Smooth Power Research Articles

Robust Proactive Power Smoothing Control of PV Systems Based on Deep Reinforcement Learning

Efficient integration of photovoltaic (PV) energy into the power grid calls for a robust regulation of its intermittency. At present, the solar forecasting-assisted proactive power smoothing control (PPSC) has shown superiority in handling such PV intermittency due to its battery-less operations. However, the implementation of PPSC is largely dependent on the quality of solar forecasts, i.e, high accuracy over a long horizon, which has seriously limited its extensive application in practice. In this context, this paper proposes a novel PPSC method based on deep reinforcement learning (RL). In addition to the actor-critic structures, a new module, namely, compensator is developed to tackle the problems of sparse reward and state transition stochasticity that are typically associated with the PPSC control task. On top of it, a novel scenario recognized experience replay (SRER) is devised to deal with the data distribution mismatching issue in PPSC. The effectiveness of the proposed method is verified using real-world data from a solar measurement grid. Empirical studies show that compared with the conventional PPSC method, the proposed method can achieve more robust smoothing performance under various forecasting scenarios, rendering it more applicable to practical PV system operations.

Composite power supply topology design with energy-controlled distribution switches

An electric car’s battery is equivalent to a fuel vehicle’s engine, without a battery, it is equal to an empty shell. The single energy supply of the battery is difficult to meet the long-term endurance requirements of electric vehicles. Combined with the existing traditional composite power structure, the advantages and disadvantages of the existing traditional composite power supply structure are analyzed. A composite power supply structure combining a supercapacitor and power battery is proposed. The supercapacitor is responsible for the peak high power output, and the power battery is responsible for smooth power output. Simulation results show that the new composite power supply has noticeable improvements compared to traditional structures regarding energy loss and power distribution.

Fault Diagnosis of Hydraulic System based on SOM Neural Network

The working principle of hydraulic system is to use the flow and pressure of liquid in the system for energy transfer and conversion. Hydraulic system realizes various work tasks such as pushing, grasping, lifting, rotating, etc. by controlling the action of hydraulic actuators. Its advantages are high power density, good stability, fast response time, smooth power output, etc. The disadvantage is that the hydraulic system is easy to lose control of more points. In this paper, taking the horizontal outrigger hydraulic circuit as an example, the hydraulic pump leakage, etc. is used as a fault sample, and the SOM neural network is used for fault diagnosis to make timely and accurate diagnosis of the abnormal or fault state of the hydraulic system, give guidance on the operation of the hydraulic system, improve the reliability and safety of operation, and reduce the fault loss to a minimum.

Real‐Time Energy Management Strategy for Fuel Cell Plug‐In Hybrid Electric Bus Using Short‐Term Power Smoothing Prediction and Distance Adaptive State‐of‐Charge Consumption

To improve energy consumption economy and fuel cell life economy, this article proposes a multiobjective real‐time energy management strategy based on short‐term power smoothing prediction and distance adaptive state‐of‐charge (SOC) consumption for fuel cell/battery plug‐in hybrid electric bus. First, a distance adaptive SOC real‐time reference trajectory planning method is proposed by collecting the actual operating condition data of Dalian city buses. Second, the motor power is smoothed using the first‐order exponential smoothing approach, and the long short term memory network is adopted to predict the smoothed motor power. Finally, based on the predicted motor power and a real‐time reference SOC, a model predictive control strategy is designed in the finite prediction horizon, and dynamic programming is used to solve multiobjective cost functions to achieve optimal power allocation. Simulation results show that the proposed strategy has remarkable performance in terms of the total operating cost, SOC sustenance, and fuel cell degradation compared with the rule‐based strategy. In addition, the average time of online energy distribution in each step of the proposed strategy is 43.8 ms, which is much smaller than the simulation step length of 1s.

ITBC Controlled IPWM for Solar Based Wide Range Voltage Conversion System

This paper presents an isolated tiny or micro-bidirectional DC–AC converter (ITBC) that operates in a single-phase, single-stage, bidirectional, and isolated configuration. The converter utilises a voltage-in-phase PWM (IPWM) control scheme to regulate the potential conversion ratio of the converter, enabling it to handle a wide voltage range. The converter also enables smooth power flow direction changes and can achieve soft switching, resulting in high efficiency. A unidirectional current controller can be used for both DC–AC and AC–DC modes. The paper provides detailed information about the micro-inverter's working principles, design procedure, characteristics, and control strategy. The proposed solution is verified by a 500-watt test bench model with a voltage input range of 30 volts to 50 volts.

