A MPC Strategy for the Optimal Management of Microgrids Based on Evolutionary Optimization

In this paper, a novel model predictive control strategy, with a 24-h prediction horizon, is proposed to reduce the operational cost of microgrids. To overcome the complexity of the optimization problems arising from the operation of the microgrid at each step, an adaptive evolutionary strategy with a satisfactory trade-off between exploration and exploitation capabilities was added to the model predictive control. The proposed strategy was evaluated using a representative microgrid that includes a wind turbine, a photovoltaic plant, a microturbine, a diesel engine, and an energy storage system. The achieved results demonstrate the validity of the proposed approach, outperforming a global scheduling planner-based on a genetic algorithm by 14.2% in terms of operational cost. In addition, the proposed approach also better manages the use of the energy storage system.Ministerio de Economía y Competitividad DPI2016-75294-C2-2-RUnión Europea (Programa Horizonte 2020) 76409

Model predictive control for microgrid functionalities: review and future challenges

ABSTRACT: Renewable generation and energy storage systems are technologies which evoke the future energy paradigm. While these technologies have reached their technological maturity, the way they are integrated and operated in the future smart grids still presents several challenges. Microgrids appear as a key technology to pave the path towards the integration and optimized operation in smart grids. However, the optimization of microgrids considered as a set of subsystems introduces a high degree of complexity in the associated control problem. Model Predictive Control (MPC) is a control methodology which has been satisfactorily applied to solve complex control problems in the industry and also currently it is widely researched and adopted in the research community. This paper reviews the application of MPC to microgrids from the point of view of their main functionalities, describing the design methodology and the main current advances. Finally, challenges and future perspectives of MPC and its applications in microgrids are described and summarized.info:eu-repo/semantics/publishedVersio

Model Predictive Control Design for the Secondary Frequency Control of Microgrid Considering Time Delay Attacks

Fast depleting fossil fuels and growing awareness of environmental protection have raised worldwide concerns, aiming to build a sustainable and smart energy ecosystem. Renewable energy generation plays an important role in providing clean power supply. However, the integration of a bulk renewable generation system would also introduce new forms of disturbances and uncertainties to impact the power quality, threatening the secure operation of the distribution network. Microgrid, as an emerging technology, is quite appealing to be interfaced with distribution systems due to its potential economic, environmental, and technical benefits. The microgrid differs from the “smart grid” with different control strategies to accomplish the goal of helping the power grid with load balancing and voltage control and assisting power markets. A hierarchical control structure for the microgrid is commonly designed to address all above issues both in islanded mode and grid-connected mode. On the other hand, concerns about cybersecurity threats in the microgrid are steadily rising, and enormous number of economic losses would occur if defense strategies are not stipulated and carried out. In the modern power system, distributed control system, intelligent measuring devices and Internet of Things (IoT) are highly recommended in microgrid systems, which lead to the vulnerability of communication channels. Cyber threats such as false data injection (FDI) attacks, denial of service (DoS) attacks, and time-delay switch attacks (TDS) can be effortlessly implemented through information and communication centers, compromising the secure operation of power systems. By theoretically analyzing the AC microgrid simulation model, the MPC control strategies, and the modified MPC method based on GCC estimation will be studied in this thesis. In the second chapter, this thesis summarizes the start-art-of microgrid control, introducing a hierarchical control structure: primary control, secondary control, and tertiary control. These control levels differ in their speed of response, the time frame in which they operate, and infrastructure requirements. We focus on the centralized secondary frequency control system, which compensates the frequency deviation caused by primary control—P/f method. Then, in Chapter 3, the isolated AC MG frequency control system including WTG, DEG, PV panel and energy storage system with MPC controller is modeled. Three case studies are designed in MATLAB/Simulink to illustrate the advantages of the MPC method compared with the traditional PI controller. In the next Chapter, since state estimation based on precise status feedback of the system components is essential for the MPC controller to calculate corresponding control signal, the status feedback attack to BESS and FESS is considered. Correspondingly, an online status switching method is proposed to detect the original statuses of BESS and FESS, updating the state estimation function to obtain desirable performance of frequency regulation. Last, considering the time delay attack hacked by the adversary in the sensor, a modified MPC method based on GCC estimation is proposed to detect and track time delay attacks online. The model of proposed method to regulate frequency deviation is built in MATLAB. There are three case studies in this part: a constant time-delay attack with 0.1 pu load increase; a time-varying delay attack with 0.1 pu load increase; and a time-varying delay attack with changing load disturbance. By analyzing results of three cases, the effectiveness of the modified MPC method is proved

