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http://hdl.handle.net/10985/17726
Laboratory Demonstration of a Multiterminal VSC-HVDC Power Grid
AMAMRA, Sid-Ali; COLAS, Frédéric; GUILLAUD, Xavier; RAULT, Pierre; NGUEFEU, Samuel
This paper presents the design, development, con- trol and supervision of a hardware-based laboratory Multi- Terminal-Direct-Current (MTDC) test-bed. This work is a part of the TWENTIES (Transmission system operation with large penetration of Wind and other renewable Electricity sources in Networks by means of innovative Tools and Integrated Energy Solutions) DEMO 3 European project which aims to demonstrate the feasibility of a DC grid through experimental tests. This is a hardware-in-the-loop DC system test-bed with simulated AC systems in real time simulation; the DC cables and some converters are actual, at laboratory scale. The laboratory scale test-bed is homothetic to a full scale high voltage direct current (HVDC) system: electrical elements are the same in per unit. The test-bed is supervised by a Supervisory Control And Data Acquisition (SCADA) system based on PcVue. Primary control based droop control method to provide DC grid power balance and coordinated control methods to dispatch power as scheduled by transmission system operator (TSO) are implemented. Since primary control acts as converter level by using local measure- ments, a coordinated control is proposed to manage the DC grid power flow. The implemented system is innovative and achievable for real-time, real-world MTDC-HVDC grid applications.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/177262017-01-01T00:00:00ZAMAMRA, Sid-AliCOLAS, FrédéricGUILLAUD, XavierRAULT, PierreNGUEFEU, SamuelThis paper presents the design, development, con- trol and supervision of a hardware-based laboratory Multi- Terminal-Direct-Current (MTDC) test-bed. This work is a part of the TWENTIES (Transmission system operation with large penetration of Wind and other renewable Electricity sources in Networks by means of innovative Tools and Integrated Energy Solutions) DEMO 3 European project which aims to demonstrate the feasibility of a DC grid through experimental tests. This is a hardware-in-the-loop DC system test-bed with simulated AC systems in real time simulation; the DC cables and some converters are actual, at laboratory scale. The laboratory scale test-bed is homothetic to a full scale high voltage direct current (HVDC) system: electrical elements are the same in per unit. The test-bed is supervised by a Supervisory Control And Data Acquisition (SCADA) system based on PcVue. Primary control based droop control method to provide DC grid power balance and coordinated control methods to dispatch power as scheduled by transmission system operator (TSO) are implemented. Since primary control acts as converter level by using local measure- ments, a coordinated control is proposed to manage the DC grid power flow. The implemented system is innovative and achievable for real-time, real-world MTDC-HVDC grid applications.Convex formulation of confidence level optimization of DG affine reactive power controllers in distribution grids
http://hdl.handle.net/10985/17728
Convex formulation of confidence level optimization of DG affine reactive power controllers in distribution grids
BUIRE, Jérôme; DIEULOT, Jean-Yves; COLAS, Frédéric; GUILLAUD, Xavier; DE ALVARO, Léticia
Volatile productions and consumptions generate a stochastic behavior of distribution grids and make its supervision difficult to achieve. Usually, the Distributed Generators reactive powers are adjusted to perform decentralized voltage control. Industrial controllers are generally equipped with a local affine feedback law, which settings are tuned at early stage using local data. A centralized and more efficient tuning method should aim to maximize the probability that all the node voltages of distribution grids remain within prescribed bounds. When the characteristics of the stochastic power forecasts are known, the centralized algorithm allows to update the settings on a regular time basis. However, the method requires to solve stochastic optimization problem. Assuming that stochastic variables have Gaussian distributions, a procedure is given which guarantees the convergence of the stochastic optimization. Convex problems drastically reduce the difficulty and the computational time required to reach the global minimum, compared to nonconvex optimal power flow problems. The linear controllers with optimized parameters are compared to traditional control laws using simulations of a real distribution grid model. The results show that the algorithm is reliable and moreover fast enough. Hence, the proposed method can be used to update periodically the control parameters.