A Method for Deploying the Minimal Number of UAV Base Stations in Cellular Networks

In this paper,we consider the scenario of using unmanned aerial vehicles base stations(UAV-BSs)to serve cellular users.In particular,we focus on frnding the minimum number of UAV-BSs as well as their deployment.We propose an optimization model which minimizes the number of UAV-BSs and optimize their positions such that the user equipment(UE)covered ratio is no less than the expectation of network suppliers,the UEs receive acceptable downlink rates,and the UAV-BSs can work in a sustainable manner.We show the NP-hardness of this problem and then propose a method to address it.The method first estimates the range of the number of UAV-BSs and then converts the original problem to one which maximizes the UE served ratio,given the number of UAV-BSs within that range.We present a maximizing algorithm to solve it with the proof of convergence.Extensive simulations based on a realistic dataset have been conducted to demonstrate the effectiveness of the proposed method.

The Initial Guess Estimation Newton Method for Power Flow in Distribution Systems

With the increasing integration of distributed generations U+0028 DGs U+0029, there is a demand for DGs to play a more important role on the voltage regulation. Meanwhile, the high penetration of DGs could raise a technical problem that the distribution system may operate with bi-directional power flow, leading to the inadequacy of the traditional power flow. Considering this new scenario in distribution system power flow, the convergence theorem is proposed, which contributes to develop a novel selection method of the initial guess closed to the convergent solution. Moreover, to ensure the fast rate of power flow convergence, the theorem of the maximum iterations estimation is also proposed. Based on the two proposed theorems, an Initial Guess Estimation Newton method is proposed, considering different operational status of DGs and initial guess sensitivity simultaneously. Based on the standard node systems, Tongliao grid, and 69 system of USA, three simulation examples are provided to illustrate the effectiveness of the proposed method. © 2017 Chinese Association of Automation.

Group-Consensus of Hierarchical Containment Control for Linear Multi-Agent Systems

The existing containment control has been widely developed for several years, but ignores the case for large-scale cooperation. The strong coupling of large-scale networks will increase the costs of system detection and maintenance. Therefore, this paper is concerned with an extensional containment control issue, hierarchical containment control. It aims to enable a multitude of followers achieving a novel cooperation in the convex hull shaped by multiple leaders. Firstly, by constructing the three-layer topology, large-scale networks are decoupled. Then,under the condition of directed spanning group-tree, a class of dynamic hierarchical containment control protocol is designed such that the novel group-consensus behavior in the convex hull can be realized. Moreover, the definitions of coupling strength coefficients and the group-consensus parameter in the proposed dynamic hierarchical control protocol enhance the adjustability of systems. Compared with the existing containment control strategy, the proposed hierarchical containment control strategy improves dynamic control performance. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed hierarchical control protocol.

Adaptive Dead-Time Modulation Scheme for Bidirectional LLC Resonant Converter in Energy Router

Although the dead-time optimization design of resonant converters has been widely researched,classical design methods focus more on achieving zero-voltage switching(ZVS)operation.The body diode loss is always ignored,which results in low-efficiency of the converter,especially,in energy router(ER).To deal with this problem,this paper proposes an adaptive deadtime modulation scheme for bidirectional LLC resonant converters in ER.First,the power loss of the MOSFET is analyzed based on the dead-time.Then,a novel dead-time optimization modulation principle is proposed.It can eliminate the body diode loss of MOSFET compared with existing literature.Based on the optimization modulation principle,this paper proposes an adaptive dead-time modulation scheme.To this end,the converter adopting the scheme no longer needs to calculate dead-time,which simplifies the parameter design process.Meanwhile,this scheme enables dead-time to dynamically change with working conditions according to the dead-time optimization modulation principle.With these effects,the ZVS operation is achieved,and the body diode loss of MOSFET is also eliminated.Furthermore,a digital implementation method is designed to make the proposed modulation scheme have fast-transient response.Finally,experimental results show that the proposed dead-time modulation scheme enables converters to achieve ZVS operation in all working conditions,and has higher efficiency than classical dead-time design methods.

