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Malaysia has been annually affected by floods during the monsoon season as well as in some cities have flash floods. The floods have caused mass evacuations, deaths, and loss of properties. Malaysia has developed several initiatives to overcome the floods such as the SMART tunnel project and flood monitoring system. However, the initiatives offered are only countering the flood at major places and do not consider a solution for the stagnant flood. In this paper, irrigation of water automatically on natural flood (IRFAN) is proposed as a solution to lower the chances of stagnant flood as well as preventive tools for the upcoming flood. IRFAN is a water diversion technique that can redirect the flow of the water flood through purpose-built channels. This technique can reduce the excess water peak flows and lowers the chances of flood. With the integration of Artificial Intelligence, the water flood can be automatically diverted towards other streams based on the level of water. The system is also embedded with an alarm system to avoid thieves from stealing the main component. The development of this system can help governments and society on reducing mass evacuations, deaths, and loss of properties.

Radiation hazard has inevitably become a global threat due to the widespread use of radiation technology in industrial manufacturing and medicine. As in medicine, the workers are in danger of being exposed to high-penetrating gamma-rays during the treatment of cancerous tumours. Hence, developing such an excellent shielding material from the polymer is vital since it can be used broadly, is low cost, and is non-poisonous to nature. This study aimed to observe the effect of additive content such as bismuth on shielding performance. To test the hypothesis that high-density material leads to higher radiation shielding performance, fabricated bismuth-low-density polyethylene (LDPE) composites that have been processed via internal melt-mixing and compression-moulding processes were labelled with LDPE-100, Bi-5, and Bi-10 containing 0, 5, and 10 wt.% of bismuth content with a thickness of 0.1, 0.2, 0.3, and 0.4 cm respectively. Throughout the experiment, a photon from a gamma source of 241Am and 133Ba with an energy range of 59 keV and 356 keV were captured by a solid-state detector to calculate the count rate in count per second (cps). The fundamental shielding parameter such as mass attenuation coefficient, half-value thickness, tenth-value thickness, and mean free path was also computed using Phy-X software to evaluate the radiation shielding effectiveness. The results showed that Bi-10 polymer composites with 10% wt. of bismuth filler had MAC, HVL, TVL, and MFP values of 1.159 cm2/g, 0.554 cm, 1.838 cm, and 0.798 cm, respectively, and may be used as an effective shielding material for gamma radiation with an energy of 59 keV compared to 356 keV.

Rising awareness for the environment as well as concerns over the sustainability of fossil fuels has encouraged developed and developing countries to find alternative ways to enhance the thermal efficiency of current power systems. The thermal efficiency of power plants can be increased from 30 – 40 % up to 80 – 90 % through the implementation of a trigeneration system by recovering dissipated waste heat for other purposes. The trigeneration system can be defined as a technology that can produce simultaneous power, heating, and cooling energy from the same fuel source. Trigeneration System Cascade Analysis (TriGenSCA) methodology is an optimisation approach based on Pinch Analysis that has been used to establish the guidelines or the proper size of the trigeneration system. This paper proposes a modification of TriGenSCA by considering a multi-period of energy consumption to optimise the size of the utility in the centralised trigeneration system by considering the transmission and storage of energy losses in the Total Site system. There are six steps involved including data extraction, identification of time slices, Problem Table Algorithm (PTA), Multiple Utility Problem Table Algorithm (MU PTA), Total Site Problem Table Algorithm (TS PTA), and modified TriGenSCA. The methodology has been tested on the centralised nuclear trigeneration system in a Total Site System as a case study and results shown that thermal energy needed by the Pressurized Water Reactor (PWR) trigeneration system with transmission losses is 2,427 MW whereas thermal energy needed by the PWR trigeneration system without transmission losses is 2,424 MW. The TriGenSCA with consideration of transmission and storage energy losses is useful for engineers and designers to determine the exact value of energy for trigeneration plant.

