Assessment of Low Global Warming Potential Refrigerants for Waste Heat Recovery in Data Center with On-Chip Two-Phase Cooling Loop

Data centers(DCs)are highly energy-intensive facilities,where about 30%–50%of the power consumed is attributable to the cooling of information technology equipment.This makes liquid cooling,especially in twophase mode,as an alternative to air cooling for the microprocessors in servers of interest.The need to meet the increased power density of server racks in high-performance DCs,along with the push towards lower global warming potential(GWP)refrigerants due to environmental concerns,has motivated research on the selection of two-phase heat transfer fluids for cooling servers while simultaneously recovering waste heat.With this regard,a heat pump-assisted absorption chiller(HPAAC)system for recovering waste heat in DCs with an on-chip twophase cooling loop driven by the compressor is proposed in the present paper and the low GWP hydrofluoroolefin refrigerants,including R1224yd(Z),R1233zd(E),R1234yf,R1234ze(E),R1234ze(Z),R1243zf and R1336mzz(Z),are evaluated and compared against R245fa as server coolant.For theHPAAC system,beginning with the development of energy and economic models,the performance is analyzed through both a parametric study and optimization using the coefficient of performance(COP),energy saving ratio(ESR),payback period(PBP)and net present value(NPV)as thermo-economic indicators.Using a standard vapor compression cooling system as a benchmark,the results indicate that with the evaporation temperature between 50℃and 70℃and the subcooling degree ranging from5℃to 15°C,R1233zd(E)with moderate compressor suction pressure and pressure ratio is the best refrigerant for the HPAAC systemwhile R1234yf performs the worst.More importantly,R1233zd(E)is also superior to R245fa based on thermo-economic performance,especially under work conditions with relatively lower evaporation temperature as well as subcooling degree.Under the given working conditions,the overall COP,ESR,NPV,and PBP of R1233zd(E)HPAAC with optimum subcooling degree range from4.99 to 11.27,25.53 to 64.59,1.13 to 4.10×10^(7) CNY and 5.77 to 2.22 years,respectively.Besides,the thermo-economic performance of R1233zd(E)HPAAC under optimum working conditions in terms of subcooling degree varying with the evaporation temperature is also investigated.

Investigations on Discharge and Decomposition Characteristics of SF6 Under Various Experimental Conditions

Detection of gas decomposition products is widely used for condition diagnosis of SF6-insulated equipment because of its an- ti-electromagnetic-interference ability and high sensitivity. Previous investigations show that the volume of gas chamber influences the types and concentrations of SF6 decomposition products. Therefore using a newly developed dual gas chromatography (GC) detection sys- tem we investigated the discharge and decomposition of SF6 in a discharge chamber with its volume close to that of the real chambers in GIS. Tests in the chamber were performed with different applied voltage, different electrode arrangements, and different defect types. For discharge between needle-to-plane electrodes, the typical gas decomposition products are SO2F2, SO2 and S2OF10. A near linear growth with the increase of voltage duration is found in the concentration of SO2F2, whereas the growth rates of SO2 and S2OF10 concentration decrease with time. Concentrations of SO2F2, SO2 and S2OF10 at the same voltage duration decrease with the decrease of the voltage amplitude and the increase of the needle-to-plane distance. Change of the gas chamber volume affects the generation rates of SO2F2 and SO2, however not S2OF10. For insulator surface defects, the typical gas decomposition products are CF4, CS2 and SO2. Among which, the concentrations of CF4 and SO2 increase with the voltage duration almost linearly. Moreover, a new parameter that represents the degree of SF6 degradation, the SF6 deterioration ratio, is proposed. In the needle-to-plane case, SF6 deterioration ratio is positively correlated to the fitting value of an averaged discharge capacity. However, the maximum value of SF6 deterioration ratio varies with the defect type.

Analysis of Conductors＇ Surface Electric Field of UHVDC Transmission Lines Based on Optimized Charge Simulation Method

The choice of the UHV lines depends on surface electric field of the bundle conductors.Based on existing calculation methods,the optimized charge simulation method is used to calculate the conductors' surface electrical field of±800 kV UHVDC transmission lines in this paper.During calculation,the offset distance is set as the variance of the objective function,the position and the quantity of the simulation charges are optimized with the gold section method,and the surface electrical field is calculated when the charge is in the optimal position.The result shows that the distribution of the surface electrical field and its maximal value can be calculated accurately with this method,although less number of simulation charges is used in this proposed method and the calculation is simple.