Model Predictive Control Design for the Secondary Frequency Control of Microgrid Considering Time Delay Attacks

Fast depleting fossil fuels and growing awareness of environmental protection have raised worldwide concerns, aiming to build a sustainable and smart energy ecosystem. Renewable energy generation plays an important role in providing clean power supply. However, the integration of a bulk renewable generation system would also introduce new forms of disturbances and uncertainties to impact the power quality, threatening the secure operation of the distribution network. Microgrid, as an emerging technology, is quite appealing to be interfaced with distribution systems due to its potential economic, environmental, and technical benefits. The microgrid differs from the “smart grid” with different control strategies to accomplish the goal of helping the power grid with load balancing and voltage control and assisting power markets. A hierarchical control structure for the microgrid is commonly designed to address all above issues both in islanded mode and grid-connected mode. On the other hand, concerns about cybersecurity threats in the microgrid are steadily rising, and enormous number of economic losses would occur if defense strategies are not stipulated and carried out. In the modern power system, distributed control system, intelligent measuring devices and Internet of Things (IoT) are highly recommended in microgrid systems, which lead to the vulnerability of communication channels. Cyber threats such as false data injection (FDI) attacks, denial of service (DoS) attacks, and time-delay switch attacks (TDS) can be effortlessly implemented through information and communication centers, compromising the secure operation of power systems. By theoretically analyzing the AC microgrid simulation model, the MPC control strategies, and the modified MPC method based on GCC estimation will be studied in this thesis. In the second chapter, this thesis summarizes the start-art-of microgrid control, introducing a hierarchical control structure: primary control, secondary control, and tertiary control. These control levels differ in their speed of response, the time frame in which they operate, and infrastructure requirements. We focus on the centralized secondary frequency control system, which compensates the frequency deviation caused by primary control—P/f method. Then, in Chapter 3, the isolated AC MG frequency control system including WTG, DEG, PV panel and energy storage system with MPC controller is modeled. Three case studies are designed in MATLAB/Simulink to illustrate the advantages of the MPC method compared with the traditional PI controller. In the next Chapter, since state estimation based on precise status feedback of the system components is essential for the MPC controller to calculate corresponding control signal, the status feedback attack to BESS and FESS is considered. Correspondingly, an online status switching method is proposed to detect the original statuses of BESS and FESS, updating the state estimation function to obtain desirable performance of frequency regulation. Last, considering the time delay attack hacked by the adversary in the sensor, a modified MPC method based on GCC estimation is proposed to detect and track time delay attacks online. The model of proposed method to regulate frequency deviation is built in MATLAB. There are three case studies in this part: a constant time-delay attack with 0.1 pu load increase; a time-varying delay attack with 0.1 pu load increase; and a time-varying delay attack with changing load disturbance. By analyzing results of three cases, the effectiveness of the modified MPC method is proved