A Dual-Frequency-Detuning Method for Improving the Coupling Tolerance of Wireless Power Transfer

This letter proposes a dual-frequency-detuning method for wireless power transfer systems to gain a smooth power profile in large coupling variation ranges. The application of the detuning method in the dual-frequency resonant network is explored to adjust the equivalent impedance of each frequency channel at different coupling conditions. Accordingly, the proposed method can freely regulate the voltage gain and output power curves even under a square-wave voltage excitation with high-order harmonic components. By designing the system properly, both the fundamental and 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> frequency channels alternately serve as the main power transfer channel under strong and weak coupling conditions, so less power fluctuation over a large coupling variation is realized. A 130W prototype is developed, and the experimental results show that the maximum power fluctuation is less than 6.8% against coupling coefficient variations from 0.35 to 0.74.

Spatial Azimuthal Misalignment Characteristics of High-Temperature Superconducting Wireless Power Transmission Systems

Magnetically coupled resonant wireless power transmission technology (WPT) based on high-temperature superconducting (HTS) coils has gained wide popularity due to its low impedance and high-quality factor Q value characteristics. This technology has greatly improved the energy transfer performance of wireless power transmission (WPT) systems. However, practical applications of conventional WPT, such as wireless charging of autonomous underwater vehicles at mooring points, often encounter spatial misalignment issues due to the complex ocean environment and ocean currents. Nonetheless, few studies have investigated the spatial misalignment of HTS WPT systems, particularly the angular misalignment. This paper presents a solution to address this problem by constructing magnetically coupled resonant wireless energy transmission systems based on HTS coils and copper coils. The study analyzes the relationship between the transmission efficiency of the WPT system and the received power of the load with respect to the spatial orientation of the coil. The performance of the superconducting coil and copper coil WPT systems is compared. The experimental results demonstrate that, under the same spatially misaligned conditions, the WPT system using HTS coils can significantly improve the transmission efficiency and load power compared to the conventional copper WPT system. Moreover, simultaneous adjustment of the lateral misalignment distance and different orientation deflection angles can improve the transmission efficiency and smooth load output power of the high-temperature superconducting WPT system.

Multi-objective genetic algorithm based energy management system considering optimal utilization of grid and degradation of battery storage in microgrid

This paper develops intelligent energy management in Microgrid using forecasting-based multi-objective optimization using genetic algorithm framework. In this work, the energy storage system is included in Microgrid network, which is essential for effective energy management and smooth power transfer. The developed model incorporates the forecasted values of solar PV and wind generation obtained using time series long short-term memory network for the next 24 h and provides the optimal values of battery and grid powers to meet the deficit of power to meet the demand in the Microgrid. The proposed model incorporates grid power consumption cost and battery degradation cost as the objectives with battery status and renewables utilization as the constraints of the optimization model. The fuzzy decision-making strategy obtains the compromise solution in the Pareto optimal front from multiple solutions. The proposed model is investigated with fixed and variable grid tariff conditions achieving efficient performance in energy management with optimal utilization of renewables, grid and battery in the system for 24 hours-time horizons. The system parameters in the Microgrid network are also investigated in the time horizon with the optimal values of proposed model. The proposed intelligent energy management system model is tested in 2.5 MW PV/wind/energy storage Microgrid system in MATLAB 2020 simulation platform and experimental setup of 1 kW grid connected Microgrid with solar PV and battery.

Analysis of energy variability and costs for offshore wind and hybrid power unit with equivalent energy storage system

Offshore wind and wave energy are largely untapped renewable resources. However, the intermittency and the high cost of energy of these resources pose a few major challenges for their wide-scale developments. Although energy storage systems are considered to mitigate or reduce the energy variability to support a reliable power network, the proposed solutions have further increased the capital expenditure. This is primarily due to a lack of systematic techno-economic assessments of offshore renewable systems with energy storage. In addition, the integration of offshore wind and wave energy systems reported in previous literature showed a number of benefits, such as power smoothing and cost reduction. This paper investigates the offshore wind and wave energy intermittency and their dispatchability and proposes an equivalent energy storage system to achieve the same level of energy variability as the combined wind and wave system. This provides a thorough understanding of the power smoothing performance and firmness of energy supply in an offshore energy farm. The economic assessment of the stand-alone offshore wind system, the wind turbine with an energy storage system and the hybrid power unit system are conducted and compared via high-fidelity cost models. In addition, the sensitivities of three system configurations are investigated at multiple locations around the world, which are selected to address typical wind and sea states. The results indicate that the hybrid wind and wave power system has merits in reducing energy variability and enhancing ocean energy dispatchability while offering highly competitive cost, compared to the other two system configurations. Furthermore, the research aims to provide a guidance and support for the developers, investors and policymakers at the pre-planning stage of developing ocean renewable energy systems.