A Low-Cost, Smart AC Charging System for Electric Vehicle

In industry development strategy of electric vehicles, apart from concerns on the development of electric vehicles, we also need to consider the issue of charging facilities construction. Firstly, through analysis, this paper discusses the importance of AC charging points for electric vehicle development. By studying existing AC charging points on the market, it presents a low-cost smart AC charging system to reduce the cost investigated by power companies and operational bodies when laying of a large number of AC charging points. Compared with the conventional one, the proposed system has prominent features of low cost, small footprint and low investment.

Discharge area segmentation of power equipment in UV image based on GVF snake model

The dynamic transmission characteristics and the sensitivities of the three stage idler gear system of the new NC power turret are studied in the paper. Considering the strongly nonlinear factors such as the periodically time-varying mesh stiffness, the nonlinear tooth backlash, the lump-parameter model of the gear system is developed with one rotational and two translational freedoms of each gear. The eigen-values and eigenvectors are derived and analyzed on the basis of the real modal theory. The sensitivities of natural frequencies to design parameters including supporting and meshing stiffnesses, gear masses, and moments of inertia by the direct differential method are also calculated. The results show the quantitative and qualitative impact of the parameters to the natural characteristics of the gear system. Furthermore, the periodic steady state solutions are obtained by the numerical approach based on the nonlinear model. These results are employed to gain insights into the primary controlling parameters, to forecast the severity of the dynamic response, and to assess the acceptability of the gear design.

Multi-Agent Consensus Control Scheme for the Load Control Problem

With the help of smart grid technologies,a lot of electrical loads can provide demand response to support the active power balance of the grid.Compared with centralized control methods,decentralized methods reduce the computational burden of the control center and enhance the reliability of the communication.In this paper,a novel second-order multi-agent consensus control method is proposed for load control problem.By introducing the velocity state into the model,the proposed method achieves better performance than traditional ones.Simulation results verify the effectiveness of the proposed method.

Fullerenes for rechargeable battery applications:Recent developments and future perspectives

The development of high-performance batteries is inseparable from the exploration of new materials.Among them,fullerene C60 as an allotrope of carbon has many unique properties that are beneficial for battery applications,including precise structure,controllable derivatization,good solubility,and rich redox chemistry.In this review,we summarize the recent progress of fullerene-based materials in the field of rechargeable batteries and the key issues that need to be solved in the future application of fullerene.We hope this review can provide guidance and stimulate research about the applications of fullerenes in the field of energy storage.

Adaptive Reference Power Based Voltage Droop Control for VSC-MTDC Systems

Featuring low communication requirements and high reliability,the voltage droop control method is widely adopted in the voltage source converter based multi-terminal direct current(VSC-MTDC)system for autonomous DC voltage regulation and power-sharing.However,the traditional voltage droop control method with fixed droop gain is criticized for over-limit DC voltage deviation in case of large power disturbances,which can threaten stable operation of the entire VSCMTDC system.To tackle this problem,this paper proposes an adaptive reference power based voltage droop control method,which changes the reference power to compensate the power deviation for droop-controlled voltage source converters(VSCs).Besides retaining the merits of the traditional voltage droop control method,both DC voltage deviation reduction and power distribution improvement can be achieved by utilizing local information and a specific control factor in the proposed method.Basic principles and key features of the proposed method are described.Detailed analyses on the effects of the control factor on DC voltage deviation and imbalanced power-sharing are discussed,and the selection principle of the control factor is proposed.Finally,the effectiveness of the proposed method is validated by the simulations on a five-terminal VSC based high-voltage direct current(VSC-HVDC)system.

Exploiting demand-side heterogeneous flexible resources in risk management of power system frequency

More demand-side flexible resources(DFRs)are participating in the frequency regulation of renewable power systems,whose heterogeneous characteristics have a significant impact on the system frequency response.Consequently,selecting suitable DFRs poses a formidable challenge for independent system operators(ISO).In this paper,a reserve allocation methodology for heterogeneous DFRs is proposed to manage the risk of power system frequency.Firstly,a performance curve is developed to describe the cost,capacity,and response speed of DFRs.Moreover,a clustering method for multiple distributed DFRs is conducted to calculate the aggregated performance curves and uncertainty coefficients.Then,the frequency security criterion considering DFRs’performance is constructed,whose linearity makes it can be easily coupled into the system scheduling model and solved.Furthermore,a risk management model for DFRs considering frequency-chance-constraint is proposed to make a trade-off between cost and frequency security.Finally,the model is transformed into mixed integer second-order cone programming(MISOCP)and solved by the commercial solver.The proposed model is validated by the IEEE 30 and IEEE 118 bus systems.

