Stability improvement and control of grid-connected photovoltaic system during faults using supercapacitor

Abstract

This paper describes the stability improvement of grid-connected photovoltaic (PV) system using supercapacitor (SC). The proposed technique is applied on PV system which using maximum power point tracking of perturbation and observation (P&O) algorithm. The P&O algorithm is used to extract the maximum power from the studied PV system. The effect of SC as a type of storage device on PV system appears at the abnormal conditions of grid faults. This technique is used to compensate the system parameters at different fault conditions. The control strategy of SC technique is developed for continuously charging and discharging to achieve its objective. In addition, the control system is presented in order to maintain the DC link voltage and to manage the power transit between the SC and the grid. The whole grid-connected PV system with SC energy storage system (ESS) is modeled and simulated using MATLAB/SIMULINK software and also the control system strategies are demonstrated. The effects of different fault conditions on the behaviors of studied grid-connected PV system with the SC ESS technique are investigated. A comparison between the behaviors of studied PV system in cases of without SC and with SC technique is studied. Also, the variations of DC voltage, active power, and reactive power for the studied PV system equipped without and with SC technique are investigated. The simulation results present a clear improvement for the system stability in case of using SC. Numerical results illustrate the validity of proposed technique with satisfactory values.

An Overview of Control Method with Various Crowbar Techniques of Wind Turbines during Power System Faults

“…ANFIS network is a data learning algorithm that uses the fuzzy logic system to transform the given inputs into a desired output via highly interconnected artificial neural network processing elements and information connections, which it is weighted to map the numerical inputs into output. The structure of ANFIS network is based on Takagi-Sugeno technique, thus fuzzy inference system is described by a set of fuzzy IF-THEN rules that have adapted via learning algorithm of neural network [17][18][19][20][21][22][23][24][25][26][27]. The inputs of ANFIS are the measured root mean square values of the three phase voltages and currents at DFIG-WT terminals, where these inputs are (Vabc, Iabc).…”

“…However, the different protection techniques are turned on/off via control strategy called ANFIS. The ANFIS networks depend on the number of fuzzy membership functions and the number of neurons that used for rule base to consist of the main construction of these networks [17][18][19][20][21][22][23]. The ANFIS structures have well known advantages of control and modelling for a highly non-linear system, as it combines the capability of FLC and ANN [24][25][26][27].…”

Review of PV power ramp rate control methods and their requirements

“…In a renewable energy resource dominant system, which would be called inverter do minant grid, according to their different instruction in comparison with conventional power plants, there should be additional requirements for system to control the rate of increase and decrease in output [16]. These facilities are necessary for controlling the frequency stability of the network.…”

Modeling PV installations under partial shading conditions

“…• The diode ideality factor A ref takes a value of the interval I = [1,2]. The choice based on empirical analysis (= 2 for crystaline, < 2 for amorphous)…”

“…Many research studies have focused on the impact of the grid faults on photovoltaic installation performances [1,2] and how the environment conditions (dust, temperature, irradiance, soiling) affect the produced energy [3]. High performance MPPT (Maximum Power Point Tracking) algorithms have been proposed [4][5][6][7][8] in order to solve the stated issues.…”