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10985/177282020-01-01T00:00:00ZBUIRE, JérômeDIEULOT, Jean-YvesCOLAS, FrédéricGUILLAUD, XavierDE ALVARO, LéticiaVolatile productions and consumptions generate a stochastic behavior of distribution grids and make its supervision difficult to achieve. Usually, the Distributed Generators reactive powers are adjusted to perform decentralized voltage control. Industrial controllers are generally equipped with a local affine feedback law, which settings are tuned at early stage using local data. A centralized and more efficient tuning method should aim to maximize the probability that all the node voltages of distribution grids remain within prescribed bounds. When the characteristics of the stochastic power forecasts are known, the centralized algorithm allows to update the settings on a regular time basis. However, the method requires to solve stochastic optimization problem. Assuming that stochastic variables have Gaussian distributions, a procedure is given which guarantees the convergence of the stochastic optimization. Convex problems drastically reduce the difficulty and the computational time required to reach the global minimum, compared to nonconvex optimal power flow problems. The linear controllers with optimized parameters are compared to traditional control laws using simulations of a real distribution grid model. The results show that the algorithm is reliable and moreover fast enough. Hence, the proposed method can be used to update periodically the control parameters.Coordinated control of active distribution networks to help a transmission system in emergency situation
http://hdl.handle.net/10985/17722
Coordinated control of active distribution networks to help a transmission system in emergency situation
MORIN, J.; COLAS, Frédéric; DIEULOT, Jean-Yves; GRENARD, S.; GUILLAUD, Xavier
This paper addresses the relevance of using reactive power from Medium Voltage (MV) networks to support the voltages of a High Voltage (HV) rural network in real-time. The selection and analysis of different optimal coordination strategies between the HV and several MV grids is investigated. The algorithms will control the reactive powers that can flow between HV/MV networks after a request from the Transmission Network Operator in case of an emergency situation such as a line outage. From a case study, the relevance of the coordination is enlightened and recommendations are given on how to tune and to combine the optimal algorithms with the advanced Volt Var Controllers of the distribution grids.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/177222018-01-01T00:00:00ZMORIN, J.COLAS, FrédéricDIEULOT, Jean-YvesGRENARD, S.GUILLAUD, XavierThis paper addresses the relevance of using reactive power from Medium Voltage (MV) networks to support the voltages of a High Voltage (HV) rural network in real-time. The selection and analysis of different optimal coordination strategies between the HV and several MV grids is investigated. The algorithms will control the reactive powers that can flow between HV/MV networks after a request from the Transmission Network Operator in case of an emergency situation such as a line outage. From a case study, the relevance of the coordination is enlightened and recommendations are given on how to tune and to combine the optimal algorithms with the advanced Volt Var Controllers of the distribution grids.Confidence Level Optimization of DG Piecewise Affine Controllers in Distribution Grids
http://hdl.handle.net/10985/17725
Confidence Level Optimization of DG Piecewise Affine Controllers in Distribution Grids
BUIRE, Jerome; COLAS, Frédéric; DIEULOT, Jean-Yves; DE ALVARO, Leticia; GUILLAUD, Xavier
Distributed generators (DGs) reactive powers are controlled to mitigate voltage overshoots in distribution grids with stochastic power production and consumption. Classical DGs controllers may embed piecewise affine laws with dead-band terms. Their settings are usually tuned using a decentralized method which uses local data and optimizes only the DG node behavior. It is shown that when short-term forecasts of stochastic powers are Gaussian and the grid model is assumed to be linear, nodes voltages can either be approximated by Gaussian or sums of truncated Gaussian variables. In the latter case, the voltages probability density functions (pdf) that are needed to compute the overvoltage risks or DG control effort are less straightforward than for normal distributions. These pdf are used into a centralized optimization problem which tunes all DGs control parameters. The objectives consist in maximizing the confidence levels for which voltages and powers remain in prescribed domains and minimizing voltage variances and DG efforts. Simulations on a real distribution grid model show that the truncated Gaussian representation is relevant and that control parameters can easily be updated even when extra DGs are added to the grid. The DG reactive power can be reduced down to 50% or node voltages variances can be reduced down to 30%.
