• Energy Research
• engineering and technology close
• 7. Clean energy close
• CN close
• GB close
• AU close
• NL close

Solar PV and battery storage technologies are known to provide savings to customers in the form of reduced electricity charges. Currently, these savings are only determined for the volume component (kWh) and not the demand component (kW or kVA). As interest grows in commercial solar PV and battery storage installations, the need to predict demand charge reductions is great. The aim of this research is to determine, with accuracy and reliability, the ability of solar PV and battery storage technologies in reducing demand charges. Results have shown that when simulated against a commercial-scale electricity consumption profile solar PV was able to reduce the maximum demand across five electricity networks in Australia by 0.05–1.51%. When coupled with a 12 kWh battery storage an additional 1.31–2.02% reduction was experienced. Battery utilisation strategy was shown to be critical in yielding greater demand reduction from the battery storage. Notably, it was shown that in the Ergon Energy electricity network, battery storage was able to supply demand at 34% lower cost ($/kW) than the network was able to. The results detail the first instance of demand reduction evaluation of solar PV coupled with battery storage, focusing on physical and financial outcomes in an Australian context.

A metafrontier slack-based efficiency measure is presented to measure environmental efficiency for various regions in China. The objective of the new approach is to investigate the change of environmental efficiency while incorporating group heterogeneities and all variable slack and environmental pollutants into environmental efficiency analysis. Global production technology is used to improve the discriminating power of environmental efficiency measurement. An empirical analysis of regional environmental efficiency is carried out incorporating sulfur dioxide emissions and the chemical oxygen demand (COD) of China’s regions from 2000–2011. Results indicate that excessive emissions pollution is the major cause of environmental inefficiency. Most of the regions return environmental efficiency values. Significant regional technology gaps in environmental efficiency are found between the east, central, and west areas. Finally, some policy implications are presented from the empirical results.

Aiming at the energy multivariate heterogeneity of thermal system and natural gas system, a novel optimization model of integrated energy system considering thermal inertia and gas inertia is proposed. First, the dynamic characteristics of the thermal system in the integrated energy system are studied, and the inertia model of the heat network pipeline and thermal building is established. Second, the characteristics of natural gas pipeline network storage are studied, and the natural gas storage and pressure energy generation models are established. Then, the optimization objective of the minimum integrated operating cost of the integrated energy system is established, and the YALMIP solver is used to solve it. Finally, a numerical example is introduced to analyze the operating cost of the integrated energy system in different scenarios, and it is verified that the integrated energy system optimization model considering the inertia of the thermal and gas proposed in this paper can effectively improve the system regulation capability and reduce the system operating cost.

AbstractThis paper is about to quantify the effect of China's urbanization on greenhouse gas (GHG) emissions by separating the part driven by the economic growth from the whole effect. In order to be accurate to estimate unknown parameters, this paper follows the method of Blanchard & Quah (1989), in which identifying conditions are set by assuming some shocks have no long-term effect on corresponding explained variables. We conclude that 1) Urbanization shock has an inverted hump-shaped effect on GHG emissions, in other words, nowadays the process of China's urbanization has been accompanied with saving energy and reducing emissions; 2) The growth rate of GHG emissions, owning to the GDP shock, can be raised by almost 1.53% annually and the urbanization level approximately contributes to 18% of the change of CO2 emissions based on empirical results; 3) China's emission reductions, in the short run, are actualy in expense of decreasing economic growth and delaying the p rocess of its urbanization.

In recent years, Smart Grid was introduced to achieve an environmentally-friendly, adequate, secure and fossil fuel-independent power system. The large scale smart grid studies require accurate state estimation to obtain an acceptable adequacy level. There exist some challenges regarding anomalous power flow studies which motivate grid operators to utilize robust and accurate estimation methods. Therefore, power system state estimators play a pivotal role in real-time grid management. In this paper, a sequential linear minimum mean square error (LMMSE) estimator is utilized to solve the DC power flow problem. First, we introduce the classic linear estimator model which assumes that to-be-estimated parameter values are unknown but deterministic. The LMMSE estimator will be discussed which treats the to-be-estimated parameter as a random variable with a known prior probability density function (pdf). We evaluate the accuracy of the LMMSE estimator by comparing it with maximum likelihood estimator (MLE). Finally, the effect of covariance matrix topology will be studied by defining three scenarios with different noise covariance matrices.

