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Author

Nursyarizal Mohd Nor

Other affiliations: Petronas
Bio: Nursyarizal Mohd Nor is an academic researcher from Universiti Teknologi Petronas. The author has contributed to research in topics: Magnet & Stator. The author has an hindex of 15, co-authored 99 publications receiving 1246 citations. Previous affiliations of Nursyarizal Mohd Nor include Petronas.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors present a comprehensive and significant research conducted on state-of-the-art intelligent control systems for energy and comfort management in smart energy buildings (SEB's).
Abstract: Buildings all around the world consume a significant amount of energy, which is more or less one-third of the total primary energy resources. This has raised concerns over energy supplies, rapid energy resource depletion, rising building service demands, improved comfort life styles along with the increased time spent in buildings; consequently, this has shown a rising energy demand in the near future. However, contemporary buildings’ energy efficiency has been fast tracked solution to cope/limit the rising energy demand of this sector. Building energy efficiency has turned out to be a multi-faceted problem, when provided with the limitation for the satisfaction of the indoor comfort index. However, the comfort level for occupants and their behavior have a significant effect on the energy consumption pattern. It is generally perceived that energy unaware activities can also add one-third to the building’s energy performance. Researchers and investigators have been working with this issue for over a decade; yet it remains a challenge. This review paper presents a comprehensive and significant research conducted on state-of-the-art intelligent control systems for energy and comfort management in smart energy buildings (SEB’s). It also aims at providing a building research community for better understanding and up-to-date knowledge for energy and comfort related trends and future directions. The main table summarizes 121 works closely related to the mentioned issue. Key areas focused on include comfort parameters, control systems, intelligent computational methods, simulation tools, occupants’ behavior and preferences, building types, supply source considerations and countries research interest in this sector. Trends for future developments and existing research in this area have been broadly studied and depicted in a graphical layout. In addition, prospective future advancements and gaps have also been discussed comprehensively.

689 citations

Journal ArticleDOI
TL;DR: In this paper, a review on the building energy scenario, the policy perspectives, building energy efficiency programs along with landmark buildings and their characteristics are discussed, and the potential of renewable energy resources in buildings and various prospective issues and challenges faced by the country have also been discussed.
Abstract: Malaysia is located in Southeast Asia near the equator within the typical tropical climatic zone. The efficient use of energy is vital due to the dependency on fossil resources that are being exhausted, which ultimately cause CO2 emissions. Economic development and population growth are deemed to affect the growing energy demand in the country. Therefore, sustainability, energy security, and climate change are crucial challenges for the power sector in Malaysia. The aforementioned issues can be tackled with energy efficient measures in the building sector. Buildings in Malaysia consume 14.3% of the overall energy and 53% of only electrical energy is being consumed in residential and commercial sectors. Therefore, energy efficiency in buildings is crucial in order to reduce the energy use and improve the local environmental sustainability. This paper discusses a review on the building energy scenario, the policy perspectives, building energy efficiency programs along with landmark buildings and their characteristics. Besides, the potential of renewable energy resources in buildings and various prospective issues and challenges faced by the country have also been discussed. The significant review content thus benefits researchers, scientists and practitioners for a better understanding on energy efficiency and the sustainable measures that have been so far taken. The review also puts forward some actions to promote building energy efficiency and conservation.

100 citations

Journal ArticleDOI
TL;DR: In this article, a multi-agent control system has been developed in combination with stochastic intelligent optimization, where the multi-objective genetic algorithm (MOGA) was used as optimization algorithm.

