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Abstract The urge to increase renewable energy penetration into the power supply mix has been frequently highlighted in response to climate change. South Korea was analyzed as a case study for which the government has shown motivation to increase renewable energy penetration. Herein, a hybrid renewable energy system (HRES) including solar and wind energies were selected due to their relatively stable and mature technology. In addition, Power-to-X has been incorporated to cover other renewable energy options such as hydrogen and synthetic natural gas (SNG). Therefore, an approach of forecasting the weather characteristics and demand loading over a relatively long timeframe was implemented via deep learning techniques (LSTM and GRU) and statistical approaches (Fbprophet and SARIMA), respectively. A deployment strategy incorporating HRES and Power-to-X is then proposed in correspondence to the forecasted results of the 15 regions considered in this study. An extension of this, the reliability of the designed system is further assessed based on the probability of the demand losses with the aid of Monte-Carlo simulation. With the proposed deployment strategy, a total annual cost of 9.88 × 1011 $/year and a greenhouse gas reduction of 1.24 × 106 tons/year are expected for a 35% renewable energy penetration. However, only SNG shows relatively competitive cost (at 23.20 $/m3 SNG), whereas the average costs of electricity (0.133 $/kWh) and hydrogen (7.784 $/kg H2) across the regions are yet to be competitive compared to the current market prices. Nonetheless, the priority of deployment across regions has been identified via TOPSIS.

Abstract Based on the periodic solution of the heat conduction equation, an analysis has been developed to study the thermal performance of a simple domestic solar water-heating system consisting of a thermal-trap solar-energy collector, connected to a water tank. To study the effects of typical parameters such as the thickness of the trap material and the presence/absence of the glass cover on the thermal performance, numerical calculations have been performed to correspond to the daily variations of the ambient temperature and solar intensity on a typical cold winter day in New Delhi.

As one of the three high-energy consumption sectors (industry, building, and transportation) in China, the transport sector faced a devastating resource and environment challenge. The transport sector was reportedly responsible for about 15.9% of the country’s total final energy consumption in 2008. This paper investigates the energy consumption and efficiency of China’s transport sector from 2003 to 2009. The transport energy data of 30 China administrative regions were divided into “three-belts” (Eastern, Western, and Central areas), and the corresponding turnovers were reported and analyzed using an index decomposition analysis (Logarithmic Mean Divisia Index). The energy data and turnover of the transport sector indicated that the high growth rate of turnover results is attributed to the high growth rate of diesel, assuming that diesel is the major fuel for freight transport. The growth of diesel is the main contributor to the overall growth of energy consumption. The growth rate of gasoline has become minimal since 2006. Since 2005, all three-belt areas, with regard to the effectiveness of energy conservation policies, have continuously improved their energy efficiencies based on the results of decomposition analysis. The energy intensity effect shows that the energy conservation and efficiency policies were more effective in the Central and Western areas than that in the Eastern area. On the other hand, the regional shift effect indicates that the policies favor to the Eastern area since only its regional shift effect contributes energy savings since 2008. The energy-mix effect is insignificant, which indicates that it is not necessary to conduct CO2 emission decomposition analysis due to the redundant observations. At last, the activity effect dominates the energy consumption increase (98.05% of the accumulated total energy increase) from 2003 to 2009, which is consistent with the rapid development of transportation in China. That is, the policies in the transport sector mainly focused on the economic development but the energy efficiencies in the study period.

Abstract Reducing a building’s energy consumption and providing better indoor environmental quality (IEQ) are the two major issues that building professionals are facing all over the world. It is not easy, however, to simultaneously address both issues. Therefore, this study aimed to establish the optimal occupant behavior that can simultaneously reduce total energy consumption and improve the IEQ, using an energy simulation and optimization tool. This study also developed an integrated IEQ score by combining three different IEQ indices (i.e., thermal comfort, indoor air quality (IAQ), and visual comfort) for building users to easily understand the IEQ condition. To analyze the effects of occupant behavior by region, the education facility was selected as the target facility, and five target regions were selected considering the Koppen climate classification system and the C40 Cities Climate Leadership Group. Finally, a total of 5 × 1.01 × 1022 occupant behavior combinations can be generated in the five target regions. As a result, among the four target variables (i.e., total energy consumption, thermal comfort, IAQ, and visual comfort), the total energy consumption of the optimal solution was found to have changed most dramatically compared to that of the basic condition in terms of percentage (94.7%), due to its strong correlation with the overall occupant behavior (the highest correlation coefficient: 0.879). Therefore, it is shown that occupant behavior has more influence on the total energy consumption than on the three IEQ indices. Among the three IEQ indices, the IAQ of the optimal solution decreased most significantly compared to that of the basic condition (the highest reduction ratio: 4.04% in Ulsan), which indicates that the IAQ has more influences on the integrated IEQ score than thermal and visual comfort. The facility manager and the building user can operate the building for reducing total energy consumption and improving the IEQ considering occupant behavior, which can be used as the building management guideline in various regions.

Abstract The deep decarbonisation of the power sector coupled with electrification of end-use sectors will be crucial towards a carbon neutral economy, as required to achieve the Paris Agreement's goal. Several studies have highlighted the relevance of electrification under deep decarbonisation. However, previous work does not explore what would be the major shifts towards electrification, i.e., in what economic activities it will likely occur and when up to 2050 considering gradually stricter GHG emissions constraints. This is of upmost relevance since relatively small variations in emission caps may trigger substantial modifications in specific components of the energy system, namely the shift for the electrification of a particular energy end-use, with impacts on the power sector’s portfolio. In this paper, we analyse the extension of the electrification of the energy system as a cost-effective strategy for deep decarbonisation. We set a large number of increasingly stringent mitigation caps to assess: (i) the degree of electrification of different energy end-uses across all economic activities, (ii) the impact in power sector portfolio and costs and (iii) investment needs. The novelty of this paper relies on the anticipation of electrification of activities traditionally supplied by non-electricity energy carriers, by exploring when and how such transformation may occur in the future, and how much it would cost. We assess the case of Portugal till 2050 by using the TIMES_PT model to generate 50 increasingly stricter decarbonisation scenarios. In the long term, incremental changes (+1%) in more aggressive decarbonisation targets (beyond −70% reduction) induce substantial increase in the share of electrification growth rates. Electric private vehicles, electricity-based steam and heat production in ceramic industrial sector and heat pumps in buildings are the most cost-effective electric technologies. We found that a decarbonisation up to near −80% of 1990′s levels of the Portuguese energy system does not have a significant impact on the power sector unit costs, and does not surpass historic values for some years. However, it should be noted that incremental changes (+1%) in more aggressive decarbonisation targets may increase sharply electricity costs in 2050 (+9%). Thus, focusing in only few scenarios may narrow the role of electrification (or other mitigation options) and its associated costs for deep decarbonisation. This paper allows researchers, planners and decision makers to enhance awareness regarding the relevance and cost-effectiveness of electrification under decarbonisation, namely its feasibility and affordability, providing fruitful insights.

Abstract Carbon capture and storage (CCS) technology is an important option in the portfolio of emission mitigation solutions in scenarios that lead to deep reductions in greenhouse gas (GHG) emissions. We focus on CCS application in hard-to-abate sectors (cement industry, iron and steel, chemicals) and introduce industrial CCS options into the MIT Economic Projection and Policy Analysis (EPPA) model, a global multi-region multi-sector energy-economic model that provides a basis for the analysis of long-term energy deployment. We use the EPPA model to explore the potential for industrial CCS in different parts of the world, under the assumptions that CCS is the only mitigation option for deep GHG emission reductions in industry and that negative emission options are not available for other sectors of the economy. We evaluate CCS deployment in a scenario that limits the increase in average global surface temperature to 2 °C above preindustrial levels. When industrial CCS is not available, global costs of reaching the target are higher by 12% in 2075 and 71% in 2100 relative to the cost of achieving the policy with CCS. Overall, industrial CCS enables continued growth in the use of energy-intensive goods along with large reductions in global and sectoral emissions. We find that in scenarios with stringent climate policy, CCS in the industry sector is a key mitigation option, and our approach provides a path to projecting the deployment of industrial CCS across industries and regions.