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/10985/177252019-01-01T00:00:00ZBUIRE, JeromeCOLAS, FrédéricDIEULOT, Jean-YvesDE ALVARO, LeticiaGUILLAUD, XavierDistributed generators (DGs) reactive powers are controlled to mitigate voltage overshoots in distribution grids with stochastic power production and consumption. Classical DGs controllers may embed piecewise affine laws with dead-band terms. Their settings are usually tuned using a decentralized method which uses local data and optimizes only the DG node behavior. It is shown that when short-term forecasts of stochastic powers are Gaussian and the grid model is assumed to be linear, nodes voltages can either be approximated by Gaussian or sums of truncated Gaussian variables. In the latter case, the voltages probability density functions (pdf) that are needed to compute the overvoltage risks or DG control effort are less straightforward than for normal distributions. These pdf are used into a centralized optimization problem which tunes all DGs control parameters. The objectives consist in maximizing the confidence levels for which voltages and powers remain in prescribed domains and minimizing voltage variances and DG efforts. Simulations on a real distribution grid model show that the truncated Gaussian representation is relevant and that control parameters can easily be updated even when extra DGs are added to the grid. The DG reactive power can be reduced down to 50% or node voltages variances can be reduced down to 30%.Grid Connected Inverter Behavior with an Output LC Filter under Voltage Sag Operation
http://hdl.handle.net/10985/6314
Grid Connected Inverter Behavior with an Output LC Filter under Voltage Sag Operation
SALHA, Fouad; COLAS, Frédéric; GUILLAUD, Xavier
The aim of this paper is to propose an over current limitation and voltage control strategy for a grid connected inverter with a LC output filter used in distributed generation and in case of voltage sag. This strategy relies on the control of LC output filter voltage with a resonant controller. This controller has to control current and load voltage throughout voltage sag. Generally, resonant controller is made up of a proportional and resonance term, which contains two imaginary poles that aimed to obtain an infinite gain at the resonance frequency. State feedback structure and pole assignment approach are used to tune the proposed control strategy. Comparative results for the application of both resonant and classical PI controller in d-q frame are showed in this paper. The last part deals with the implementation of control strategies on a real time simulation environment. The effectiveness of the proposed controller under a voltage sag operation is shown by experimental results.
Thu, 01 Jan 2009 00:00:00 GMThttp://hdl.handle.net/10985/63142009-01-01T00:00:00ZSALHA, FouadCOLAS, FrédéricGUILLAUD, XavierThe aim of this paper is to propose an over current limitation and voltage control strategy for a grid connected inverter with a LC output filter used in distributed generation and in case of voltage sag. This strategy relies on the control of LC output filter voltage with a resonant controller. This controller has to control current and load voltage throughout voltage sag. Generally, resonant controller is made up of a proportional and resonance term, which contains two imaginary poles that aimed to obtain an infinite gain at the resonance frequency. State feedback structure and pole assignment approach are used to tune the proposed control strategy. Comparative results for the application of both resonant and classical PI controller in d-q frame are showed in this paper. The last part deals with the implementation of control strategies on a real time simulation environment. The effectiveness of the proposed controller under a voltage sag operation is shown by experimental results.Stochastic Optimization of PQ Powers at the Interface between Distribution and Transmission Grids
http://hdl.handle.net/10985/17724
Stochastic Optimization of PQ Powers at the Interface between Distribution and Transmission Grids
BUIRE, Jérôme; COLAS, Frédéric; DIEULOT, Jean-Yves; GUILLAUD, Xavier
This paper addresses the volt-var control of distribution grids embedding many distributed generators (DGs). Specifically, it focuses on the compliance of powers to specified PQ diagrams at the high voltage/medium voltage (HV/MV) interface while the voltages remain well controlled. This is achieved using a two-stage optimization corresponding to two different classes of actuators. The tap position of capacitor banks is selected on a daily basis, given a stochastic model of the input powers prediction, which allows infrequent actuation and increases the device lifespan. In a second stage, a confidence level optimization problem allows to tune on an hourly basis the parameters of the DGs reactive power affine control laws. Results on a real-size grid show that the combined tuning of these actuators allows the ability to comply with European grid codes while the control effort remains reasonable.
