Forecast of Power Generation for Grid-Connected Photo-voltaic System Based on Grey Theory and Verification Model

Being photovoltaic power generation affected by radiation strength, wind speed, clouds cover and environment temperature, the generating in each moment is fluctuating. The operational characteristics of grid-connected PV systems are coincided with gray theory application conditions. A gray theory model has been applied in short-term forecast of grid-connected photovoltaic system. The verification model of the probability of small error will help to check the accuracy of the gray forecast results. The calculated result shows that the ?model accuracy has been greatly enhanced.

Influence of Control Modes of Grid-Connected Solar Photovoltaic Generation on Grid Power Flow

Integration of Solar Photovoltaic (PV) generation into an existing distribution system has many impacts on the system, with the power flow being one of the major issues. This impact is not generic for any network, but it may manifest itself either positively or negatively, depending on the grid configuration, interface control modes, operation mode, and load profile. Grid-connected PV systems have three control options of the local voltage controller of the interface DC-AC converter. These control modes are Power Factor control, voltage control, and Droop Voltage control. This paper aims at evaluating and comparing the impacts of those control modes on the grid power flow. A set of evaluation criteria and indices is defined and mathematically formulated. Based on the requirements of the used program (Power Factory Dig Silent V14.1.3), a computation plan (algorithm) has been proposed. The algorithm has been applied to a typical weak network and a wide range of simulations has been carried out. Simulation results have been thoroughly discussed and important findings have been concluded.

Increasing the Efficiency and Level of Environmental Safety of Pro-Environmental City Heat Supply Technologies by Low Power Nuclear Plants

In connection with the current prospect of decarbonization of coal energy through the use of small nuclear power plants (SNPPs) at existing TPPs as heat sources for heat supply to municipal heating networks, there is a technological need to improve heat supply schemes to increase their environmental friendliness and efficiency. The paper proves the feasibility of using the heat-feeding mode of ASHPs for urban heat supply by heating the network water with steam taken from the turbine. The ratio of electric and thermal power of a “nuclear” combined heat and power plant is given. The advantage of using a heat pump, which provides twice as much electrical power with the same heat output, is established. Taking into account that heat in these modes is supplied with different potential, the energy efficiency was used to compare these options. To increase the heat supply capacity, a scheme with the use of a high-pressure heater in the backpressure mode and with the heating of network water with hot steam was proposed. Heat supply from ASHPs is efficient and environmentally friendly even in the case of significant remoteness of heat consumers.

Neural-Network-Based Terminal Sliding Mode Control for Frequency Stabilization of Renewable Power Systems

This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turbines is taken into account for simulation studies. The terminal sliding mode controllers are assigned in each area to achieve the LFC goal. The increasing complexity of the nonlinear power system aggravates the effects of system uncertainties. Radial basis function neural networks(RBF NNs) are designed to approximate the entire uncertainties. The terminal sliding mode controllers and the RBF NNs work in parallel to solve the LFC problem for the renewable power system. Some simulation results illustrate the feasibility and validity of the presented scheme.

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults,the conventional maximum power point tracking(MPPT)and inverter control methods of a PV power generation system cannot achieve optimal power output.They can also lead to misjudgments and poor dynamic performance.To address these issues,this paper proposes a new MPPT method of PV modules based on model predictive control(MPC)and a finite control set model predictive current control(FCS-MPCC)of an inverter.Using the identification model of PV arrays,the module-based MPC controller is designed,and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature.An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors,the optimal voltage vector is selected according to the optimal value function,and the corresponding optimal switching state is applied to power semiconductor devices of the inverter.The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified,and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink.The results show that MPC has better tracking performance under constraints,and the system has faster and more accurate dynamic response and flexibility than conventional PI control.

A Simulation Research on the Grid-Connected Control Technology of Single-Phase Inverters Based on MATLAB

This paper primarily discusses the main circuit of single-phase inverter circuits.It begins by introducing the research context and the significance of the subject,then discusses the topology of grid-connected single-phase inverter circuits,continues by discussing the control strategy for grid-connected single-phase inverter circuits,realizes a sinusoidal pulse width modulation(SPWM)signal generation circuit and an inverse control algorithm program,and finally ensures good output waveform and fast dynamic response.In view of the hysteresis feature of the grid voltage’s synchronous signal sampling circuit,the acquisition function in digital signal processing(DSP)control chips is applied,and the reasons for the hysteresis phenomenon are thoroughly investigated.The reliability of the SPWM control algorithm is revealed through the results.

Study on the Energy Dispatch Strategy of PV Power Plant

Now the energy efficiency of the PV power plant is low.For this case,this paper presents a PV power plant energy scheduling strategy.It includes new grid scheme and scheduling algorithm.Through the establishment of PV power station network model and the method of computer simulation of its scheduling algorithm,this paper describes its realization way,and then proves that the scheduling strat egy is correct and the effectiveness of improving energy conversion rate.At the same time,the PV power station scheduling strategy aslo re duces the environmental pollution,and alleviates the energy crisis and environmental crisis.

