scholarly journals Two cases studies of Model Predictive Control approach for hybrid Renewable Energy Systems

AIMS Energy ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1241-1259
Author(s):  
Lei Liu ◽  
◽  
Takeyoshi Kato ◽  
Paras Mandal ◽  
Alexey Mikhaylov ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Model Predictive Control ◽  
Power System ◽  
Predictive Control ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
First Case ◽  
Control Scheme ◽  
Wide Range ◽  
Simulation Results

<abstract><p>This work presents a load frequency control scheme in Renewable Energy Sources(RESs) power system by applying Model Predictive Control(MPC). The MPC is designed depending on the first model parameter and then investigate its performance on the second model to confirm its robustness and effectiveness over a wide range of operating conditions. The first model is 100% RESs system with Photovoltaic generation(PV), wind generation(WG), fuel cell, seawater electrolyzer, and storage battery. From the simulation results of the first case, it shows the control scheme is efficiency. And base on the good results of the first case study, to propose a second case using a 10-bus power system of Okinawa island, Japan, to verify the efficiency of proposed MPC control scheme again. In addition, in the second case, there also applied storage devices, demand-response technique and RESs output control to compensate the system frequency balance. Last, there have a detailed results analysis to compare the two cases simulation results, and then to Prospects for future research. All the simulations of this work are performed in Matlab®/Simulink®.</p></abstract>

scholarly journals Quasi-Z-Source Four-Leg Inverter with PV by using Model Predictive Control Scheme

2019 ◽  
pp. 73-82
Author(s):  
Konda Ramanaiah ◽  
P. Rajasekhar
Keyword(s):  
Renewable Energy ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Renewable Energy Sources ◽  
Operating Conditions ◽  
Solar Irradiation ◽  
Voltage Source ◽  
Three Phase ◽  
Control Scheme ◽  
Wide Range

The Implementation of Quasi-Z-Source Four-Leg Inverter with PV by using Model Predictive Control Scheme is proposed in this paper. In order to reduce the drawbacks of traditional three phase voltage source inverter (VSI). Photovoltaic (PV) is a term which converts the light into electricity. This topology features a wide range of voltage gain which is suitable for applications in renewable energy-based power systems, where the output of the renewable energy sources varies widely with operating conditions such as wind speed, solar irradiation and temperature. To improve the capability of the controller, an MPC scheme is used which implements a discrete-time model of the system. The controller handles each phase current independently, which adds flexibility to the system. The performance of quasi z source three-phase four-leg VSI with PV by using model predictive control (MPC) was simulated using MATLAB Simulink under balanced and unbalanced load conditions as well as single-phase open-circuit fault condition.

scholarly journals Model Predictive Control of Two-Area Load Frequency Control Based Imperialist Competitive Algorithm

2015 ◽  
Vol 16 (1) ◽  
pp. 75
Author(s):  
M. Elsisi ◽  
M. A. S. Aboelela ◽  
M. Soliman ◽  
W. Mansour
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Frequency Control ◽  
Imperialist Competitive Algorithm ◽  
Pi Controller ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Competitive Algorithm ◽  
Load Frequency ◽  
Wide Range

Imperialist Competitive Algorithm (ICA) has recently been explored to develop a novel algorithm for distributed optimization and control. This paper proposes a Model Predictive Control (MPC) of Load Frequency Control (LFC) based ICA to enhance the damping of oscillations in a two-area power system. A two-area non-reheat thermal system is considered to be equipped with Model Predictive Control (MPC). ICA is utilized to search for optimal controller parameters by minimizing a time-domain based objective function. The performance of the proposed controller has been evaluated with the performance of the conventional PI controller, and  PI  controller  tuned  by  ICA in  order  to  demonstrate  the  superior efficiency of the proposed MPC tuned by ICA. Simulation results emphasis on the better performance of the optimized MPC based on ICA in compare to optimized PI controller based on ICA and conventional one over wide range of operating conditions, and system parameters variations.

scholarly journals 5G Poor and Rich Novel Control Scheme Based Load Frequency Regulation of a Two-Area System with 100% Renewables in Africa

2020 ◽  
Vol 5 (1) ◽  
pp. 2
Author(s):  
Hady H. Fayek
Keyword(s):  
Power System ◽  
Fractional Order ◽  
Packet Loss ◽  
Pid Controller ◽  
Frequency Control ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Load Frequency ◽  
Control Scheme ◽  
Non Linear

Remote farms in Africa are cultivated lands planned for 100% sustainable energy and organic agriculture in the future. This paper presents the load frequency control of a two-area power system feeding those farms. The power system is supplied by renewable technologies and storage facilities only which are photovoltaics, biogas, biodiesel, solar thermal, battery storage and flywheel storage systems. Each of those facilities has 150-kW capacity. This paper presents a model for each renewable energy technology and energy storage facility. The frequency is controlled by using a novel non-linear fractional order proportional integral derivative control scheme (NFOPID). The novel scheme is compared to a non-linear PID controller (NPID), fractional order PID controller (FOPID), and conventional PID. The effect of the different degradation factors related to the communication infrastructure, such as the time delay and packet loss, are modeled and simulated to assess the controlled system performance. A new cost function is presented in this research. The four controllers are tuned by novel poor and rich optimization (PRO) algorithm at different operating conditions. PRO controller design is compared to other state of the art techniques in this paper. The results show that the PRO design for a novel NFOPID controller has a promising future in load frequency control considering communication delays and packet loss. The simulation and optimization are applied on MATLAB/SIMULINK 2017a environment.

scholarly journals Model Predictive Control for Load Frequency Control with Wind Turbines

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Yi Zhang ◽  
Xiangjie Liu ◽  
Yujia Yan
Keyword(s):  
Model Predictive Control ◽  
Power System ◽  
Predictive Control ◽  
Wind Turbines ◽  
Optimization Problems ◽  
Load Frequency Control ◽  
Distributed Model ◽  
Load Frequency ◽  
The Impact ◽  
A Performance

Reliable load frequency (LFC) control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC) based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC) and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.