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/10985/177242019-01-01T00:00:00ZBUIRE, JérômeCOLAS, FrédéricDIEULOT, Jean-YvesGUILLAUD, XavierThis paper addresses the volt-var control of distribution grids embedding many distributed generators (DGs). Specifically, it focuses on the compliance of powers to specified PQ diagrams at the high voltage/medium voltage (HV/MV) interface while the voltages remain well controlled. This is achieved using a two-stage optimization corresponding to two different classes of actuators. The tap position of capacitor banks is selected on a daily basis, given a stochastic model of the input powers prediction, which allows infrequent actuation and increases the device lifespan. In a second stage, a confidence level optimization problem allows to tune on an hourly basis the parameters of the DGs reactive power affine control laws. Results on a real-size grid show that the combined tuning of these actuators allows the ability to comply with European grid codes while the control effort remains reasonable.Embedding OLTC nonlinearities in predictive Volt Var Control for active distribution networks
http://hdl.handle.net/10985/17730
Embedding OLTC nonlinearities in predictive Volt Var Control for active distribution networks
MORIN, J.; COLAS, Frédéric; DIEULOT, Jean-Yves; GRENARD, S.; GUILLAUD, Xavier
Volatile productions and consumptions generate a stochastic behavior of distribution grids and make its supervision difficult to achieve. Usually, the Distributed Generators reactive powers are adjusted to perform decentralized voltage control. Industrial controllers are generally equipped with a local affine feedback law, which settings are tuned at early stage using local data. A centralized and more efficient tuning method should aim to maximize the probability that all the node voltages of distribution grids remain within prescribed bounds. When the characteristics of the stochastic power forecasts are known, the centralized algorithm allows to update the settings on a regular time basis. However, the method requires to solve stochastic optimization problem. Assuming that stochastic variables have Gaussian distributions, a procedure is given which guarantees the convergence of the stochastic optimization. Convex problems drastically reduce the difficulty and the computational time required to reach the global minimum, compared to nonconvex optimal power flow problems. The linear controllers with optimized parameters are compared to traditional control laws using simulations of a real distribution grid model. The results show that the algorithm is reliable and moreover fast enough. Hence, the proposed method can be used to update periodically the control parameters.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/177302017-01-01T00:00:00ZMORIN, J.COLAS, FrédéricDIEULOT, Jean-YvesGRENARD, S.GUILLAUD, XavierVolatile productions and consumptions generate a stochastic behavior of distribution grids and make its supervision difficult to achieve. Usually, the Distributed Generators reactive powers are adjusted to perform decentralized voltage control. Industrial controllers are generally equipped with a local affine feedback law, which settings are tuned at early stage using local data. A centralized and more efficient tuning method should aim to maximize the probability that all the node voltages of distribution grids remain within prescribed bounds. When the characteristics of the stochastic power forecasts are known, the centralized algorithm allows to update the settings on a regular time basis. However, the method requires to solve stochastic optimization problem. Assuming that stochastic variables have Gaussian distributions, a procedure is given which guarantees the convergence of the stochastic optimization. Convex problems drastically reduce the difficulty and the computational time required to reach the global minimum, compared to nonconvex optimal power flow problems. The linear controllers with optimized parameters are compared to traditional control laws using simulations of a real distribution grid model. The results show that the algorithm is reliable and moreover fast enough. Hence, the proposed method can be used to update periodically the control parameters.Laboratory-based test bed of a three terminals DC networks using power hardware in the loop
http://hdl.handle.net/10985/10300
Laboratory-based test bed of a three terminals DC networks using power hardware in the loop
AMAMRA, Sid-Ali; COLAS, Frédéric; GUILLAUD, Xavier; NGUEFEU, Samuel
In this paper a three stations MTDC grid is presented, providing a specific application of our work. The experimental platform is intended to combine electrical power components and communication/control equipment with real-time simulation tools. In this way the platform can test grid elements and evaluate different operation scenarios under various conditions.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/103002013-01-01T00:00:00ZAMAMRA, Sid-AliCOLAS, FrédéricGUILLAUD, XavierNGUEFEU, SamuelIn this paper a three stations MTDC grid is presented, providing a specific application of our work. The experimental platform is intended to combine electrical power components and communication/control equipment with real-time simulation tools. In this way the platform can test grid elements and evaluate different operation scenarios under various conditions.Impact of Grid-forming Converter on Electromechanical Oscillations
http://hdl.handle.net/10985/24241
Impact of Grid-forming Converter on Electromechanical Oscillations
BOUKHENFOUF, Johan; GUILLAUD, Xavier; BRUYERE, Antoine
As distributed generation increases, it is essential to study its impact on the grid dynamics. This paper focuses on understanding the influence of the emergent technology of Grid-Forming converters on the electromechanical oscillations of the power system. Interactions among synchronous generators and gridforming converters are analyzed thanks to simplified models. These highlight the similarities of both sources, and thus, explain the participation of the converter in the oscillation. They also revealed the differences that justify the damping effect of Grid-Forming converter. This conclusion, obtained with simplified models, is validated with a small-signal stability analysis of a detailed model in the dq0-frame.