75 citations

Journal ArticleDOI
TL;DR: A mixed integer optimization using genetic algorithm for determining the optimum size and placement of battery-sourced distributed PV generation (B-SDPVG) in distribution networks and it was revealed that integration of battery storage and intelligent scheduling for charging and discharging of batteries produced much better results and improved the quality of distribution networks.
Abstract: Batteries are essential for efficiently utilizing the energy from the photovoltaic (PV) modules. However, integration of batteries with PV plants at large scale needs more attention in terms of size, location, and times for the charging and discharging of the batteries. This paper addresses these aspects. It presents a mixed integer optimization using genetic algorithm for determining the optimum size and placement of battery-sourced distributed PV generation (B-SDPVG) in distribution networks. The total energy loss index is formulated as the main objective function and simultaneously, the bus voltage deviations and penetrations of the B-SDPVG are calculated. The yields from the PV plants are estimated using 15 years of weather data modeled with the aid of beta probability density function. Furthermore, a novel charge–discharge control model is developed for determining the choice of the charging and discharging of batteries at each hour. By considering different time varying voltage-dependent load models, the proposed algorithm is applied on the IEEE 33 bus and the IEEE 69 bus test distribution networks. The numerical results of two distribution networks with time-varying loads show the advantages of the proposed methodology. It was revealed that integration of battery storage and intelligent scheduling for charging and discharging of batteries produced much better results and improved the quality of distribution networks. The supply of power from the B-SDPVG during the peak load hours and at night was made possible for each load model. The proposed charge–discharge control model for scheduling the charging and discharging of the batteries was found dynamic. Results of this paper can be of potential importance in planning for the integration of battery storage in distribution networks.

39 citations

Proceedings ArticleDOI
01 Oct 2015
TL;DR: In this article, the authors reviewed different energy storage systems (ESS) and their sizing techniques, used in power system and recommended that current energy models used for sizing of energy storage should be reconsidered and re-designed.
Abstract: The increasing penetration of renewable energy sources in electrical grids mandates to utilize some energy storage to overcome the variations of intermittent power outputs. The energy storage technologies can help in balancing the generation and demand by storing unused electricity and then supplying it back to grid when required. In future grids, energy storage technologies are expected to become a major source of electricity; a collaborator to those distributed generations (DG) resources. The objective of this research was to review different energy storage systems (ESS) and their sizing techniques, used in power system. Study focused on Mechanical Energy Storage (MES), Electric and Magnetic Energy Storage (EMES) and Electro-Chemical Energy Storage (ECES) systems. Through this review, it is known that most of the research regarding energy storage sizing for large PV plants follow similar techniques as used for standalone PV systems. Additionally some authors have proposed energy models which considered only daily or yearly energy demand without considering certain network constraints. Estimating energy storage capacity without considering the electrical networks constraints may pose a threat to future energy balance predictions leading to a huge loss of investment due to unplanned storage sizing. Therefore it is recommended that current energy models used for sizing of energy storage should be reconsidered and re-designed.

38 citations


Cited by
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01 Oct 2012
TL;DR: MedicineNet是一家在线医疗保健出版公司,通过友好的交互式网站为用户提供通俗易读的专业权威性医学信息。
Abstract: MedicineNet是一家在线医疗保健出版公司,通过友好的交互式网站为用户提供通俗易读的专业权威性医学信息。该网站编辑团队由训练有素、极富经验的内科学、健康管理、互联网技术和商业领域资深专家组成,主体成员为经董事会认证的70多位内科医生。网站自成立以来得到了全美国用户的认可。

394 citations

Journal ArticleDOI
12 Mar 2018-Energies
TL;DR: In this paper, the authors introduce a common dictionary and taxonomy that gives a common ground to all the engineering disciplines involved in building design and control, and critically discuss the outcomes of different existing MPC algorithms for building and HVAC system management.
Abstract: In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems and the availability of a significant amount of monitored building data. MPC has found successful implementation in building thermal regulation, fully exploiting the potential of building thermal mass. Moreover, MPC has been positively applied to active energy storage systems, as well as to the optimal management of on-site renewable energy sources. MPC also opens up several opportunities for enhancing energy efficiency in the operation of Heating Ventilation and Air Conditioning (HVAC) systems because of its ability to consider constraints, prediction of disturbances and multiple conflicting objectives, such as indoor thermal comfort and building energy demand. Despite the application of MPC algorithms in building control has been thoroughly investigated in various works, a unified framework that fully describes and formulates the implementation is still lacking. Firstly, this work introduces a common dictionary and taxonomy that gives a common ground to all the engineering disciplines involved in building design and control. Secondly the main scope of this paper is to define the MPC formulation framework and critically discuss the outcomes of different existing MPC algorithms for building and HVAC system management. The potential benefits of the application of MPC in improving energy efficiency in buildings were highlighted.

319 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated heat pump systems in smart grids, focussing on fields of application and control approaches that have emerged in academic literature, based on a review of published literatu...
Abstract: This paper investigates heat pump systems in smart grids, focussing on fields of application and control approaches that have emerged in academic literature. Based on a review of published literatu ...

310 citations