Control and management of energy storage systems in microgrids

The rate of integration of the renewable energy sources in modern grids have significantly increased in the last decade. These intermittent, non-dispatchable renewable sources, though environment friendly tend to be grid unfriendly. This is precisely due to the issues pertaining to grid congestion, voltage regulation and stability of grids being reported as a result of the incorporation of renewable sources. In this scenario, the use of energy storage systems (ESS ) in electric grids is being widely proposed to overcome these issues. However, integrating energy storage systems alone will not compensate for the issue created by renewable generation. The control and management of the ESS should be done optimally so that their full capabilities are exploited to overcome the issues in the power grids and to ensure their lower cost of investment by prolonging ESS lifetime through minimising degradation. Motivated by this aspect this Ph.D work focusses on developing an efficient, optimal control and management strategy for ESS in a microgrid, especially hybrid ESS. The Ph.D work addresses this issue by proposing a hierarchical control scheme comprising of a lower power management and higher energy management stage with contributions in each stage. In the power management stage this work focusses on improving aspects of real time control of power converters interfacing ESS to grid and the microgrid system as whole. The work proposes control systems with improved dynamic behaviour for power converters based on the reset control framework. In the microgrid control the work presents a primary+secondary control scheme with improved voltage regulation performance under disturbances, using an observer. The real time power splitting strategies among hybrid ESS accounting for the ESS operating efficiencies and degradation mechanisms will also be addressed in the primary+secondary control of power management stage. The design criteria, stability and robustness analysis will be carried out, along with simulation or experimental verifications. In the higher level energy management stage, the contribution of this work involves application of an economic MPC framework for the management of ESS in microgrids. The work specifically addresses the problems of mitigating grid congestion from renewable power feed-in, minimising ESS degradation and maximising self consumption of generated renewable energy using the MPC based energy management system. A survey of the forecasting methods that can be used for MPC will be carried out and a neural network based forecasting unit for time series prediction will be developed. The practical issue of accounting for forecasting error in the decision making of MPC will be addressed and impact of the resulting conservative decision making on the system performance will be analysed. The improvement in performance with the proposed energy management scheme will be demonstrated and quantified.La integración de las fuentes de energía renovables en las redes modernas ha aumentado significativamente en la última década. Estas fuentes renovables, aunque muy convenientes para el medio ambiente son de naturaleza intermitente, y son no panificables, cosa que genera problemas en la red de distribución. Esto se debe precisamente a los problemas relacionados con la congestión de la red y la regulación del voltaje. En este escenario, el uso de sistemas de almacenamiento de energía (ESS) en redes eléctricas está siendo ampliamente propuesto para superar estos problemas. Sin embargo, la integración de sistemas de almacenamiento de energía por sí solos no compensará el problema creado por la generación renovable. El control y la gestión del ESS deben realizarse de manera óptima, de modo que se aprovechen al máximo sus capacidades para superar los problemas en las redes eléctricas, garantizar un coste de inversión razonable y prolongar la vida útil del ESS minimizando su degradación. Motivado por esta problemática, esta tesis doctoral se centra en desarrollar una estrategia de control y gestión eficiente para los ESS integrados en una microrred, especialmente cuando se trata de ESS de naturaleza. El trabajo de doctorado propone un esquema de control jerárquico compuesto por un control de bajo nivel y una parte de gestión de energía operando a más alto nivel. El trabajo realiza aportaciones en los dos campos. En el control de bajo nivel, este trabajo se centra en mejorar aspectos del control en tiempo real de los convertidores que interconectan el ESS con la red y el sistema de micro red en su conjunto. El trabajo