Thu, 01 Jun 2023 00:00:00 GMThttp://hdl.handle.net/10985/242412023-06-01T00:00:00ZBOUKHENFOUF, JohanGUILLAUD, XavierBRUYERE, AntoineAs distributed generation increases, it is essential to study its impact on the grid dynamics. This paper focuses on understanding the influence of the emergent technology of Grid-Forming converters on the electromechanical oscillations of the power system. Interactions among synchronous generators and gridforming converters are analyzed thanks to simplified models. These highlight the similarities of both sources, and thus, explain the participation of the converter in the oscillation. They also revealed the differences that justify the damping effect of Grid-Forming converter. This conclusion, obtained with simplified models, is validated with a small-signal stability analysis of a detailed model in the dq0-frame.Distributed Economic Dispatch of Embedded Generation in Smart Grids
http://hdl.handle.net/10985/11353
Distributed Economic Dispatch of Embedded Generation in Smart Grids
DIBANGOYE, Jille; GUILLAUD, Xavier; COLAS, Frédéric; FAKHAM, Hicham; DONIEC, Arnaud
In a Smart Grid context, the increasing penetration of embedded generation units leads to a greater complexity in the management of production units. In this arti- cle, we focus on the impact of the introduction of decentralized generation for the unit commitment problem (UC). Unit Commitment Problems consist in finding the optimal schedules and amounts of power to be generated by a set of gen- erating units in response to an electricity demand forecast. While this problem have received a significant amount of attention, classical approaches assume these problems are centralized and deterministic. However, these two assumptions are not realistic in a smart grid context. Indeed, finding the optimal schedules and amounts of power to be generated by multiple distributed generator units is not trivial since it requires to deal with distributed computation, privacy, stochastic planning, ... In this paper, we focus on smart grid scenarios where the main source of complexity comes from the proliferation of distributed generating units. In solving this issue, we consider distributed stochastic unit commitment prob- lems. We introduce a novel distributed gradient descent algorithm which allow us to circumvent classical assumptions. This algorithm is evaluated through a set of experiments on real-time power grid simulator.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/113532015-01-01T00:00:00ZDIBANGOYE, JilleGUILLAUD, XavierCOLAS, FrédéricFAKHAM, HichamDONIEC, ArnaudIn a Smart Grid context, the increasing penetration of embedded generation units leads to a greater complexity in the management of production units. In this arti- cle, we focus on the impact of the introduction of decentralized generation for the unit commitment problem (UC). Unit Commitment Problems consist in finding the optimal schedules and amounts of power to be generated by a set of gen- erating units in response to an electricity demand forecast. While this problem have received a significant amount of attention, classical approaches assume these problems are centralized and deterministic. However, these two assumptions are not realistic in a smart grid context. Indeed, finding the optimal schedules and amounts of power to be generated by multiple distributed generator units is not trivial since it requires to deal with distributed computation, privacy, stochastic planning, ... In this paper, we focus on smart grid scenarios where the main source of complexity comes from the proliferation of distributed generating units. In solving this issue, we consider distributed stochastic unit commitment prob- lems. We introduce a novel distributed gradient descent algorithm which allow us to circumvent classical assumptions. This algorithm is evaluated through a set of experiments on real-time power grid simulator.