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<p>The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are conventional method for C1 ETOU, C2 ETOU, and C1 ETOU with Optimization technique, and C2 ETOU with optimization technique tariff, respectively. The impact of the EP has been analysed, while the performance of six-time segmentation of C1 and C2 ETOU tariff indicate that the electricity cost for the medium voltage of installation has been reduced. It is hoped that the results from this study can benefit consumers by giving them the flexibility to rearrange their own energy consumption profile, so that the demand side will enjoy significant reduction of electricity cost in the future.</p><p> </p>

This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. Subsequently, significant simulation results of operation profit gain through 24 hours electricity consumption had been analyzed properly. The proposed method had shown reduction of approximately 6% of the electricity cost at peak and mid peak zones, when 20%, 40%, 60%, 80% and 100% load shifting weightages were applied to the identified 10% controlled loads consequently. It is hoped that the finding of this study can help poise the manufacturers to switch to ETOU tariff as well as support the national Demand Side Management (DSM) program

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Objective of this study is to estimate building energy saving at Bangunan Sultan Salahuddin Abdul Aziz Shah from a retrofit of Water Cooling Package Unit (WCPU) system. This research calculates energy savings as recommended by International Performance Measurement and Verification Protocol (IPMVP) using Option C-Whole Facility Measurement. In this study, the baseline period is defined from July 2012 to June 2013, the retrofit of WCPU was performed on July 2013 and the reporting period is from August 2013 to July 2014. The baseline energy use and the post retrofit energy use data are collected from utility bills. On the other hand, the energy governing factors other than the retrofit such as outdoor temperature or Cooling Degree Day (CDD), number of working days (NWD) and occupancy on the building are gathered corresponding to the pre-defined baseline and post-retrofit period. These non-retrofit energy governing factors are used to model adjusted baseline energy in calculating energy savings using regression analysis. Two types of energy saving analyses have been presented in the case study; 1) Single linear regression for each independent variable, 2) Multiple linear regression. Results show that number of occupancy has the highest coefficient regression, R2 followed by NWD and CDD. This indicates that occupancy has stronger correlation with the energy use in the building than NWD and CDD. Finding also shows that the R² for multiple linear regression model are higher than single linear regression model. This shows the fact that more than one component are affecting the energy use in the building.

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