Load Control in Real Time Price Prediction

dc.accessRightsAnonymous*
dc.audienceScience
dc.contributor.authorArsi, Irisa
dc.contributor.mentorWache, Holger
dc.date.accessioned2017-09-05T18:19:35Z
dc.date.available2017-09-05T18:19:35Z
dc.date.issued2017-06-20
dc.description.abstractSwitzerland’s electricity consumption in 2014 was 59.3 TWh (Abrell, 2016) and continues to rise every year. As residential needs for electrical energy increase, so does the demand (Abrell, 2016; Filippini, 2011; IEA, 2012; Zhao et al, 2013). As a result, the necessary energy for meeting the demand cannot be provided by the power grid (Abrell, 2016; Filippini, 2011). The Swiss government has tried by applying new methods in price calculation for electricity to help shift the loads to different times (Abrell, 2016). Nevertheless, over- loadings and blackouts occur several times per year creating high maintenance costs (Abrell, 2016; Filippini, 2011), for the production companies which reflects to the users’ payments as well. On the one hand consumers' demand aims at electrical energy of high quality and reliability (Abrell, 2016), but on the other hand producers’ aim in less maintenance costs. A clear solution is needed for the demand and supply of Switzerland’s grid to balance. A new solution, a new methodology based not entirely in technology but also in the correct use of Information Systems. This paper will describe a new proposal, solution for the Swiss energy production and consumption to balance through energy scheduling and flexible pricing. Smart buildings and smart appliances, will provide users, with an ECO efficient use of the energy through the Information. The users can create their own demand schedule, in accordance to the calculated prices by the combination of RTP and IBR and their actual needs. During Real Time Electricity Pricing (RTP) prices can be generated hourly and transmitted to users. A problem that increases with RTP is that users tend to maximize the use of their appliances during the low peak prices and potentially create overloads, which could lead to instability of the grid or even a power blackout. In order, to avoid such problems, and secure except of flexible prices also reliability and stability for the system, RTP needs to be combined with the Inclining Block Rate (IBR) methodology. During IBR pricing prices can be calculated according to the loads. The combination of the two methodologies give the possibility to the users not only to schedule their energy use by time but loads as well. An important fact that rises through this proposal is the possibility, given to the energy production companies and the government, to balance the maintenance costs which will lead in saving thousands of francs every year by simply involving the end-users in the electric grid operation. Simply by giving the possibility to users to control their appliances’ consumption, for different periods, by reducing their consumption or shift their loads to low peak periods.
dc.identifier.urihttp://hdl.handle.net/11654/25424
dc.identifier.urihttps://doi.org/10.26041/fhnw-1150
dc.language.isoenen_US
dc.publisherHochschule für Wirtschaft FHNW
dc.spatialOlten
dc.subjectRTP Real Time Pricing
dc.subjectIBR Inclining Block Rate
dc.subjectDR Demand Response
dc.subjectIS Information Systems
dc.subjectICT Information Communication Technology
dc.subjectRTEP Real Time Electricity Prices
dc.subjectPAR Power Peak Ratio
dc.subjectTOU Time of Use
dc.subjectTOUR Time of Use Pricing
dc.subjectCPP Critical Peak Pricing
dc.subjectkWh Kilowatt- hour
dc.subjectTWh Terawatt- hour
dc.subjectRES Renewable Energy Sources
dc.subjectWEM Wholesale Energy Market
dc.subjectES Energy Scheduling
dc.subjectFBE Free Basic Electricity
dc.subjectTSO Transmission system operator
dc.subjectRA Regulatory authority
dc.subjectElCom Federal Electricity Commission
dc.subjectEMS Energy management system
dc.subjectEMC Energy management controller
dc.subjectAOA Automatically operated appliance
dc.subjectMOA Manually operated appliance
dc.subjectLOT Length operation time
dc.subjectOTI Operation time interval
dc.subject.ddc004 - Computer Wissenschaften, Internetde
dc.subject.ddc003 - Systemede
dc.titleLoad Control in Real Time Price Prediction
dc.type11 - Studentische Arbeit
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.IsStudentsWorkyes
fhnw.PublishedSwitzerlandYes
fhnw.StudentsWorkTypeMaster
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutMaster of Sciencede_CH
relation.isMentorOfPublication9a5348f4-47b3-437d-a1f9-7cf66011e883
relation.isMentorOfPublication.latestForDiscovery9a5348f4-47b3-437d-a1f9-7cf66011e883
Dateien

Originalbündel

Gerade angezeigt 1 - 1 von 1
Vorschaubild
Name:
Arsi_Irisa_2017_Load control in real time prediction.pdf
Größe:
2.55 MB
Format:
Adobe Portable Document Format
Beschreibung: