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Abstract In this paper, we estimate the energy efficiency of educational buildings with the case study of buildings in City University of Hong Kong by constructing an energy demand stochastic frontier model. The model is estimated by using the university statistical data from 2011 to 2015. For the consistent frequency of data among the variables, we have adopted the quadratic-match sum method to convert annual university report data into a monthly dataset. Our result shows the average energy efficiency is 0.87, implying that 13% of total energy consumption can be saved. We then calculate how much of the energy saving potential has been achieved by constructing the performance score, which increases from 0.08 to 0.17. It implies that the campus performs more efficiently in saving energy over time. We further develop econometric decomposition analysis based on the energy demand frontier model to identify the factors affecting energy consumption. It suggests that research activities account for a large share of overall energy consumption. Analysis on energy end-use shows university should improve efficiency in lab instrument as it is least efficient among the four usages. We expect this paper can provide the fundamental and methodological guideline for university-scale energy efficiency estimation.

Extreme weather events, many of which are climate change related, are occurring with increasing frequency and intensity and causing catastrophic outages, reminding the need to enhance the resilience of power systems. This paper proposes a proactive operation strategy to enhance system resilience during an unfolding extreme event. The uncertain sequential transition of system states driven by the evolution of extreme events is modeled as a Markov process. At each decision epoch, the system topology is used to construct a Markov state. Transition probabilities are evaluated according to failure rates caused by extreme events. For each state, a recursive value function, including a current cost and a future cost, is established with operation constraints and intertemporal constraints. An optimal strategy is established by optimizing the recursive model, which is transformed into a mixed integer linear programming by using the linear scalarization method, with the probability of each state as the weight of each objective. The IEEE 30-bus system, the IEEE 118-bus system, and a realistic provincial power grid are used to validate the proposed method. The results demonstrate that the proposed proactive operation strategies can reduce the loss of load due to the development of extreme events.

Abstract Power-to-gas (PtG), as a promising technology proposed to store surplus renewable energy (RE), can hardly be commercialized for its low profitability. In this paper, three approaches are proposed in this paper to enhance the profitability of the PtG. Firstly, a cooperative union containing PtG is proposed and its sustainability analysis is undertaken based on Shapley Value method. Secondly, the PtG reaction heat, as an essential by-product of PtG which is valuable and therefore requires further study, is fully exploited for district heating in the operation of regional integrated energy system, which is solved by an improved SOCP method. Thirdly, a symbiosis cooperation mode is designed for wind power and PtG to enhance the benefit of PtG through optimization-based trading strategy, which is a MINLP model and solved by Big-M method. The results show that the daily profit of PtG is significantly increased with the cooperative union as the symbiosis cooperation mode can produce a 15.1% profit lift, meanwhile, exploitation of reaction heat can produce an 8.6% profit lift. Finally, our study reveals the conflict of interest between wind power and the cogeneration. A sensitivity study on the proportion of reaction heat used for district heating is performed to verify the mutually beneficial relation between PtG and the cogeneration. The findings of this paper can guide the commercialization of PtG.

AbstractInvestment cost associated to the generation of renewable energy such as wind and solar is generally estimated to be higher. As the wind and solar energy generation do not require any fuel, the marginal cost of electricity generation through renewable energy technologies is very low. Therefore, in the long run, the prices are expected to get reduced, once investment cost is recovered; whereas, in the short run, the expected energy price of electricity increases.However, the final electricity price depends on several factors such as distribution cost, operating cost, storage cost (if any), load factor, and cost associated to switching of technology for electricity generation through total energy mix. In case of solar and wind energy generation, the technologies have grid priorities, but solar and wind are highly sensitive to weather conditions. Therefore, to make the system efficient, an energy system also depends on coal fired plant, gas fired plants, nuclear plants, biomass, hydro, etc. for meeting the energy supply needs. Based on overall capacities, investment costs, energy imports and fuel prices, the final electricity prices are decided. With the current trends in advancement of technologies, and priority for one technology over the other, the prices can still fluctuate in the future.In the current energy literature, methods available for price forecasting followed the modelling approaches that use range of variables for forecasting the possible scenarios. These scenarios and forecasting might affect an investment decisions of investors. However, the challenging future scenario in European energy mix addresses the issue of falling electricity price while the renewable energy technologies getting cheaper; which tends to freeze further investments, unless sufficient government support is available.The current study aims to explore the various economic forecasting methods presented in the literature for the purpose of energy price modelling, in different contexts, such as geographies, demand, supply, marketing, strategy, etc. The results suggest a large variation in the methodologies being used by scientists to address the issues in different countries. A wide range of variable selection approach has been observed. Our study suggests that the current market has not researched well on long run forecasting methods. This study also aims to present some thoughts on energy marketing in the context of emerging economies, such as India for the energy policy framing.