A Smart Charging Algorithm Based on a Fast Charging Station Without Energy Storage System

With the growing popularity of electric vehicles(EV),there is an urgent demand to solve the stress placed on grids caused by the irregular and frequent access of EVs.The traditional direct current(DC)fast charging station(FCS)based on a photovoltaic(PV)system can effectively alleviate the stress of the grid and carbon emission,but the high cost of the energy storage system(ESS)and the under utilization of the grid-connected interlinking converters(GIC)are not very well addressed.In this paper,the DC FCS architecture based on a PV system and ESS-free is first proposed and employed to reduce the cost.Moreover,the proposed smart charging algorithm(SCA)can fully coordinate the source/load properties of the grid and EVs to achieve the maximum power output of the PV system and high utilization rate of GICs in the absence of ESS support for FCS.SCA contains a self-regulated algorithm(SRA)for EVs and a grid-regulated algorithm(GRA)for GICs.While the DC bus voltage change caused by power fluctuations does not exceed the set threshold,SRA readjusts the charging power of each EV through the status of the charging(SOC)feedback of the EV,which can ensure the power rebalancing of the FCS.The GRA would participate in the adjustment process once the DC bus voltage is beyond the set threshold range.Under the condition of ensuring the charging power of all EVs,a GRA based on adaptive droop control can improve the utilization rate of GICs.At last,the simulation and experimental results are provided to verify the effectiveness of the proposed SCA.

Exponential-function-based droop control for islanded microgrids

An exponential-function-based droop control strategy for the distributed energy resources(DERs)is proposed to reduce the reactive power-sharing deviation,limit the minimum value of frequency/voltage,whilst improving the utilization rate of renewable energy.Both DERs and loads are interconnected to achieve a power exchange by converters,where the power management system should accurately share the active/reactive power demand.However,the proportional reactive power sharing often deteriorates due to its dependence on the line impedances.Thus,an exponential-function-based droop control is proposed to(1)prevent voltage and frequency from falling to the lower restraint,(2)achieve accurate reactive power sharing,(3)eliminate communication and improve the usage ratio of renewable energy.Furthermore,its stability is analyzed,and the application in islanded AC/DC hybrid microgrids is investigated to achieve the bidirectional power flow.The simulation and experimental results show that the reactive power sharing deviation can be reduced,and the utilization rate of renewable energy is improved by using the proposed method.Moreover,the simulation results illustrate that the system can maintain stable operation when the microgrid is switched from one supplied energy operation condition to another absorbed one.

Adaptive Bidirectional Droop Control for Electric Vehicles Parking with Vehicle-to-grid Service in Microgrid

With the popularity of electric vehicles(EVs),a large number of EVs will become a burden to the future grid with arbitrary charging management.It is of vital significance to the control of the EVs charging and discharging state appropriately to enable the EVs to become friendly to the grid.Therefore,considering the potential for EVs seen as energy storage devices,this paper proposes a multiport DC-DC solid state transformer topology for bidirectional photovoltaic/battery-assisted EV parking lot with vehicle-to-grid service(V2G-PVBP).Relying on the energy storage function of EVs,V2G-PVBP is able to not only satisfy the normal requirements of EVs’owner,but also provide the function of load shifting and load regulation to the microgrid.In this paper,EVs are categorized into limited EV and freedom EV.Limited EVs are always kept in charging state and freedom EVs can take part in the load regulation of the microgrid.The proposed adaptive bidirectional droop control is designed for freedom EVs to make them autonomously charge or discharge with certain power which according to each EV’s state of charge,battery capacity,leaving time,and other factors to maintain the stability of the future microgrid.Eventually,the simulation and experiment of the adaptive bidirectional droop control based V2G-PVBP are provided to prove the availability of V2G-PVBP.