용량이 다른 PV-ESS의 연계운전을 위한 pu단위 제어기 설계법

This paper proposes a per unit conversion methodology for a PV(Photovoltaic)-ESS(Energy Storage System) interconnected system with contrasting capacity to another and performs power smoothing of PV output. PV and ESS comprehensively designed into per unit for caculation. Since PV and ESS have different capacities, when integrating PV and ESS systems, choosing a base value for inner per unit conversion is highly important. The system contains an inner loop controller with SOC feedback values which adds difficulties when converting into per unit. In this paper, we theoretically discuss and prove how to design a controller including internal SOC feedback controller in pu unit, used for active power smoothing. This methodology is supported by logical verifications and simulations. Verification is carried out by comparing the different case studies of PV-ESS system of implementing pu conversion method and relevant simulation is tested using PSCAD simulation, and the output data was inspected through correlation.

Design and Control of Two-Stage DC-AC Solid-State Transformer for Remote Area and Microgrid Applications

The critical challenges with integrating renewable energy into the grid are smooth power flow control, isolation between the high-voltage and low-voltage networks, voltage regulation, harmonic isolation, and power quality regulation. This paper considers the design and construction of a two-stage DC-AC solid-state transformer based on wide bandgap (WBG) semiconductor technologies, an optimized medium-frequency transformer, and PI and dq controllers for supplying urban area electric drive systems and microgrid applications. The designed SST consists of a dual active bridge (DAB) DC-DC converter followed by a DC-AC three-phase inverter. Each stage of the SST was simulated with independent controllers. The proposed system was initially developed in MATLAB/Simulink and a laboratory prototype was constructed to verify the results experimentally. Resistive and inductive load were used to test the load disturbance to evaluate the voltage regulation performance. This work has comprehensively provided the performance of a double stage (DC-DC and DC-AC converter) by taking into consideration input voltage, load disturbance, and voltage tracking both in simulation and experiment. The dual active bridge with its controller is able to maintain the desired output reference voltage with minimal voltage ripples under input voltage fluctuations and load variations. Similarly, the three-phase DC-AC converter’s controller exhibits better performance in tracking the desired reference voltage and producing well-regulated AC voltage with low harmonic distortion.

An unprecedented control of 3‐phase grid tied solar photovoltaic‐hydrogen/bromine‐supercapacitor composite storage microgrid for pulse power load regulation under nonideal grid conditions

AbstractPhotovoltaic (PV) power penetration into the distribution grid has increased. PV power fluctuations, abrupt load changes, nonlinear loading, growing usage of portable electronic devices, electric cars low average power and comparatively high pulse power needs, and other factors translate into severe grid instability. As a result, in these circumstances, power exchange between PV and the utility grid becomes a difficult task. Therefore, this article proposes a hydrogen/bromine (H2/Br2) redox flow battery and supercapacitor composite energy storage for a three phase grid tied PV system with multifunctional active power filter support to ensure grid codes. Further, the system is equipped with an unprecedented control technique that encompasses: an adaptive frequency tuned complex coefficient filter‐phase locked loop that provides grid frequency and phase angle information under adverse grid conditions, a modified sparrow search algorithm tuned tilt integral derivative with filter plus double integral controllers are employed to regulate the control errors under various system dynamic and disturbance conditions, fractional order incremental conductance maximum power point tracking is incorporated to efficiently track the PV peak power irrespective of atmospheric variations, a holistic fast‐acting power based energy management control employed for efficient regulation of load power and smooth out the PV power variation, and PV feedforward control dynamics to enhances system dynamics by reducing oscillations under various atmospheric conditions. The aim is to attain a smooth power transition with the grid at the unit power factor under normal and nonideal grid conditions. With reactive power injection, the control also maintains the voltage profile. During all these operations, no trade‐off occurs with the system power quality. Matlab simulations and the real time simulation test bench results under unfavorable grid circumstances demonstrate the effectiveness of the proposed method, and system harmonics are well within bounds in all the scenarios undertaken.