The current crude phenol separation process is featured by the conventional distillation columns and its close boiling range between the components significantly increases the energy consumption. Compared to the conventional heat integrated technology, the advanced heat integrated technology has more or less advantage of simple structure, higher energy efficiency and economic benefit in some specific separation schemes but is lack of the application in process transformation. It has the potential to be a high-energy-efficient way to improve the energy efficiency of the crude phenol separation process. An improved middle vapor recompression distillation column (IMVRC) was proposed on the basis of the conventional middle vapor recompression distillation column (MVRC), with more consideration of operating pressure set and separated stage. The vapor recompression distillation column (VRC) and MVRC are used as the competitive configurations to estimate the performance of IMVRC for separating three different boiling range mixtures. Besides, the crude phenol process is established as two steam-driven and three electrical-driven processes with the conventional and advanced heat integrated technologies used. Furthermore, the flexibility of IMVRC for the process design is investigated and the extended structure of IMVRC (E-IMVRC) for the crude phenol separation process is achieved. The results show the IMVRC has the preferable energy and total annual cost (TAC) benefits in all the different boiling range mixtures. And the different separated stage makes the distinct structure of IMVRC with different cooling and heating duty arrangement, which benefits the potential heat integrated flexibility in the process design. Consequently, the electrical-driven processes have the significant TAC saving than the steam-driven processes. Moreover, the E-IMVRC performs best in all the 4E analysis.

AbstractWith the increasing proportion of natural gas in power generation, natural gas network and electricity network are closely coupled. Therefore, planning of any individual system regardless of such interdependence will increase the total cost of the whole combined systems. Therefore, a multi-objective optimization model for the combined gas and electricity network planning is presented in this work. To be specific, the objectives of the proposed model are to minimize both investment cost and production cost of the combined system while taking into account the N−1 network security criterion. Moreover, the stochastic nature of wind power generation is addressed in the proposed model. Consequently, it leads to a mixed integer non-linear, multi-objective, stochastic programming problem. To solve this complex model, the Elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to capture the optimal Pareto front, wherein the Primal–Dual Interior-Point (PDIP) method combined with the point-estimate method is adopted to evaluate the objective functions. In addition, decision makers can use a fuzzy decision making approach based on their preference to select the final optimal solution from the optimal Pareto front. The effectiveness of the proposed model and method are validated on a modified IEEE 24-bus electricity network integrated with a 15-node natural gas system as well as a real-world system of Hainan province.

Abstract The development and application of a standard methodology for evaluating the energy and carbon budgets of biofuel production systems is described, with emphasis on wood fuel production from short rotation coppice. Five major tasks were involved: definition of the system boundary; estimation of energy benefits; estimation of carbon sequestration; estimation of energy costs; estimation of carbon emissions. Calculation of overall energy and carbon budgets required a set of ‘standard’ assumptions about practices and resultant energy inputs to be made. These standard assumptions accounted for all activities involved in production and delivery of biofuel within the immediate vicinity of the farm ( 3.2 km ). The energy ratio, that is the ratio of energy produced to energy consumed by the biofuel producing system, was estimated to be much greater than 1, typically around 30. This energy ratio proved to be very sensitive to assumptions about crop management and wood processing, as well as associated energy inputs, varying from 20 to 64 when model input assumptions were varied between extremes. The carbon emissions coefficient exhibited similar sensitivity to input assumptions. The gross non-renewable energy requirement, that is the total consumption of non-renewable energy associated with the direct consumption of 1 MJ of energy in the form of wood fuel, was estimated to be 0.035 MJ MJ −1 . The carbon emissions coefficient, that is the carbon emitted in producing 1 MJ of energy in the form of wood from short rotation coppice, was estimated to be 0.0013 kgC MJ −1 . Further research is needed to validate input assumptions and to estimate budgets for complete, practical, energy generation systems.

Abstract Photovoltaic-thermal (PVT) technology integrates PV and conventional solar thermal collectors. Here theoretical modeling and experiments were conducted to evaluate the performance of PVT collectors in series. Analytical expressions for N collectors in series were derived using basic energy balance equations and computer-based thermal models. We analyzed the outlet temperature of working fluid, PV module temperature, and absorber plate temperature of PVT collectors in series. In addition, the test setup of the performance of PVT collectors was established, including 36 PVT collectors in this experimental system and every six PVT collectors in a series. The thermal efficiency and electrical efficiency of the PVT collectors were evaluated. We validated the modelling prediction using experimental data and found a good concurrence between the measured and predicted data.