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Insight on how industrial's practices and commitments could affect better energy-efficient buildings implementation is still limited despite the emerging concerns over the demand to minimize energy consumption. This study aims to fill the gap by investigating industry behaviours and practices and recommending holistic energy-efficient management strategies in Malaysia. The study used an explanatory sequential mixed approach comprising 4 case studies of conventional buildings, 72 building stakeholders submitted a survey questionnaire, and 7 experts were interviewed to enable triangulation of information. The analysis revealed that current energy management strategies are based on low-hanging fruit measures. The results also suggest that financial, managerial, and knowledge limitations are the primary constraints to effectual energy-saving methods. This paper demonstrates three-tier intervention strategies in education, policy, and technology towards accelerating industry transition in achieving best practices in energy-efficient buildings. The outcomes of this study may advantage building interested parties in addressing relevant barriers to energy-efficient execution and designing effective efforts to encourage conventional building for the building advancement in Malaysia. This research offers findings by delivering greater practical perspectives on the extent of industry practises and behaviours regarding energy-efficient building implementation, including by presenting energy management approaches for benchmarks in energy-efficient buildings in Malaysia. • Financial, managerial and knowledge are the constraints to effectual energy-saving. • Intervention in education, policy and technology are the strategies for energy-saving. • Low-hanging fruit measures effective for simple behavioural changes. [ABSTRACT FROM AUTHOR]

As the energy demand keeps growing with the world's increasing population, concerns have arisen about the carbon emissions that contribute to critical environmental issues. These environmental concerns drive many nations to commit themselves in pursuing sustainable energy resources. Different process integration techniques have been developed to achieve a viable energy planning sector. In reference to the literature review, the use of time-sliced based models in optimization problems is still sparse. Hence, this paper aims to develop a time-sliced based optimization model that can be integrated into energy integration models. With that, a multi-period pinch-based methodology (targeting, scheduling, and optimization) for electric power systems with the hybridization of renewables and fossil-based energy is proposed. The prospective framework is designed to meet the emissions limit, fulfil energy demand, and minimize the electricity bill. An illustrative case study in Malaysia incorporated with an actual billing system is used to demonstrate the effectiveness of the proposed framework. The results show that it is capable of reducing the total electricity bill by 35% and achieving a 71% reduction of emissions by using solar PV as the renewables. • Three-step multi-period pinch-based methodology for energy planning is presented. • The model incorporates an actual billing system. • Time-sliced based optimization model is developed in the proposed framework. • Optimal emission reduction ratio and storage size are identified as 0.71 and 236 kWh. • The total electricity bill can be further reduced by 35%. [ABSTRACT FROM AUTHOR]

The biomass energy sector in most developing countries is not well established due to the high cost of implementation and lack of quantitative planning tools. This paper addresses this issue by presenting a quantitative planning tool used to plan and optimise biomass supply chains based on carbon reduction targets. The tool proposed in this work centres on three important stages: Carbon Emission Pinch Analysis (CEPA), mathematical optimisation, and multi-stakeholder analysis. CEPA is used to determine the minimum amount of biomass to achieve carbon reductions. Then, mathematical optimisation is used to optimise the biomass supply chain based on the carbon reduction target. The optimisation step considers the use of new biomass power plants and co-firing existing power plants. Following this, the importance of power plants within the optimal biomass supply chain is identified using a multi-stakeholder analysis method known as Shapley-Shubik power index. Shapley-Shubik power index is used to determine the level of power held by each power plant in the biomass supply chain based on the number of times each stakeholder become pivotal in achieving several quotas (i.e., power purchase agreement). A case study comprising a biomass supply chain in Malaysia is solved to demonstrate the presented tool. The case study analyses several scenarios in which the biomass supply chain can be deployed. Case study results indicated that co-firing existing power plants did indeed minimise capital and operating expenditure. Conversely, the cost of transporting biomass may be high depending on the location of these plants. Boiler systems were the most chosen due to their high biomass-to-power conversion rates. The multi-stakeholder analysis determined that a power plant with higher power output, cheaper costs, and superior biomass-to-power conversion rate often appears as the more significant player in the supply chain. • A methodology is developed for optimal biomass supply chain planning based on carbon reduction targets. • Shapley-Shubik power index is used to determine pivotal players in optimal biomass supply chain. • Co-firing opportunities are considered to achieve targets in a cost-effective manner. • Results show co-firing schemes were more preferred compared to new biomass plants due to lower cost. • Plants with higher efficiency and lower cost tend to become pivotal players in optimal supply chains. [ABSTRACT FROM AUTHOR]

Industry and agriculture in Malaysia are the main contributors to economic growth and employment. These sectors also play an important role in Malaysia's total exports. The question then is whether technological innovation, sectoral output, and exports growth have had a real impact on these two sectors, which are very important for policy-making. This paper attempts to empirically identify such relations using econometric methods, including an autoregressive distributed lag (ARDL) bounds testing method and a dynamic ordinary least squares (DOLS) during 1978–2018. The results confirmed that overall long-run economic growth is the main contributor to the increase in energy consumption with a greater magnitude than in the short-run. In the long-run, an increase of 1% in economic growth leads to an increase of 4.6% and 1.1% in energy demand in agriculture and industrial sectors, respectively. Exports are the second largest contributor to energy demand in the overall economy and the agriculture sector. Finally, the technological innovation that enhances energy efficiency is only effective in reducing energy consumption in the industrial sector, which ultimately reduces emissions. [Display omitted] • It the relationships between energy consumption and crude oil price is investigated. • Technological innovation have negative relationships with energy consumption. • Economic growth is the main factor to energy consumption in the short- and long-runs. • The magnitude of long-run economic growth effects are greater than the short-run. • Agriculture export is the main contributor to energy consumption in the short-run. [ABSTRACT FROM AUTHOR]