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Fast frequency response (FFR) of battery energy storage system (BESS) is an effective way to mitigate the system frequency deviation induced by the fluctuation of power generation from the increased renewable energy resources and the impact of reduced system inertia caused by decreased synchronous generators. However, existing standards referring to technical requirements for the frequency measurement do not sufficiently consider abnormal grid conditions, such as voltage unbalance, frequency sweep, and dynamic voltage step. This article shows the impact of frequency measurement logic on the FFR performance of BESS in grid disturbance conditions by control hardware-in-the-loop (CHIL) testing and proposes improved frequency measurement logic based on a phase-locked loop (PLL). A benchmarking of the proposed PLL was conducted against existing PLL and discrete Fourier transformation-based frequency measurement logics. Finally, the FFR performance of BESS with each frequency measurement logic has been tested in CHIL simulation. This CHIL comprises the actual power plant controller, the actual bidirectional inverter control board, and a real-time simulator. In the CHIL experiments, several system disturbance situations likely to happen in existing power systems were considered as test cases and showed that the frequency measurement accuracy and latency were violated in some frequency measurement logics. Furthermore, this article reveals the effects of frequency measurement accuracy and latency on the FFR performance of BESS by a closed-loop power control simulation with a CHIL environment. In conclusion, considerations for the frequency measurement method used for FFR are proposed. [ABSTRACT FROM AUTHOR]

This article presents a 40-channel high-resolution automotive LiDAR system-on-chip (SoC), which utilizes the world’s first dual-data converter (DDC). The proposed DDC consolidates the functions of ADC and TDC into a single circuitry and achieves acquisition of both high-precision time and voltage data from the input, realizing a 5 $\times $ smaller analog front-end (AFE) area than prior arts. Such innovations lead us to a 40-channel AFE integration of the SoC without silicon cost increase, which characterizes our LiDAR system with 2 $\times $ higher pixel resolution. To enhance the ADC’s signal-to-noise and distortion ratio (SNDR) without sacrificing the area efficiency, a calibration-free and variation-tolerant voltage-controlled oscillator (VCO)-based ADC with a multiphase pulse density modulator (MP-PDM)-based feedback is proposed. Our proof-of-concept LiDAR system achieves a measurement range of 225 m at 70-klx direct sunlight, with a resolution of 240 $\times $ 192 pixels at 10 frames per second (FPS). To quantitatively measure the effect of the resolution improvement of our LiDAR, we evaluate the LiDAR’s detection accuracy of small targets 75 m away. Due to the 2 $\times $ higher vertical pixel resolution, our LiDAR can detect targets with 2 $\times $ smaller height. The 3-D point cloud of the LiDAR captured outdoor in the wild is presented. [ABSTRACT FROM AUTHOR]

We develop an algorithm for synthesizing a spatial pattern of charging/discharging operations of in-vehicle batteries for provision of ancillary service (AS) in power distribution grids. The algorithm is based on the ordinary differential equation (ODE) model of the distribution voltage that has been recently introduced. In this paper, first, we derive analytical solutions of the ODE model for a single straight-line feeder through a partial linearization, thereby providing a physical insight to the impact of spatial electric vehicle (EV) charging/discharging to the distribution voltage. Second, based on the analytical solutions, we propose an algorithm for determining the values of charging/discharging power (active and reactive) by in-vehicle batteries in the single feeder grid, so that the power demanded as AS (e.g., a regulation signal to the distribution system operator for the primary frequency control reserve) is provided by EVs, and the deviation of the distribution voltage from a nominal value is reduced in the grid. Effectiveness of the algorithm is established with numerical simulations on the single feeder grid and on a realistic feeder grid with multiple bifurcations. [ABSTRACT FROM AUTHOR]

This paper presents a time-to-digital converter/analog-to-digital-converter (TDC/ADC) hybrid LiDAR system-on-chip (SoC) to realize reliable self-driving systems. The smart accumulation technique (SAT) is proposed to achieve both 200-m and high-pixel-resolution range imaging, which was untrodden with conventional LiDARs. The “smart” accumulation is realized by a simple object recognition strategy with small circuit overhead. When compared to conventional accumulations, the LiDAR range is enhanced without degrading the pixel resolution. Moreover, a TDC/ADC hybrid architecture is proposed to achieve a wide-distance-range LiDAR with a small silicon area and short-range precision. To minimize the ADC cost, a residue-quantizing noise-shaping (RQNS) SAR ADC is proposed. The prototype LiDAR SoC is fabricated in the 28-nm CMOS technology and integrated into the silicon photomultiplier (SiPM)-based LiDAR system. LiDAR measured with 240 $\times$ 96 pixels at 10 frames/s achieves a measurement range of 200 m with a 70-klx direct sunlight: the measurement range is 2 $\times$ longer than conventional designs. Furthermore, our LiDAR achieves 4 $\times$ higher effective pixel resolution compared to conventional designs using simple accumulation. A 3-D point-cloud image acquired with a real-life environment is presented. [ABSTRACT FROM AUTHOR]

The large integration of photovoltaic (PV) power generation systems into power systems causes deterioration in power system stability. In our previous work, we showed that reactive power control using the inverters of PV systems, known as dynamic voltage support (DVS) capability, is a promising approach to improve the short-term voltage stability in power systems. In this paper, we propose a novel DVS capability as a function of PV inverters. In contrast to the conventional DVS capability, the proposed method uses both active and reactive power injection to improve the short-term voltage stability. Numerical examples show that the proposed DVS capability further improves the short-term voltage stability compared with the conventional DVS capability. Furthermore, the proposed method can alleviate a frequency drop after a fault caused by interruption in PV systems. [ABSTRACT FROM AUTHOR]

To integrate large scale renewable energy sources in the power grid, the battery energy storage performs an important role for smoothing their natural intermittency and ensuring grid-wide frequency stability. Electric vehicles have not only large introduction potential but also much available time for control because they are almost plugged in the home outlets as distributed battery energy storages. Therefore, vehicle-to-grid (V2G) is expected to be one of the key technologies in smart grid strategies. This paper proposes an autonomous distributed V2G control scheme. A grid-connected electric vehicle supplies a distributed spinning reserve according to the frequency deviation at the plug-in terminal, which is a signal of supply and demand imbalance in the power grid. As a style of EV utilization, it is assumed that vehicle use set next plug-out timing in advance. In such assumption, user convenience is satisfied by performing a scheduled charging for the plug-out, and plug-in idle time is available for the V2G control. Therefore a smart charging control is considered in the proposed scheme. Satisfaction of vehicle user convenience and effect to the load frequency control is evaluated through a simulation by using a typical two area interconnected power grid model and an automotive lithium-ion battery model. [ABSTRACT FROM PUBLISHER]