Simulation And Analysis of An Intelligent Power System Stabilizer Using Fuzzy Logic

2020 ◽  
Vol 27 (4) ◽  
pp. 70-86
Author(s):  
firas AlDurze ◽  
sura Abdullah
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Synchronous Machine ◽  
Operating Conditions ◽  
Superior Performance ◽  
Power System Stabilizer ◽  
Operation Conditions ◽  
Wide Range ◽  
Simulation Results ◽  
System Stabilizer

The basic aim of the power system stabilizer is to damp the fluctuations that occur on the rotating axis of the synchronous generator that result from noise or disturbance on the power system. This is achieved by producing an appropriate damping torque for these fluctuations across the excitation circuit of the generator and for a wide range of operation conditions. The study describes the types of power system stabilizers and giving an mathematical model of the power system that consists of a synchronous machine connected to the infinite bus though transmission lines. This has been achieved by simulating the electric and mechanical equations of power systems and proposing a methodological approach to design a Fuzzy Logic Power System Stabilize (FPSS) relaying in the design on the (Matlab/Fuzzy logic toolbox).Speed deviation (Δω) and acceleration (∆ώ) of the synchronous machine are chosen as the input signals to the fuzzy controller in order to achieve a good dynamic performance .The complete range for the variation of each of the two controller inputs is represented by a 7×7 decision table, i.e. 49 rules using proportional derivative like fuzzy logic. The power system (SMIB) was tested with the presence and absence of the excitation system, then (CPSS) was added, and then (FPSS).The simulation results of the proposed fuzzy logic on )SMIB( gave a better dynamic response, decreased the settling time and good performance of the stabilizer in damping the fluctuations that arise in the speed of rotation of the generator and its active power in various operating conditions when proposed (FPSS) is compared with conventional PSS. The simulation results proved the superior performance of the proposed (FPSS).

Robust design of power system stabilizer using bacterial foraging algorithm

2013 ◽  
Vol 62 (1) ◽  
pp. 141-152 ◽  
Author(s):  
K. Abdul Hameed ◽  
S. Palani
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Operating Conditions ◽  
Power System Stabilizer ◽  
Bacterial Foraging ◽  
Wide Range ◽  
Bacterial Foraging Algorithm ◽  
Simulation Results ◽  
The Time Domain ◽  
System Stabilizer

Abstract In this paper, a novel bacterial foraging algorithm (BFA) based approach for robust and optimal design of PID controller connected to power system stabilizer (PSS) is proposed for damping low frequency power oscillations of a single machine infinite bus bar (SMIB) power system. This paper attempts to optimize three parameters (Kp, Ki, Kd) of PID-PSS based on foraging behaviour of Escherichia coli bacteria in human intestine. The problem of robustly selecting the parameters of the power system stabilizer is converted to an optimization problem which is solved by a bacterial foraging algorithm with a carefully selected objective function. The eigenvalue analysis and the simulation results obtained for internal and external disturbances for a wide range of operating conditions show the effectiveness and robustness of the proposed BFAPSS. Further, the time domain simulation results when compared with those obtained using conventional PSS and Genetic Algorithm (GA) based PSS show the superiority of the proposed design.

scholarly journals LQR Tuning Using AIS for Frequency Oscillation Damping

2020 ◽  
Vol 3 (4) ◽  
pp. 112
Author(s):  
Muhammad Abdillah ◽  
Teguh Aryo Nugroho ◽  
Herlambang Setiadi
Keyword(s):  
Optimal Control ◽  
Power System ◽  
Clonal Selection ◽  
Dynamic Performance ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Primary Control ◽  
Frequency Oscillation ◽  
Lqr Control ◽  
Wide Range

Commonly, primary control, i.e. governor, in the generation unit had been employed to stabilize the change of frequency due to the change of electrical load during system operation. But, the drawback of the primary control was it could not return the frequency to its nominal value when the disturbance was occurred. Thus, the aim of the primary control was only stabilizing the frequency to reach its new value after there were load changes. Therefore, the LQR control is employed as a supplementary control called Load Frequency Control (LFC) to restore and keep the frequency on its nominal value after load changes occurred on the power system grid. However, since the LQR control parameters were commonly adjusted based on classical or Trial-Error Method (TEM), it was incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios. To overcome this problem, this paper proposed an Artificial Immune System (AIS) via clonal selection to automatically adjust the weighting matrices, Q and R, of LQR related to various system operating conditions changes. The efficacy of the proposed control scheme was tested on a two-area power system network. The obtained simulation results have shown that the proposed method could reduce the settling time and the overshoot of frequency oscillation, which is better than conventional LQR optimal control and without LQR optimal control.

Sign in / Sign up

Export Citation Format

Share Document