• Energy Research
• 2016-2025close
• 7. Clean energy close
• 13. Climate action close
• Southeast University close

To unlock the potential of flexible resources, a multi-time-scale economic scheduling strategy for the virtual power plant (VPP) to participate in the wholesale energy and reserve market considering large quantity of deferrable loads (DLs) aggregation and disaggregation is proposed in this paper. For the VPP multi-time-scale scheduling including day-ahead bidding and real-time operation, the following models are proposed, namely, DLs aggregation model based on clustering approach, economic scheduling model considering DLs aggregation, and DLs disaggregation model satisfying consumers’ requirements, respectively. The proposed strategy can realize the efficient management of massive DLs to reduce the energy management complexity and increase the overall economics with high computation efficiency, which indicate its promising application in the VPP economic scheduling.

In order to improve the degree of renewable energy integration, the demand response resource, especially on the air conditioning load side, has received attention. Currently, most of the control modes for air conditioners are centralised control, which is difficult to be applied to widely distributed air conditioning. The current studies focus on central air conditioning, but there are few studies on split-type inverter air conditioning, even though inverter air conditioning has become the most common split air system on the market. With this background, this study designs a consensus control strategy on the basis of distributed control mode, which for inverter air conditioners. The strategy is used for renewable energy integration in the studied region. The test results of various cases reveal the following findings: (i) the strategy adapts to the widely distributed air conditioning, (ii) the strategy can guarantee a fair allocation of power imbalance and user comfort, (iii) the control strategy can adapt to the uncertainties of air conditioners and the urban microclimate while efficiently consuming renewable energy. Therefore, the proposed consensus control strategy has practical value.

Abstract In a pressurized water reactor (PWR), the control rod drop analysis is crucial for the reactor safety and the integrity of core structure. Especially under a seismic condition, the horizontal deflections of the reactor system could cause impact between the control rods and the guide thimbles, and then the resulting frictional forces can significantly increase the scram time and intensify mechanical interaction at the absorber rod cladding and spider springs. The CRDAC code is a control rod scram analysis tool developed by China Nuclear Power Technology Research Institute (CNPRI). In a previous work, Liu et al., 2013 , Li et al., 2013 studied the transverse behavior and the fluid-structure interaction of the whole movement system based on this code. Liu calculated the scram time of a 12ft fuel assembly under the Wenchuan earthquake wave. Huang et al. (2014) proposed a flow model to describe the effect of the flow field parameters on the scram time under the operation condition. This paper presents the seismic analysis method based on the CRDAC code which developed by China Nuclear Power Technology Research Institute (CNPRI). Both the scram time and the seismic response have been calculated, such as the maximum pressure in the guide thimble, impact forces to the spider spring, and friction forces to the absorber rod. According to the design requirements of the third-generation nuclear power plants, safety shutdown earthquake (SSE) and operating basis earthquake (OBE) for the horizontal response need to satisfy 0.3 g and 0.15 g, respectively. Therefore, the maximum accelerations of both the input and the initial horizontal deformation of a fuel assembly have been taken into account in this paper. After several sensitive analyses, it is found that the CRDAC code is a powerful tool for the design of control rods and fuel assemblies.

Abstract Technological progress is an effective way to improve electricity efficiency. Due to the existence of the rebound effect, it is of great significance to optimize the technical power saving policy by examining the rebound effect caused by different technological progress paths.Based on the panel data of electricity industry in 30 provinces of China from 1997 to 2013, this paper systematically examines the rebound effects of electricity consumption under the two sources of technological progress, namely independent innovation and technology import. Then, it discusses the impact of coal-electricity linkage policy. The empirical results are as follows: (1) without considering rebound effect, independent innovation significantly promotes electricity conservation, while the effects of technology import is not obvious; (2) when considering the rebound effect, electricity price declining driven by independent innovation is not conducive to electricity saving, while electricity price declining driven by technology import has an electricity-saving effect; (3)The coal-electricity linkage policy that began in 2004 not only reduced the rebound effect by increasing the flexibility of electricity prices to a certain extent and improved the electricity-saving effect of independent innovation, but also reduced the electricity-saving effect of technology import.

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

With the implement the new power system reform, the competition in the electricity sales market is becoming increasingly fierce, and electricity retailers need to adopt effective operating strategies to increase revenue. Electricity sales companies face the risk of electricity price uncertainty when participating in the spot market. Sampling and scenario reduction methods are used to obtain random scenarios of electricity prices and loads. Conditional value-at-risk (CVaR) is introduced and scenario analysis is used to evaluate the market analysis of electricity retailers. An optimization model for electricity purchase by electricity retailers in day-ahead market was established, and the bidding curve was optimized. Electricity retailers can stabilize revenue and avoid risks by increasing power purchases in day-ahead market during peak period and using interruptible loads.

The voltage unbalance (VU) problem aroused the severe operation accident for wind farm, as the single-phase traction power supply system (TPSS) and wind farm connected to a common busbar. This paper presents a uniform mathematical model to portray the VU transfer between the TPSS of high-speed railway (HSR), wind farm and asymmetric grid. Furthermore, an estimating approach for VUF of TPSS is proposed to illustrate the VU impact of wind farm on TPSS. Finally, the effectiveness of proposed model is verified by a case study, and revealed the reason of how to the wind farm affects VU propagation.

The high penetration of wind energy in electrical power systems presents challenges for all operators. For the wind farm (WF) planners, one of these challenges is optimizing its layout with a set of constraints. This paper proposes a bi-hierarchy optimization scheme to determine the capacity and layout of a grid-connected WF. The environmental impacts involved by the installation of a WF have been taken into consideration in the problem. The first-layer model optimizes the WF capacity and configuration with minimized comprehensive generation cost of wind energy and two sets of constraints. The sound pressure level ( SPL ) limit of the noise emitted by the wind turbines (WTs) is handled to be one of the constraints of the first-layer model. The second-layer model determines the generation schedule of other conventional generators. A Gaussian wake model is applied to calculate the effective wind speed for each WT. For the simulations, the WF is supposed to be integrated in the IEEE 30-bus test system. The wild goats algorithm (WGA) and the quadratic programming (QP) method are used to solve the problem. The simulation results validate the effectiveness of the proposed model and prove that environmental influences of WFs should not be ignored during the planning stage.

In order to improve the system efficiency and operational economy of hybrid energy storage (HES) tramway under cycle conditions, this paper presents an energy management method based on equivalent loss instantaneous optimization (ELIO) for lithium battery/supercapacitor hybrid energy storage system (HESS) with dual DC/DC topology. The online convex programming method is used to solve the problem, and the optimal dynamic mixing degree at each moment of the system is obtained. This proposed method properly allocates the power flow between lithium battery and supercapacitor to minimum the system equivalent loss in the unit control period. According to the equivalent loss theory, the ELIO problem is converted to the optimal output power solution of the HESS. Under various operating conditions, the multi-index performance is tested and analyzed by a HESS test platform, which consists of lithium battery, supercapacitor, bidirectional DC/DC converter and energy management system. The experimental results show that compared with the power following strategy, this proposed ELIO method can effectively improve more than system efficiency, operational economy and driving mileage, and improved the service life of HESS by smoothing battery operating pressure.