Research of Power Take-off System for “Sharp Eagle Ⅱ” Wave Energy Converter

The " Sharp Eagle” device is a wave energy converter of a hinged double floating body. The wave-absorbing floating body hinges on the semi-submerged floating body structure. Under the action of wave, the wave-absorbing floating body rotates around the hinge point, and the wave energy can be converted into kinetic energy. In this paper, the power take-off system of " Sharp Eagle Ⅱ” wave energy converter (the second generation of " Sharp Eagle”) was studied, which adopts the hydraulic type power take-off system. The 0-1 power generation mode was applied in this system to make the " Sharp Eagle Ⅱ” operate under various wave conditions. The principle of power generation was introduced in detail, and the power take-off system was simulated. Three groups of different movement period inputs were used to simulate three kinds of wave conditions, and the simulation results were obtained under three different working conditions. In addition, the prototype of " Sharp Eagle Ⅱ” wave energy converter was tested on land and in real sea conditions. The experimental data have been collected, and the experimental data and simulation results were compared and validated. This work has laid a foundation for the design and application of the following " Sharp Eagle” series of devices.

COHERENT RADIATION OF MILLIMETER WAVES GENERATED BY AN INTENSE ROTATING ANNULAR RELATIVISTIC ELECTRON BEAM

Properties of coherent radiation of millimeter waves generated by an intense rotating annularrelativistic electron beam(E-layer)which is from a cusp magnetic field are investigated.The linearizedVlasov-Maxwell equations are used to analyze the interaction between E-layer and resonators of themagnetron.The dispersion relation is deduced and numerical calculation is made.The results show that thefrequency of microwave radiation is ω_r(ω_r=lΩ〃 where Ω〃 is the electron relativistic cyclotron frequencyin the axial magnetic field;l is the azimuthal mode number,l=n+mN;N is the number of sideresonators,n=0,1,2,……N/2,m is any integer).The growth rate of radiation is still large enough even ifl is large.It is good for generating a millimeter wave radiation at low axial magnetic field.If the modes canbe controlled well,a tunable,high power millimeter wave device can be made.

Derated Mode of Power Generation in PV System Using Modified Perturb and Observe MPPT Algorithm

In a grid-integrated photovoltaic system(GIPVS),there exist issues such as surplus active power and inadequate performance of maximum power point tracking(MPPT).A surplus active power causes the overvoltage problem at the point of common coupling in low-or medium-voltage grid during the peak hours of power generation.Additionally,the inadequate performance of the MPPT algorithm results in power loss due to high settling time during the sudden change of irradiance.Therefore,to solve the surplus power problem,the curtailment of active power is suggested with improved MPPT algorithm under variable irradiance conditions.In this paper,a derated power generation mode(DPGM)control strategy is presented for the curtailment of active power.Additionally,a drift-free(named as modified)perturb and observe(P&O)technique is also proposed to improve the performance of the MPPT algorithm.Consequently,the DPGM control scheme with the intermediate boost converter shaves the surplus active power during the peak hours of power generation.Furthermore,the modified MPPT algorithm deals with the fluctuation of irradiance during non-peak hours.Thus,the proposed control scheme delivers in a more efficient system during the peak hours of power generation.In addition,it reduces the power loss and settling time during the change of irradiance for non-peak hours.Based on the proposed control scheme,a 30 kW system has been simulated in MATLAB/Simulink using Simpower tools under different environmental conditions.

Residue Theorem based soft sliding mode control for wind power generation systems

This paper proposes a residue theorem based soft sliding mode control strategy for a permanent magnet synchronous generator(PMSG)based wind power generation system(WPGS),to achieve the maximum energy conversion and improved in the system dynamic performance.The main idea is to set a soft dynamic boundary for the controlled variables around a reference point.Thus the controlled variables would lie on a point inside the boundary.The convergence of the operating point is ensured by following the Forward Euler method.The proposed control has been verified via simulation and experiments,compared with conventional sliding mode control(SMC)and proportional integral(PI)control.