Comprehensive evaluation of multi-energy complementary ecosystem based on improved multicriteria decision-making method

The multi-energy complementary ecosystem is an important form of the modern energy system.However,standardized evaluation criteria and the corresponding method framework have not yet been formed,resulting in unclear standards and irregular processes of its construction.To cope with this issue,a novel comprehensive evaluation framework for multi-energy complementary ecosystems is proposed in this study.First,a 5D comprehensive evaluation criteria system,including environment,economy,technology,safety and systematicness,is constructed.Then,a novel multicriteria decision-making model integrating an analytic network process,entropy and preference-ranking organization method for enrichment evaluation under an intuitional fuzzy environment is proposed.Finally,four practical cases are used for model testing and empirical analysis.The results of the research show that the unit cost of the energy supply and the internal rate of return indexes have the highest weights of 0.142 and 0.010,respectively.It means that they are the focus in the construction of a multi-energy complementary ecosystem.The net flows of four cases are 0.015,0.123,-0.132 and-0.005,indicating that cases with a variety of energy supply forms and using intelligent management and control platforms to achieve cold,heat and electrical coupling have more advantages.

Interharmonic Analysis Model of Photovoltaic Grid-connected System with Extended Dynamic Phasors

The interactions between randomly fluctuating power outputs from photovoltaic(PV) at the DC side and background voltage distortions at the AC side could generate interharmonics in the PV grid-connected system(PVGS). There is no universal method that can reveal the transmission mechanism of interharmonics and realize accurate calculation in different scenarios where interharmonics exist in the PVGS. Therefore, extended dynamic phasors(EDPs) and EDP sequence components(EDPSCs) are employed in the interharmonic analysis of the PVGS. First, the dynamic phasors(DPs) and dynamic phasor sequence components(DPSCs) are extended into EDPs and EDPSCs by selecting a suitable fundamental frequency other than the power frequency. Second, an interharmonic analysis model of the PVGS is formulated as a set of state space equations. Third, with the decoupling characteristics of EDPSCs,generation principles and interactions among the interharmonics in the PVGS are presented by the sequence components,and its correctness is verified by simulation and experiment.The presented model can be used to accurately calculate the interharmonics generated in the PVGS both at the AC and DC sides. Because of the decoupling among the EDPSCs, the set of state space equations can effectively describe the principle.

Planning and Real-time Pricing of EV Charging Stations Considering Social Welfare and Profitability Balance

This paper presents a planning and real-time pricing approach for EV charging stations(CSs).The approach takes the form of a bi-level model to fully consider the interest of both the government and EV charging station operators in the planning process.From the perspective of maximizing social welfare,the government acts as the decision-maker of the upper level that optimizes the charging price matrix,and uses it as a transfer variable to indirectly influence the decisions of the lower level operators.Then each operator at the lower level determines their scale according to the goal of maximizing their own revenue,and feeds the scale matrix back to the upper level.A Logit model is applied to predict the drivers’preference when selecting a CS.Furthermore,an improved particle swarm optimization(PSO)with the utilization of a penalty function is introduced to solve the nonlinear nonconvex bi-level model.The paper applies the proposed Bi-level planning model to a singlecenter small/medium-sized city with three scenarios to evaluate its performance,including the equipment utilization rate,payback period,traffic attraction ability,etc.The result verifies that the model performs very well in typical CS distribution scenarios with a reasonable station payback period(average 6.5 years),and relatively high equipment utilization rate,44.32%.

Deep Reinforcement Learning Based Charging Scheduling for Household Electric Vehicles in Active Distribution Network

With the booming of electric vehicles(EVs) across the world, their increasing charging demands pose challenges to urban distribution networks. Particularly, due to the further implementation of time-of-use prices, the charging behaviors of household EVs are concentrated on low-cost periods, thus generating new load peaks and affecting the secure operation of the medium-and low-voltage grids. This problem is particularly acute in many old communities with relatively poor electricity infrastructure. In this paper, a novel two-stage charging scheduling scheme based on deep reinforcement learning is proposed to improve the power quality and achieve optimal charging scheduling of household EVs simultaneously in active distribution network(ADN) during valley period. In the first stage, the optimal charging profiles of charging stations are determined by solving the optimal power flow with the objective of eliminating peak-valley load differences. In the second stage, an intelligent agent based on proximal policy optimization algorithm is developed to dispatch the household EVs sequentially within the low-cost period considering their discrete nature of arrival. Through powerful approximation of neural network, the challenge of imperfect knowledge is tackled effectively during the charging scheduling process. Finally, numerical results demonstrate that the proposed scheme exhibits great improvement in relieving peak-valley differences as well as improving voltage quality in the ADN.