AbstractIn the previous study papers the change of the total energy intensity is decomposed to the structure factor and the efficiency factor, not considering the household energy factor, because GDP are not made only by household energy. Household energy is about ten percents in the total energy consumption and the household energy of unit GDP are always being decreased. In this paper the change of the total energy intensity is decomposed to the structure adjustment factor, the efficiency factor and the household energy factor. The result of decomposition shows the efficiency factor contribute most to the reduction of total energy intensity from 1985 to 2007, the household energy factor the next, and structure adjustment factor the last. The result of decomposition also explains the causation of the abnormal ascending of total energy intensity from 2002 to 2005.

Abstract Low efficiency of heat conduction and absorption is a key problem to restrict the application of phase change materials (PCMs). Foam metals, which work as random heat transfer networks, are often used to improve the thermal conductivity of PCMs. But further improvements are still required in engineering. Interestingly, random micro-channels also widely exist in natural heat and mass transfer systems (e.g., minor veins of leaves and blood capillaries) that always appear with ordered branching networks of macro-channels. But the ordered branching networks, which perform as efficient transfer networks, are rare in metal-foam-enhanced PCMs. Therefore, this work enhances the PCMs’ heat-absorption efficiency by constructing heat transfer networks mimicking leaf veins. Given the gap that there lack trusted design criteria to design the heat transfer networks, we propose an innovative optimization criterion mimicking the generating process of leaf veins. Combine the criterion with an original flexibility-oriented optimization framework, a generating design method is established. The optimization performance is discussed in point-area PCM structures. Compared with the metal-foam-enhanced PCM plate, the heat-absorption efficiency of the generating-based PCM plate is increased to 196.67% in concentrating heat from the PCMs, and the heat-absorption efficiency is also enhanced for more than 3.79 times in dispersing heat to the PCMs. With these improvements, the proposed method is applied in cooling high-power electronic devices which solves the overheating problem and prolongs the working time to 400.00%. Further applications can be expended to PCM-cooling systems, heat pump, collection and output of solar energy and waste heat, etc.

Abstract The aim of this paper is to present the critical verification for TRX and BAPL benchmarks between the ENDF/B-VIII.0 and ENDF/B-VII.0 library. Using DRAGON5.0.6 code with 281-group WIMS-D and DRAG library, the integral parameters for TRX and BAPL benchmarks are compared to the Monte-Carlo code and experimental values. For the verification of DRAGON code, the influence of tracking method, resonance self-shielding method, and leakage model are investigated in this paper. The results indicated that the combination methods of collision probability method, equivalence theory, and P1 leakage model have better accuracy in TRX and BAPL benchmarks. For the comparison of ENDF/B-VII.0 and ENDF/B-VIII.0 library, the difference of integral parameters is small between the ENDF/B-VII.0 and ENDF/B-VIII.0 library. The relative error of ρ28 and δ25 is less than 1%. However, the accuracy of δ25 and C* is underestimated by about 1.0%∼1.5% in ENDF/B-VIII.0 library. It means that the fission cross section for U-235 is overestimated in ENDF/B-VIII.0 library and the 2-group cross section comparison is consistent with this tendency. Therefore, the absorption cross section for whole region is increased in thermal energy group, which finally leads to the keff and kinf decreased in ENDF/B-VIII.0 library. Compared with the experimental values in TRX and BAPL cases, the integral parameters in ENDF/B-VIII.0 are more accurate than the ENDF/B-VII.0 library.

Carbon neutrality innovation technologies are a leading research topic in sustainable development. Among these, anaerobic digestion is considered as a better choice for biowaste utilization. However, large amounts of produced biogas slurry hamper the widespread application of anaerobic digestion. The hydrothermal process is regarded as favorable to treat biogas slurry. The effects of inorganic and organic matter in processed water from the hydrothermal-treated biogas slurry were investigated in our research. The changes in inorganic elements such as P, Ca, Mg, Cu, and Zn were detected at different reaction temperatures (90, 120, 150, 180, 210, and 240 ℃) and acid catalytic conditions (0.5, 1, 2, 3, 4, 4.5, and 5 mL 5 M HCl). The changes in organic matter were analyzed using three-dimensional excitation emission matrix fluorescence spectroscopy. With the increase in the hydrothermal reaction temperatures, the quantity of total and inorganic P and the concentration of Ca initially increased and then decreased, concentration of Mg remained constant, while the concentration of Zn and Cu showed a trend of initial decrease and then increase, and the macromolecular organic matter was hydrolyzed into small, soluble molecular organic matter. With the increase in HCl, the amount of released total and inorganic P and concentrations of Ca, Mg, Zn, and Cu increased, and the macromolecular organic matter was hydrolyzed into small molecular organic matter. The hydroponic testing indicated that the processed water has a positive effect on the growth of maize. These results provide critical findings on the reuse of biogas slurry, which is useful for biowaste management and improves carbon neutrality strategy.