Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

Wang, Huan; Zeng, Guo‐Qiang; Dai, Yuxing; Bi, Dongxue; Sun, Jinsheng; Xie, Xiaoyun

doi:10.3390/en10101502

Cited by 75 publications

(46 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, from the theoretical perspective, the optimal design issue of the weighting vectors, prediction horizon and control horizon in the proposed MPC method is still challenging. From the perspective of engineering practice, the proposed method will be further studied in depth by tuning the weighting vectors, prediction horizon and control horizon based on evolutionary algorithms, such as multi-objective optimization algorithms [46][47][48]. On the other hand, the extension of MPC to more complex power systems by taking into account the robust control performance indices [45] and real-time predictive power of renewable energy systems [49] is another significant subject of future investigation.…”

Section: Discussionmentioning

confidence: 99%

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

2017

View full text Add to dashboard Cite

Abstract:As the penetration level of renewable distributed generations such as wind turbine generator and photovoltaic stations increases, the load frequency control issue of a multi-area interconnected power system becomes more challenging. This paper presents an adaptive model predictive load frequency control method for a multi-area interconnected power system with photovoltaic generation by considering some nonlinear features such as a dead band for governor and generation rate constraint for steam turbine. The dynamic characteristic of this system is formulated as a discrete-time state space model firstly. Then, the predictive dynamic model is obtained by introducing an expanded state vector, and rolling optimization of control signal is implemented based on a cost function by minimizing the weighted sum of square predicted errors and square future control values. The simulation results on a typical two-area power system consisting of photovoltaic and thermal generator have demonstrated the superiority of the proposed model predictive control method to these state-of-the-art control techniques such as firefly algorithm, genetic algorithm, and population extremal optimization-based proportional-integral control methods in cases of normal conditions, load disturbance and parameters uncertainty.

show abstract

Section: Discussionmentioning

confidence: 99%

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

2017

View full text Add to dashboard Cite

show abstract

“…Another non-linear controller, which is called an optimized fractional-order proportional-integral-derivative (FOPID), has been proposed to regulate active power injection of fuel cell due to more satisfactory performance of this controller in comparison to the traditional ones. The outcome of mentioned research shows that the proposed controller provide a faster response and small overshoot compared to established controllers [14]. Recently, the tendency to deploy algorithm-based non-integer controller during load frequency control of microgrids have increased dramatically.…”

Section: Introductionmentioning

confidence: 89%

Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid

2020

View full text Add to dashboard Cite

In recent years, residential rate consumptions have increased due to modern appliances which require a high level of electricity demands. Although mentioned appliances can improve the quality of consumers’ lives to a certain extent, they suffer from various shortcomings including raising the electricity bill as well as serious technical issues such as lack of balance between electricity generation and load disturbances. This imbalance can generally lead to the frequency excursion which is a significant concern, especially for low-inertia microgrids with unpredictable parameters. This research proposes an intelligent combination of two approaches in order to alleviate challenges related to the frequency control mechanism. Firstly, a learning-based fractional-order proportional-integral-derivative (FOPID) controller is trained by recurrent adaptive neuro-fuzzy inference (RANFIS) in the generation side during various operational conditions and climatic changes. In the following, a decentralized demand response (DR) programming in the load side is introduced to minimize consumption rate through controllable appliances and energy storage systems (ESSs). Furthermore, parameters uncertainties and time delay, which are generally known as two main concerns of isolated microgrids, are regarded in the frequency plan of a low-inertia microgrid including renewable energy sources (RESs), and energy storage systems (ESSs). Simulation results are illustrated in three different case studies in order to compare the performance of the proposed two methods during various operational conditions. It is obvious that the frequency deviation of microgrid can be improved by taking advantage of intelligent combination of both DR program and modern control mechanism.

show abstract

“…genetic algorithm, extremal optimization and predictive control strategies) and related multi-objective optimization algorithms have been adopted prevalently for the design of optimal PI/PID and FO PI/PID controllers. [17][18][19][20][21][22] As dynamic and/or households loads can represent a high proportion of the total load in BIPv/Wt system, the problem with power quality is a particular concern. 23 For grid-on building-integrated hybrid PV/WT renewable systems, the maximum load voltage and current THD allowed is 5% which is the main determinant of the power quality assessment.…”

Section: Introductionmentioning

confidence: 99%

Application of fractional-order voltage controller in building-integrated photovoltaic and wind turbine system

Gül

Tan

2019

Measurement and Control

View full text Add to dashboard Cite

The share of electricity generation based on clean, inexhaustible and continuous energy sources, such as solar and wind, in total energy production, is rising day by day due to its significant advantages such as having the less negative impact on global climate and environmental pollution and not requiring fuel for energy production. It is reported that commercial and residential buildings correspond to about 20.1% of the world energy consumption, so it is necessary to provide energy needs of buildings with hybrid renewable energy systems. When using non-continuous energy sources such as solar panel and wind turbines, it is important to ensure ensuring a stable and quality power flow to the building while the power demands of building show very sharp variability. This work presents a voltage control system using fractional-order operators in the smart residential building-integrated hybrid renewable power plant (solar + wind). In this research article, fractional-order proportional–integral/proportional–integral–derivative controllers are proposed on a synchronous frame for a pulse-width modulation based three-phase voltage source inverter in residential building-integrated solar panel and wind turbines system (building-integrated photovoltaic/wind turbine system) in order to improve the quality of injected voltage to building. When comparing the effect of closed-loop voltage control system with integer order controllers (proportional–integral and proportional–integral–derivative) on the power quality at the building distribution by analyzing the simulation results for proposed case study, use of fractional-order voltage controllers for nonlinear system such as building integrated with hybrid renewable sources is more suitable than using integer order voltage controllers.

show abstract

Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

Cited by 75 publications

References 37 publications

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid

Application of fractional-order voltage controller in building-integrated photovoltaic and wind turbine system

Contact Info

Product

Resources

About