation User gets results calculated by the algorithm shown in figure 2, using the house description that more closely matches his/her house. The algorithm calculates the home energy efficiency score (good, fair, bad) of the users home. Algorithm 1 Step1 Input Home size Month consumption Residents number Home location Step2 Calculate EUI Step3 calculates the home performance (perf) requires the EUI of the building and the EUI of similar buildings or with the best-practice building (best).
Step4 Checks the home performance (perf) If (perf90) ScoreGood Else if (perf70 and perf89) ScoreFair Else if (perf69) ScoreBad End if Figure 2 algorithm for calculating the home energy efficiency score results In this section the results of the implementation and evaluation of the ECA Tool are presented. Figure 3 shows the results analysis page, which represents the core of the ECA Tool. This page provides the user with various useful information such as the home energy efficiency rating (Bad, Fair, Good), Neighbourhood comparison, possible energy saving. Possible cost saving and list of recommendation to help user improve his/her home energy efficiency. Figure 3 Analysis page Evaluation Model For the purposes of this work TAM model (Davis, 1989) has been used and the external variables have excluded. The final model is shown in Figure 4.
The reason why we skip attitudes towards use and stopped at the actual usage, because the tracking and analysis electricity online is an new idea in Sudan. Figure 4 Evaluation Model In this work, questionnaire items were developed based on the existing, well-established questionnaire used in the TAM literature, with some modifications to suit this particular case, which are shown in table 2. Table 2 The questionnaire items Section I Perceived Usefulness (PU)Using ECA Tool provides me with useful information.PU1Using ECA Tool helps me to become more aware.PU2Using ECA Tool can improve my home energy efficiency rating.PU3Using ECA Tool can save me a lot of money.PU4Section II Perceived Ease of Use (PEOU)ECA Tool is easy to use.PEOU1ECA Tool is user-friendly. PEOU2It is easy to become skilful at using ECA Tool.PEOU3 The survey respondents were asked to rate their opinion using a five-point scale ranging from 1strongly disagree, 2disagree, 3neither disagree nor agree, 4agree and 5strongly agree, for perceived usefulness and perceived ease of use. Demographic Data The first part of the questionnaire focuses on general information about the respondents.
The gender chosen based on 24 (77.4) of the respondents are male and 7 (22.6) are female. The age ranges between 21-25 years old with 11 (35.5) and 26-30 years old with (65.5). The education level are 4 (12.9) of the respondents were high school. 17 (54.8) of the respondents were bachelor degree and10 (32.2) of the respondents were Master degree. Discussion The descriptive statistics of the two factors Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) are shown in Table 3.
References 6 E. Zurich, Motivating Energy-Efficient Behavior With Information Systems Understanding The Impact Of Personalization And Rewards On User Behavior, 2013. 7 M. D. Zenebe, Interactive Web-Based Guideline For The Efficiency Of Household Electric Power Consumption Establishing the web-based application, 2010.
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