The energy and power sectors are critical sectors, especially as energy demands rise every year. Increasing energy demand will lead to an increase in fuel consumption and CO2 emissions. Improving the thermal efficiency of conventional power systems is one way to reduce fuel consumption and carbon emissions. The previous study has developed a new methodology called Trigeneration System Cascade Analysis (TriGenSCA) to optimise the sizing of power, heating, and cooling in a trigeneration system for a Total Site system. However, the method only considered a single period on heating and cooling demands. In industrial applications, there are also batches, apart from continuous plants. The multi-period is added in the analysis to meet the time constraints in batch plants. This paper proposes the development of an optimal trigeneration system based on the Pinch Analysis (PA) methodology by minimizing cooling, heating, and power requirements, taking into account energy variations in the total site energy system. The procedure involves seven steps, which include data extraction, identification of time slices, Problem Table Algorithm, Multiple Utility Problem Table Algorithm, Total Site Problem Table Algorithm, TriGenSCA, and Trigeneration Storage Cascade Table (TriGenSCT). An illustrative case study is constructed by considering the trigeneration Pressurized Water Reactor Nuclear Power Plant (PWR NPP) and four industrial plants in a Total Site system. Based on the case study, the base fuel of the trigeneration PWR NPP requires 14 t of Uranium-235 to an average demand load of 93 GWh/d. The results of trigeneration PWR NPP with and without the integration of the Total Site system is compared and proven that trigeneration PWR NPP with integration is a suitable technology that can save up to 0.2% of the equivalent annual cost and 1.4% of energy compared to trigeneration PWR NPP without integration.

Hybrid power systems are becoming more popular nowadays as they provide a good transition towards renewable energy systems integration while still maintaining power sources from fossil fuels. Uncertainties based on seasonal changes, weather patterns and demand fluctuations have been considered. Disasters such as earthquake, tornado and hurricane are becoming more frequent and unpredictable as climate change is affecting major parts of the world. Safety and resilience are two important aspects that need to be taken into consideration in designing power systems due to the increase in extreme weather and natural disasters. Safety precautions are taken into consideration to withstand major damage and ensure the power system can continue to run smoothly with no or little interruption to the power supply. Previous studies focused on optimizing the cost and efficiency of the system based on season change, weather and demand fluctuations. The purpose of this research is to develop a novel methodology to design a hybrid power system considering resilience and safety aspects. This research primarily focuses on the use of Decision Matrix Risk Assessment Technique (DMRA) and Power Cascade Table (PCT) to evaluate the impact of disasters towards the power systems with and without safety consideration. The results of the case study have shown that the implementation of safety can reduce the total cost by up to USD209.3 M when catastrophic events occur.

The development of biomass-based cogeneration energy systems in Malaysia is progressing to meet the circular economy concept and sustainability goal. This comprehensive review aims to report recent advancements in biomass-based cogeneration/biomass co-firing technology in Malaysia correlated with the optimization modeling role. First, this work presents the outlook and current scenario of cogeneration systems in Malaysia by observing performance and the challenges confronted by the technologies. Next, investigation of technical issues concerning the key players of the technologies and the biomass supply chain. This work had prepared using quantitative content-based analysis-meta-analysis. The practical implication of this review enables a complex optimization model that integrates biomass-based cogeneration and biomass supply chain considering economic and environmental viability. It will further enhance progress toward the Malaysian “Industry 4.0-driven” energy initiative. A novel optimization model grounded on Industry 4.0 parameters will foster new opportunities for researchers.

Research and development on integrated energy systems such as cogeneration and trigeneration to improve the efficiency of thermal energy as well as fuel utilisation have been a key focus of attention by researchers. Total Site Utility Integration is an established methodology for the synergy and integration of utility recovery among multiple processes. However, Total Site Cooling, Heating and Power (TSCHP) integration methods involving trigeneration systems for industrial plants have been much less emphasised. This paper proposes a novel methodology for developing an insight-based numerical Pinch Analysis technique to simultaneously target the minimum cooling, heating and power requirements for a total site energy system. It enables the design of an integrated centralised trigeneration system involving several industrial sites generating the same utilities. The new method is called the Trigeneration System Cascade Analysis (TriGenSCA). The procedure for TriGenSCA involves data extraction, constructions of a Problem Table Algorithm (PTA), Multiple Utility Problem Table Algorithm (MU PTA), Total Site Problem Table Algorithm (TS PTA) and estimation of energy sources by a trigeneration system followed by construction of TriGenSCA, Trigeneration Storage Cascade Table (TriGenSCT) and construction of a Total Site Utility Distribution (TSUD) Table. The TriGenSCA tool is vital for users to determine the optimal size of utilities for generating power, heating and cooling in a trigeneration power plant. Based on the case study, the base fuel source for power, heating and cooling is nuclear energy with a demand load of 72 GWh/d supplied by 10.8 t of Uranium-235. Comparison between conventional PWR producing power, heating and cooling seperately, and trigeneration PWR system with and without integration have been made. The results prove that PWR as a trigeneration system is the most cost-effective, enabling 28% and 17% energy savings as compared to conventional PWR producing power, heating and cooling separately.

