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The challenges of modern power systems with a high level of renewable generation penetration will impose increased ancillary service on Photovoltaic (PV) systems, including frequency regulation. In this paper, a frequency regulation strategy for PV systems without energy storage is proposed. The proposed strategy is divided into two layers: the frequency regulation layer and the power reserve control layer. In the power reserve control layer, a novel power reserve control is proposed as the core element and novel feature. The existing power reserve control for PV systems must estimate the maximum available power, which is difficult because of the variation in environmental conditions and complex modeling of PV systems. Instead, a power tracking control method based on a curtailment power-current curve is proposed. It can automatically track a given reserve ratio under any environmental condition without an irradiance sensor. In the frequency regulation layer, the combination of droop control and virtual inertia control is used to adjust the given power reserve ratio. Simulation results show that the proposed strategy offers good accuracy and tracking speed and can significantly improve the frequency response of the power system.

Accurate estimation of lithium battery state of charge is very important for ensuring the operation of battery management system, realizing the energy management strategy of electric vehicles, reducing mileage anxiety and promoting the sustainable development of electric vehicles. In this paper, several studies are carried out for state of charge estimation of lithium-ion battery: (1) Aiming at the problem of parameter identification of battery model, an optimal identification method of model parameters based on ant lion optimization algorithm is proposed. (2) An adaptive weighting Cubature particle filter (AWCPF) method is proposed for SOC estimation. The proposed AWCPF method is based on particle filter (PF) algorithm, while the Cubature Kalman filter (CKF) algorithm is utilized to generate the proposal distribution for PF algorithm, which can retrain the particles degradation problem in PF algorithm. To solve the problem that the CKF algorithm is sensitive to noise, comparing with fixed sigma point weights of the conventional CKF, the weights of sigma points are adaptively adjusted based on state and measurement residual vectors. Furthermore, the process noise and measurement noise are estimated iterative. In this paper, experimental verification of different initial values of SOC under various working conditions is carried out. The results show that the proposed AWCPF algorithm based SOC estimation method has high estimation accuracy, strong robustness, fast convergence speed, with the maximum SOC estimation error is less than 1%.

This paper considers the off-line roadside unit (RSU) ON/OFF scheduling problem in a sparse vehicular ad hoc network (VANET). We formulate the problem as a mixed integer non-linear programming problem and propose a heuristic scheduling algorithm called Multi-Level Greedy (MLG) algorithm to find a suboptimal approximation. In the proposed MLG algorithm, we introduce the concepts of optimal service location and suboptimal service location. Then, we obtain the ON-OFF state matrix of RSUs. Simulation results show that the MLG algorithm can significantly reduce the energy consumption of RSUs deployed and can provide a reference basis for energy efficient scheduling in VANETs.

This paper investigates a linear generator (LIG) for application in high speed maglev train. Its configuration and working principle are introduced in detail. The mathematic models of magnetic field and induced voltage are established by the equivalent magnetic circuit method and the law of electromagnetic induction respectively, through which the characteristics of LIG and impact factors are analyzed preliminarily. An analytical and numerical method is proposed to analyze the characteristics of LIG further, in which the finite element model is applied to calculate the magnetic field accurately and the analytical model is used for the induced voltage calculation in a discrete way. The relationships of induced voltage amplitude and speed, induced voltage frequency and speed are clarified, providing the basis for the design of power supply system on vehicle. Finally, the experiments for the magnetic field and induced voltage are carried out on the performance test bench of magnet and real vehicle respectively to validate the analysis results.

Hydraulic transformer is a significant component to develop the future energy saving hydraulic systems; however, the speed stability is one of the problems in such a machine because the rotor is unconstrained and the rotary inertia of the rotor is small. In this paper, aiming at the rotating speed of hydraulic transformer, a hydro-dynamic model of is proposed considering the nonlinear friction, oil compressibility and leakage. Both simulation and experiment are carried out to validate the hydro-dynamic model. Moreover, this paper theoretically analyzes the low-speed stability of hydraulic transformer based on the hydro-dynamic model for the first time. The mechanism of creep is discussed and the creep judgment method is presented. The influence of each parameter on creep is investigated, and the possible ways to avoid creep are explored. The calculations of the lowest stable rotating speed and the lowest stable flow rate without creep are given. This study is significant for the design and practical application of hydraulic transformer in the future.

Cell-free (CF) network is a favorable technique against inter-cell interferences to improve the network capacity. However, to further improve the network capacity, a large number of base stations (BSs) are required to be deployed with high cost and power consumption. To tackle this problem, an energy-efficient technique called reconfigurable intelligent surface (RIS)-aided CF network has been recently proposed. By replacing some of the required power-hungry BSs with low-power RISs, the energy efficiency of CF network can be enhanced with guaranteed performance. To achieve this goal, in this paper, we first formulate a joint active and passive beamforming problem to maximize the energy efficiency of RIS-aided CF networks. Then, we propose an alternate optimization algorithm to solve this problem. Specifically, we decompose the original energy efficiency maximization problem into multiple subproblems and solve them alternatively. Particularly, we adopt the zero-forcing (ZF) beamforming scheme to optimize the active beamforming at BSs, while the sequential programming (SP) method is adopted to realize the passive beamforming at RISs. Moreover, a realistic energy-consumption model for wideband RIS-aided CF networks is provided, and the effectiveness of the proposed scheme is evaluated by simulations. Finally, simulation results verify that, the proposed scheme is able to achieve a higher energy efficiency than the existing benchmark solution.

Improving the accuracy of power system load forecasting is important for economic dispatch. However, a load sequence is highly nonstationary and hence makes accurate forecasting difficult. In this paper, a method based on wavelet decomposition (WD) and a second-order gray neural network combined with an augmented Dickey-Fuller (ADF) test is proposed to improve the accuracy of load forecasting. First, the load sequence is decomposed by WD to reduce the nonstationary load sequence. Then, the ADF test is adopted as the test method for the stationary load sequence of each decomposed component after WD in which the test results determine the best WD level. Finally, because forecasting the wavelet details characterized by high frequencies is difficult owing to its fluctuation, a second-order gray forecasting model is used to forecast each component after WD. Furthermore, to obtain the optimum parameters of the second-order gray forecasting model, the neural network mapping approach is used to build the second-order gray neural network forecasting model. The simulation result of a real load sequence verifies that the method proposed in this paper can effectively improve the load-forecasting accuracy.

Ice shedding of transmission lines may lead to interphase flashover and thereby endanger power transmission. The ice shedding of transmission lines is essentially an energy conversion process. Based on the vibration theory and energy method of cable structures, the iced load of a transmission line is regarded as the working load under the condition of a bare conductor. The theoretical analysis model of ice shedding for a single-span transmission line was established with a vertical symmetrical vibration mode configuration. Then the analytical solution of maximum jump height is given. The proposed formula makes clear the quantitative relationship among maximum jump height and the verticality of the conductor, the icing mass ratios, and the dimensionless frequency. The vibration of a single-span transmission line after ice shedding is investigated by the finite element method to validate the proposed formula. The results show that the maximum jump height calculated by the formula has a good agreement with the finite element analysis, which fully meets the engineering accuracy requirements. The total jump height calculated by the current method is only 1.6% lower than that from finite element method. The contribution of high-order vertical mode is small with a small sag. By considering the contribution of high-order vertical modes, the calculation formula was further modified to get more accurate results. Since the vertical modes are mainly determined by dimensionless parameters, a simplified calculation empirical formula for maximum jump height optimization was obtained by fitting based on parametric analysis results. The presented proposed formula can provide theoretical guidance and be employed to predict the maximum jump height after ice shedding for transmission line design.