Abstract In recent years, distributed energy systems (DESs) have been recognized as a promising option for sustainable development of future energy systems, and their application has increased rapidly with supportive policies and financial incentives. With growing concerns on global warming and depletion of fossil fuels, design optimization of DESs through economic assessments for short-run benefits only is not sufficient, while application of exergy principles can improve the efficiency in energy resource use for long-run sustainability of energy supply. The innovation of this paper is to investigate exergy in DES design to attain rational use of energy resources including renewables by considering energy qualities of supply and demand. By using low-temperature sources for low-quality thermal demand, the waste of high-quality energy can be reduced, and the overall exergy efficiency can be increased. The goal of the design optimization problem is to determine types, numbers and sizes of energy devices in DESs to reduce the total annual cost and increase the overall exergy efficiency. Based on a pre-established DES superstructure with multiple energy devices such as combined heat and power and PV, a multi-objective linear problem is formulated. In modeling of energy devices, the novelty is that the entire available size ranges and the variation of their efficiencies, capital and operation and maintenance costs with sizes are considered. The operation of energy devices is modeled based on previous work on DES operation optimization. By minimizing a weighted sum of the total annual cost and primary exergy input, the problem is solved by branch-and-cut. Numerical results show that the Pareto frontier provides good balancing solutions for planners based on economic and sustainability priorities. The total annual cost and primary exergy input of DESs with optimized configurations are reduced by 21–36% as compared with conventional energy supply systems, where grid power is used for the electricity demand, and gas-fired boilers and electric chillers fed by grid power for thermal demand. A sensitivity analysis is also carried out to analyze the influence of energy prices and energy demand variation on the optimized DES configurations.

The design of transition pathways for sustainable electricity systems with high penetrations of renewable energy sources requires the use of energy modeling tools that are able to account for two key aspects: the evolution of fossil fuels and technology prices, and the natural dynamics of renewable resources. However, the modeling methodologies most currently used focus on only one of these two aspects, which hinders their suitability for performing long-term analysis with high penetrations of renewable energy sources. This paper presents a modeling framework that is able to optimize the investment in new renewable generation capacity on the long-term while taking into account the hourly dynamics of electricity supply and demand. The framework combines two of the most used energy planning tools, each able to account for one of the aspects of the modeling of energy systems. The framework was applied to continental Portugal for the time period of 2005–2050, in order to identify optimal investment plans in new renewable and fossil generation capacity with the goal of achieving significant CO2 emissions reduction, under different scenarios. The results show that the inclusion of dynamics in the modeling methodology can help avoid overinvestment and reduce the excess of electricity from renewable energy sources that cannot be used by the system. These results can have a significant impact on the design of a sustainable electricity system and may lead to a diversification of the energy sources used.

This study aims to develop a novel design method for reducing the energy consumption and CO2 emissions of local energy systems, simultaneously considering the recovery of industrial waste heat, and effectively dealing with the non-continuous nature of energy usage and heat recovery. A multi-period concept has been adopted for characterizing the change of heat demand and associated heat recovery in local energy systems which is used for targeting of the minimum energy consumption. In addition, techno-economic analysis is used to provide design guidelines for better heat integration. This design methodology also incorporates the impacts of heat storage and part-load performance of energy production equipment. Opportunities for utilization of low grade heat in process industries have been systematically considered for the minimization of energy generation in local energy systems together with the evaluation of the economic feasibility of such systems for integration of industrial low grade heat with local energy systems. Case studies are used to demonstrate the applicability and practicality of the heat integration methodology developed in this work, and to illustrate how a holistic approach can improve the overall energy efficiency of local energy systems.