The progressive rising of high living standards and populations’ growth has led to increasing energy demands. This has led to the energy shortage gap in both developing and developed countries. Government is developing new technology to increase the thermal efficiency of existing power systems. Trigeneration is one of the innovations that can increase the performance of power systems by reusing waste energy for heating and cooling applications. Pinch Analysis (PA) is a methodology that has been commonly applied for more than 40 years to design and optimum configurations of various resource networks. Previous studies have been performed optimisation of trigeneration system in a Total Site system based on the PA method called Trigeneration System Cascade Analysis (TriGenSCA). However, the previous study does not consider the performance of the trigeneration system through overall sensitivity analysis of Total Site system. Overall sensitivity analysis of the Total Site system that includes industrial plant’s maintenance shutdown and production changes affected the performance of the centralized trigeneration system to generate energy to be supplied to the demands. Through this analysis, the size of the trigeneration system and back-up system can be estimated taking into consideration data fluctuations probability. The methodology has been tested on the centralized nuclear trigeneration system in a Total Site system considering four industrial plants as a case study, leading to extra 3.1 MW of Low-Pressure Steam (LPS) and 7.15 MW of Hot Water (HW) are needed from the back-up system if Plant B is shut down as well as extra of 82.4 MW of HW is needed by the back-up system if Plant C is shut down. The size of the boiler and condensate system, hence, need to be improved to overcome the deficit energy as the Plants B and C are shut down.

Depletion and rising prices of fossil fuel, as well as environmental pollution, have led the world to find energy-efficient technologies such as improvement of efficiency of the current energy systems. The thermal efficiency of the current systems can be improved from 30 – 40 % to 80 – 90% through implementation of trigeneration system. Trigeneration is a system which can improve the efficiency of the current energy systems by reusing the waste heat to produce power, heating and cooling from a single fuel. Pinch Analysis is a methodology which enables users to optimize the energy, water and other resources. Trigeneration System Cascade Analysis (TriGenSCA) is developed to minimize power, heating and cooling energies as well as obtain optimal sizing of the trigeneration system. In the previous TriGenSCA, transmission energy losses which contribute significantly to the final amount of energy arrived at the demand was not considered. This leads to an optimistic target for energy reduction. The objective of this work is to develop an extension of numerical insight-based Pinch Analysis methodology for optimal trigeneration system which considers energy losses in the transmission lines and storage systems. There are three major steps on developing TriGenSCA, which are data extraction, construction of TriGenSCA with transmission and storage energy losses, and comparison of TriGenSCA with and without transmission energy losses consideration. The transmission energy losses are included in the TriGenSCA where energy depleted due to the transportation of energy from the trigeneration system to the demand load, separated by 10 km of distances. Aluminium cable steel, carbon and stainless steel pipelines are used to transfer power and thermal energies to the demands. Based on the case study, the energy difference of TriGenSCA with and without transmission energy losses is 76.83 MWh/d. This shows huge energy is lost due to the transmission process. The development of this systematic methodology can give benefits to engineers, designers and power plant managers in order to determine the exact value of utility and thus, perform the optimal design of a trigeneration system.

Conventional nuclear power reactors convert between 30 – 35 % only of the total energy input into electricity while the remaining was wasted. The waste heat is sometimes used for desalination processes while the remaining heat is transferred to a cooling media or lost to the surrounding. Therefore, heat from nuclear reactor can be used to produce heat and power, as well as for cooling in a trigeneration system. This paper presents the Trigeneration System Cascade Analysis (TriGenSCA) for an optimal Pressurised Water Reactor (PWR) design. The TriGenSCA framework allows engineers to determine an optimum utility generation system size and estimate the required amount of external utilities. The analysis includes data extraction, cascade analysis for size estimation and calculation of the new trigeneration system size. The technique also enables users to determine accurate results for energy minimisation based on demand fluctuations. Application of the framework on a case study presented on this paper demonstrates the trigeneration PWR system successfully saved energy of 328GWh/y (97 %).