PEAK SHAVING STRATEGIES IN HYBRID POWER SYSTEM USING POWER PINCH ANALYSIS
Load demandudistribution variesbdepending onBtime and ambientNtemperature and isanot constant. The electricitybpricing also differs based on the consumption time ofupower where higher price has to be payed during peak hours. Therefore, the applicationNof peak shaving strategies has been proposed d...
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| Main Author: | |
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| Format: | Final Year Project |
| Language: | English |
| Published: |
IRC
2019
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| Online Access: | http://utpedia.utp.edu.my/20044/1/Harchana%20FYP2%20Dissertation.pdf http://utpedia.utp.edu.my/20044/ |
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| Summary: | Load demandudistribution variesbdepending onBtime and ambientNtemperature and isanot constant. The electricitybpricing also differs based on the consumption time ofupower where higher price has to be payed during peak hours. Therefore, the applicationNof peak shaving strategies has been proposed due to the significantNdifferenceNof theNloadbprofilesNover time. Peak shaving strategies are applied as it reduces the electricity purchased from the grid during peak hours which provides a reduction in energy cost. Theuobjective of this project was to study the effects of peak shaving strategies in Hybrid Power System (HPS) using Power Pinch Analysis (PoPA) known as Modified Storage Cascade Table (SCT). Modified SCT was specifically used as power losses that occur during conversion, transfer and storage were considered. Three design parameters were useful to be extracted from the Modified SCT which are minimum outsourced electricity supply (MOES), available excess electricity for next day (AEEND) and maximum storage capacity. The peakushavingNmethods used in this project are load shifting, peak clippingBand valley filling. The effects of the proposed strategies were evaluated using payback period by dividing the net capital investment with the net annual savings. Overall all the strategies can significantly reduce the amount of electricity purchased from the grid with load shifting giving the lowest payback period of 0.39 year for Case Study 1 and 0.83 year for Case Study 2. |
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