Power System Flow Adjustment and Sample Generation Based on Deep Reinforcement Learning

With the increasing complexity of power system structures and the increasing penetration of renewable energy,the number of possible power system operation modes increases dramatically.It is difficult to make manual power flow adjustments to establish an initial convergent power flow that is suitable for operation mode analysis.At present,problems of low efficiency and long time consumption are encountered in the formulation of operation modes,resulting in a very limited number of generated operation modes.In this paper,we propose an intelligent power flow adjustment and generation model based on a deep network and reinforcement learning.First,a discriminator is trained to judge the power flow convergence,and the output of this discriminator is used to construct a value function.Then,the reinforcement learning method is adopted to learn a strategy for power flow convergence adjustment.Finally,a large number of convergent power flow samples are generated using the learned adjustment strategy.Compared with the traditional flow adjustment method,the proposed method has significant advantages that the learning of the power flow adjustment strategy does not depend on the parameters of the power system model.Therefore,this strategy can be automatically learned without manual intervention,which allows a large number of different operation modes to be efficiently formulated.The verification results of a case study show that the proposed method can independently learn a power flow adjustment strategy and generate various convergent power flows.

Improving contrast and sectioning power in confocal imaging by third harmonic generation in SiOx nanocrystallites

We present a new optical microscope in which the light transmitted by a sample-scanned transmission confocal microscope is frequency-tripled by SiOx nanocrystallites in lieu of being transmitted by a confocal pinhole. This imaging technique offers an increased contrast and a high scattered light rejection. It is demonstrated that the contrast close to the Sparrow resolution limit is enhanced and the sectioning power are increased with respect to the linear confocal detection mode. An experimental implementation is presented and compared with the conventional linear confocal mode.

High performance decoupled active and reactive power control for three-phase grid-tied inverters using model predictive control

Finite control set-model predictive control (FCS-MPC) is employed in this paper to control the operation of a three-phase grid-connected string inverter based on a direct PQ control scheme. The main objective is to achieve high-performance decoupled control of the active and reactive powers injected to the grid from distributed energy resources (DER).The FCS-MPC scheme instantaneously searches for and applies the optimum inverter switching state that can achieve certain goals, such as minimum deviation between reference and actual power;so that both power components (P and Q) are well controlled to their reference values.In addition, an effective method to attenuate undesired cross coupling between the P and Q control loops, which occurs only during transient operation, is investigated. The proposed method is based on the variation of the weight factors of the terms of the FCS-MPC cost function, so a higher weight factor is assigned to the cost function term that is exposed to greater disturbance. Empirical formulae of optimum weight factors as functions of the reference active and reactive power signals are proposed and mathematically derived. The investigated FCS-MPC control scheme is incorporated with the LVRT function to support the grid voltage in fulfilling and accomplishing the up-to-date grid codes. The LVRT algorithm is based on a modification of the references of active and reactive powers as functions of the instantaneous grid voltage such that suitable values of P and Q are injected to the grid during voltage sag.The performance of the elaborated FCS-MPC PQ scheme is studied under various operating scenarios, including steady-state and transient conditions. Results demonstrate the validity and effectiveness of the proposed scheme with regard to the achievement of high-performance operation and quick response of grid-tied inverters during normal and fault modes.

Novel Wind Power Grid-connection System Using Inductive Filtering Technology

Herein,a novel wind power grid-connection system based on inductive filtering is proposed to improve grid-connection compatibility,and is implemented in a 50-MW real system.First,the topology and wiring configuration of the proposed system are discussed.Thereafter,an equivalent circuit and mathematical model are established to reveal the filtering characteristics and resonance damping mechanism of the proposed system.Finally,a 50-MW wind farm-based experimental study,which is conducted to validate the effectiveness and availability of the system is discussed.The experimental results show that the main harmonics,power factor,voltage fluctuation,and flicker satisfy national standards.

Modified vector controlled DFIG wind energy system based on barrier function adaptive sliding mode control

Increased penetration of wind energy systems has serious concerns on power system stability. In spite of several advantages, doubly fed induction generator (DFIG) based wind energy systems are very sensitive to grid disturbances. DFIG system with conventional vector control is not robust to disturbances as it is based on PI controllers. The objective of this paper is to design a new vector control that is robust to external disturbances. To achieve this, inner current loop of the conventional vector control is replaced with sliding mode control. In order to avoid chattering effect and achieve finite time convergence, the control gains are selected based on positive semi-definite barrier function. The proposed barrier function adaptive sliding mode (BFASMC) is evaluated by testing it on a benchmark multi-machine power system model under various operating conditions. The simulated results show that the proposed method is robust to various disturbances.

Comparative study of three types of controllers for DFIG in wind energy conversion system

This paper presents an enhanced control strategy for Wind Energy Conversion System(WECS)using Doubly-Fed Induction Generator(DFIG).A robust Super-Twisting(STW)sliding mode control for variable speed wind turbine is developed to produce the optimal aerodynamic torque and improve the dynamic performance of the WECS.The electromagnetic torque of the DFIG is directly tracked using the proposed control to achieve maximum power extraction.The performance and the effectiveness of the STW control strategy are compared to conventional Sliding Mode(SM)and Proportional-Integral(PI)controllers.The proposed STW algorithm shows interesting features in terms of chattering reduction,finite convergence time and robustness against parameters variations and system disturbances.