Developing Machine Learning-Based Intelligent Control System for Performance Optimization of Solar PV-Powered Refrigerators

Display refrigerators consume significantly high energy, and improving their efficiency is essential to minimize energy consumption and greenhouse gas emissions. Therefore, providing the refrigeration system with a reliable and energy-efficient mechanism is a real challenge. This study aims to design and evaluate an intelligent control system (ICS) using artificial neural networks (ANN) for the performance optimization of solar-powered display refrigerators (SPDRs). The SPDR was operated using the traditional control system at a fixed frequency of 60 Hz and then operated based on variable frequencies ranging from 40 to 60 Hz using the designed ANN-based ICS combined with a variable speed drive. A stand-alone PV system provided the refrigerator with the required energy at the two control options. For the performance evaluation, the operating conditions of the SPDR after the modification of its control system were compared with its performance with a traditional control system (TCS) at target refrigeration temperatures of 1, 3, and 5 °C and ambient temperatures of 23, 29, and 35 °C. Based on the controlled variable frequency speed by the modified control system (MCS), the power, energy consumption, and coefficient of performance (COP) of the SPDR are improved. The results show that both refrigeration control mechanisms maintain the same cooling temperature, but the traditional refrigerator significantly consumes more energy (p &lt; 0.05). At the same target cooling temperature, increasing the ambient temperature decreased the COP for the SPDR with both the TCS and MCS. The average daily COP of the SPDR varied from 2.8 to 3.83 and from 1.91 to 2.82 for the SPDR with the TCS and MCS, respectively. The comparison results of the two refrigerators’ conditions indicated that the developed ICS for the SPDR saved about 35.5% of the energy at the 5 °C target cooling temperature and worked with smoother power when the ambient temperature was high. The COP of the SPDR with the MCS was higher than the TCS by 26.37%, 26.59%, and 24.22% at the average daily ambient temperature of 23 °C, 29 °C, and 35 °C, respectively. The developed ANN-based control system optimized the SPDR and proved to be a suitable tool for the refrigeration industry.

Comparative Study of Grid Frequency Stability Using Flywheel-Based Variable-Speed Drive and Energy Capacitor System

Recently, there has been a rise in the integration of renewable energy sources into power grids. As a result of this, there is a need to carry out new studies in order to understand the dynamics of power grids during disturbances that is mainly caused by the stochastic nature of wind energy. The operation of modern power grids that are tied to wind farms follows a stipulated grid requirement or grid codes, considering the allowable threshold frequency variation during grid dynamics. This paper presents a comparative study of two frequency control schemes considering grid frequency stability using two frequency control topologies. A novel dynamic flywheel scheme with a doubly fed induction generator (DFIG) variable-speed wind turbine with the coordinated control of excess kinetic energy and mechanical torque during operation was the first scheme, and a control strategy of an energy capacitor system (ECS) with a squirrel cage induction generator fixed-speed wind turbine (FSWT) was the second scheme. The salient part of this study was that the DFIG maximum point power tracking for effective smoothing of the output of the wind generator in the first scheme was designed based on the control strategy of its reference power to achieve smoothing of the wind power at the terminals of the wind generator. The model system employed in this work was a wind farm that is tied to a conventional power grid made of steam and hydro synchronous turbines. For an effective and fair comparison of results, the same natural wind speed was used in PSCAD/EMTDC for both schemes. When no control, Scheme 1, and Scheme 2 were implemented, the frequency dips were 47.20, 49.99, and 49.99 Hz with overshoots of 50.500, 50.005, and 50.001 Hz and recovery times of over 600.00, 0.01, 0.01 s, respectively, for the frequency variable.

Determination of the power smoothing effect in a photovoltaic-hydrokinetic system by experimental analysis and pattern search

Sizing optimization and power smoothing methodology in highly fluctuating grid-connected renewable systems represent important challenges nowadays, the total cost and energy quality depend on the effective balance between source and load with certain restrictions to increase reliability and enhance the use of renewable sources at all scales. This article presents a novel power smoothing effect and sizing optimization methodology for a grid-connected photovoltaic-hydrokinetic system by pattern search method comparatively with three optimization algorithms encompassing a multi-objective optimization. In this context, the method considers the reduction of power fluctuations using supercapacitors, where the objective function considers technical and economic indexes. The main contribution of the research is that the objective function decreases the fluctuation suppression ratio to sizing optimization of renewable system through three pattern search size optimization algorithms. Experiments have shown that pattern search method can find the global optimum by reducing the computational effort; the Latin hypercube algorithm reduces the photovoltaic capacity by approximately 5 % and 2.3 % with respect to the Nelder Mead and genetic algorithm respectively. The influence of the supercapacitor successfully reduces power fluctuations and causes an increase in self-consumption of 32.32 %, this result represents an annual cost savings of 42 % on energy purchased from the grid. Furthermore, this paper goes further by calculating the optimal location of a hydrokinetic turbine in a river using the HEC-RAS software to determine with high precision the HKT power fluctuations as input signal to novel proposed method.