propone sistemas de control con comportamiento dinámico mejorado para convertidores de potencia desarrollados en el marco del control de tipo reset. En el control de microrred, el trabajo presenta un esquema de control primario y uno secundario con un rendimiento de regulación de voltaje mejorado bajo perturbaciones, utilizando un observador. Además, el trabajo plantea estrategias de reparto del flujo de potencia entre los diferentes ESS. Durante el diseño de estos algoritmos de control se tienen en cuenta los mecanismos de degradación de los diferentes ESS. Los algoritmos diseñados se validarán mediante simulaciones y trabajos experimentales. En el apartado de gestión de energía, la contribución de este trabajo se centra en la aplicación del un control predictivo económico basado en modelo (EMPC) para la gestión de ESS en microrredes. El trabajo aborda específicamente los problemas de mitigar la congestión de la red a partir de la alimentación de energía renovable, minimizando la degradación de ESS y maximizando el autoconsumo de energía renovable generada. Se ha realizado una revisión de los métodos de predicción del consumo/generación que pueden usarse en el marco del EMPC y se ha desarrollado un mecanismo de predicción basado en el uso de las redes neuronales. Se ha abordado el análisis del efecto del error de predicción sobre el EMPC y el impacto que la toma de decisiones conservadoras produce en el rendimiento del sistema. La mejora en el rendimiento del esquema de gestión energética propuesto se ha cuantificado.La integració de les fonts d'energia renovables a les xarxes modernes ha augmentat significativament en l’última dècada. Aquestes fonts renovables, encara que molt convenients per al medi ambient són de naturalesa intermitent, i són no panificables, cosa que genera problemes a la xarxa de distribució. Això es deu precisament als problemes relacionats amb la congestió de la xarxa i la regulació de la tensió. En aquest escenari, l’ús de sistemes d'emmagatzematge d'energia (ESS) en xarxes elèctriques està sent àmpliament proposat per superar aquests problemes. No obstant això, la integració de sistemes d'emmagatzematge d'energia per si sols no compensarà el problema creat per la generació renovable. El control i la gestió de l'ESS s'han de fer de manera _optima, de manera que s'aprofitin al màxim les seves capacitats per superar els problemes en les xarxes elèctriques, garantir un cost d’inversió raonable i allargar la vida útil de l'ESS minimitzant la seva degradació. Motivat per aquesta problemàtica, aquesta tesi doctoral es centra a desenvolupar una estratègia de control i gestió eficient per als ESS integrats en una microxarxa, especialment quan es tracta d'ESS de natura híbrida. El treball de doctorat proposa un esquema de control jeràrquic compost per un control de baix nivell i una part de gestió d'energia operant a més alt nivell. El treball realitza aportacions en els dos camps. En el control de baix nivell, aquest treball es centra a millorar aspectes del control en temps real dels convertidors que interconnecten el ESS amb la xarxa i el sistema de microxarxa en el seu conjunt. El treball proposa sistemes de control amb comportament dinàmic millorat per a convertidors de potència desenvolupats en el marc del control de tipus reset. En el control de micro-xarxa, el treball presenta un esquema de control primari i un de secundari de regulació de voltatge millorat sota pertorbacions, utilitzant un observador. A més, el treball planteja estratègies de repartiment de el flux de potència entre els diferents ESS. Durant el disseny d'aquests algoritmes de control es tenen en compte els mecanismes de degradació dels diferents ESS. Els algoritmes dissenyats es validaran mitjanant simulacions i treballs experimentals. En l'apartat de gestió d'energia, la contribució d'aquest treball se centra en l’aplicació de l'un control predictiu econòmic basat en model (EMPC) per a la gestió d'ESS en microxarxes. El treball aborda específicament els problemes de mitigar la congestió de la xarxa a partir de l’alimentació d'energia renovable, minimitzant la degradació d'ESS i maximitzant l'autoconsum d'energia renovable generada. S'ha realitzat una revisió dels mètodes de predicció del consum/generació que poden usar-se en el marc de l'EMPC i s'ha desenvolupat un mecanisme de predicció basat en l’ús de les xarxes neuronals. S'ha abordat l’anàlisi de l'efecte de l'error de predicció sobre el EMPC i l'impacte que la presa de decisions conservadores produeix en el rendiment de el sistema. La millora en el rendiment de l'esquema de gestió energètica proposat s'ha quantificat