Sustainable development and applications of variable frequency transformer (VFT)

Power system interconnection is achieved by incorporating phase shifting transformers (PST) and back-to-back high voltage direct current (B2B HVDC) systems. Incorporating PSTs in an electrical power system is highly undesirable owing to its step wise variation of power transition. On the other hand, B2B HVDC systems are rarely employed in weak grids, due to their massive consumption of reactive power for device commutation. The variable frequency transformer (VFT) is capable of resolving the concerns described above by delivering improved performance on account of lower reactive power consumption besides providing smooth controllable power. This paper presents a critical review of VFT depicting its sustainable development for power system interconnection. To start with, an overview of VFT is presented followed by a brief description of other power flow controllers. These power flow controllers are compared with VFT to highlight its advantages over other conventional power flow controllers. This paper further identifies role of VFT in improving system stability and suppressing low frequency oscillations. This study also identifies the possible gaps for incorporation of VFT in power systems that have not been reported in literature and intends to serve as a useful reference for researchers working in the field of power system interconnection.

A Novel Fuzzy-Logic-Based Control Strategy for Power Smoothing in High-Wind Penetrated Power Systems and Its Validation in a Microgrid Lab

Wind power generation has undergone significant development in recent decades due to its environmental advantages and its economic competitiveness. However, its increasing level of penetration is not exempt from drawbacks, such as those derived from the fluctuating nature of the wind. To reduce its negative incidence on grid power quality and stability, different techniques have been developed, such as those based on power smoothing. In these techniques, there is a research gap on the adjustment of the time constant that adapts to the needs of the smoothing, avoiding uncertain results, computational efforts and delays in the response of the control. This paper addresses the problem, proposing a novel method for power smoothing in a wind turbine by using a fuzzy-logic-based supercapacitor storage system and time-constant fitting, with a first-order adaptive transfer function. The method considers as input variables the active power generated by the wind turbine and the state of charge of the supercapacitor, both sampled simultaneously. After a computation process, the proposal generates active power set-point values that the supercapacitor must produce to compensate for the intermittency of the wind, seen from the point of connection to the grid. The results were validated experimentally with comprehensive laboratory tests.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

Short-Term Power Load Forecasting Based on an EPT-VMD-TCN-TPA Model

Accurate short-term load forecasting is the key to ensuring smooth and efficient power system operation and power market dispatch planning. However, the nonlinear, non-stationary, and time series nature of load sequences makes load forecasting difficult. To address these problems, this paper proposes a short-term load forecasting method (EPT-VMD-TCN-TPA) based on the hybrid decomposition of load sequences, which combines ensemble patch transform (EPT), variational modal decomposition (VMD), a temporal convolutional network (TCN), and a temporal pattern attention mechanism (TPA). In which, the trend component (Tr(t)) and the residual fluctuation component (Re(t)) of the load series are extracted using EPT, and then the Re(t) component is decomposed into intrinsic modal function components (IMFs) of different frequencies using VMD. The Tr(t) and IMFs components of the fused meteorological data are predicted separately by the TCN-TPA prediction model, and finally, the prediction results of each component are reconstructed and superimposed to obtain the final predicted value of the load. In addition, experiments after reconstructing each IMF component according to the fuzzy entropy (FE) values are discussed in this paper. To evaluate the performance of the proposed method in this paper, we used datasets from two Areas of the 9th Mathematical Modeling Contest in China. The experimental results show that the predictive precision of the EPT-VMD-TCN-TPA model outperforms other comparative models. More specifically, the experimental results of the EPT-VMD-TCN-TPA method had a MAPE of 1.25% and 1.58% on Area 1 and Area 2 test sets, respectively.

Active power control strategy of DFIGs in flexible interconnected distribution network

In the development of new-type power system, the flexible interconnected distribution network becomes a better inclination. With the continuous increase of wind power generation in the flexible interconnected distribution network, the frequency stability issue caused by the high randomness of wind power generation has become increasingly prominent. This paper suggests an advanced active power strategy of double-fed induction generators (DFIGs) based on modifying power tracking curves in the interconnected distribution network for smoothing out the fluctuations of the system frequency. To this end, the various power tracking operation is used to participate in power smoothing instead of maximum power tracking operation so as to fully utilize the large rotor inertia of the double-fed induction generators for smoothing out the fluctuations of the power output of double-fed induction generators and system frequency. The control gain for the various power tracking operation is determined by the instantaneous system frequency deviation and rotor speed of the DFIG. Based on the modified IEEE 14 power system, simulation results successfully proved that the suggested advanced active power strategy is benefit for reducing the fluctuations of the output power of the DFIG and suppressing the maximum system frequency deviations with the scenario of continuously varying wind speed conditions.