Advanced Primary Controllers for Inverter Based Power Sources: Microgrids and Wind Power Plants

The aim of this doctoral thesis is to present the research activity fulfilled during the Ph.D. studies. The research project of the candidate was focused on two main cores. The first core is centred in the microgrid area; in particular in islanded microgrid modelling and control. Firstly, the model was compared with experimental results collected in some facilities available at University of Genoa. Then traditional controllers for islanded microgrid are analysed and explored, proposing a new stability estimation procedure for droop controlled microgrid. Finally, a new control strategy based on Model Predictive Control (MPC) is proposed in order to collect many functionalities in just one control layer. MPC is widely used in MG environment, but just for power and energy management at tertiary level; instead here it is here proposed with an inedited use. Some experimental validations about this new methodology are obtained during a research period in Serbia and Denmark. The second core is related with synthetic inertia for wind turbine connected to the main grid, i.e. frequency support during under-frequency transients. This aspect is very important today because it represents a way to increase grid stability in low inertia power systems. The importance of this feature is shared by all the most important Transmitter System Operators (TSO) all over the world

Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids

[EN] Microgrids have emerged as a solution to address new challenges in power systems with the integration of distributed energy resources (DER). Inverter-based microgrids (IBMG) need to implement proper control systems to avoid stability and reliability issues. Thus, several researchers have introduced multi-objective control strategies for distributed generation on IBMG. This paper presents a review of the different approaches that have been proposed by several authors of multi-objective control. This work describes the main features of the inverter as a key component of microgrids. Details related to accomplishing efficient generation from a control systems' view have been observed. This study addresses the potential of multi-objective control to overcome conflicting objectives with balanced results. Finally, this paper shows future trends in control objectives and discussion of the different multi-objective approaches.Gonzales-Zurita, Ó.; Clairand, J.; Peñalvo-López, E.; Escrivá-Escrivá, G. (2020). Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids. Energies. 13(13):1-29. https://doi.org/10.3390/en13133483S1291313Ross, M., Abbey, C., Bouffard, F., & Joos, G. (2015). Multiobjective Optimization Dispatch for Microgrids With a High Penetration of Renewable Generation. IEEE Transactions on Sustainable Energy, 6(4), 1306-1314. doi:10.1109/tste.2015.2428676Murty, V. V. S. N., & Kumar, A. (2020). Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems. Protection and Control of Modern Power Systems, 5(1). doi:10.1186/s41601-019-0147-zKatircioğlu, S., Abasiz, T., Sezer, S., & Katırcıoglu, S. (2019). 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An inclusive methodology for Plug-in electrical vehicle operation with G2V and V2G in smart microgrid environments. International Journal of Electrical Power & Energy Systems, 102, 312-323. doi:10.1016/j.ijepes.2018.04.037Ghosh, S., & Chattopadhyay, S. (2020). Three-Loop-Based Universal Control Architecture for Decentralized Operation of Multiple Inverters in an Autonomous Grid-Interactive Microgrid. IEEE Transactions on Industry Applications, 56(2), 1966-1979. doi:10.1109/tia.2020.2964746Mohapatra, S. R., & Agarwal, V. (2020). Model Predictive Control for Flexible Reduction of Active Power Oscillation in Grid-Tied Multilevel Inverters Under Unbalanced and Distorted Microgrid Conditions. IEEE Transactions on Industry Applications, 56(2), 1107-1115. doi:10.1109/tia.2019.2957480Ziouani, I., Boukhetala, D., Darcherif, A.-M., Amghar, B., & El Abbassi, I. (2018). Hierarchical control for flexible microgrid based on three-phase voltage source inverters operated in parallel. International Journal of Electrical Power & Energy Systems, 95, 188-201. doi:10.1016/j.ijepes.2017.08.027Golshannavaz, S., & Mortezapour, V. (2018). A generalized droop control approach for islanded DC microgrids hosting parallel-connected DERs. Sustainable Cities and Society, 36, 237-245. doi:10.1016/j.scs.2017.09.038Safa, A., Madjid Berkouk, E. L., Messlem, Y., & Gouichiche, A. (2018). A robust control algorithm for a multifunctional grid tied inverter to enhance the power quality of a microgrid under unbalanced conditions. International Journal of Electrical Power & Energy Systems, 100, 253-264. doi:10.1016/j.ijepes.2018.02.042Andishgar, M. H., Gholipour, E., & Hooshmand, R. (2017). An overview of control approaches of inverter-based microgrids in islanding mode of operation. Renewable and Sustainable Energy Reviews, 80, 1043-1060. doi:10.1016/j.rser.2017.05.267Li, Z., Zang, C., Zeng, P., Yu, H., Li, S., & Bian, J. (2017). 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Microgrids Power Quality Enhancement Using Model Predictive Control

In electric power systems, any deviation with respect to the theoretical sinusoidal waveform is considered to be a disturbance in the power quality of the electrical grid. The deviation can alter any of the parameters of the waveform: frequency, amplitude, and symmetry among phases. Microgrid, as a part of the electric power system, has to contribute providing an adequate current waveform in grid connected-mode, as well as to guarantee similar voltage features than the standard requirement given for public distribution grids under normal exploitation conditions in islanded mode. Adequate power quality supply is necessary for the correct compatibility between all the devices connected to the same grid. In this paper, the power quality of microgrids is managed using a Model Predictive Control (MPC) methodology which regulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the following microgrids working modes: grid-connected, islanded, and interconnected. The simulation results demonstrate that the proposed methodology improves the transient response in comparison with classical methods in all the working modes, minimizing the harmonic content in the current and the voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems