The building sector is undergoing a deep transformation to contribute to meeting the climate neut... more The building sector is undergoing a deep transformation to contribute to meeting the climate neutrality goals set by policymakers worldwide. This process entails the transition towards smart energy-aware buildings that have lower consumptions and better efficiency performance. Digitalization is a key part of this process. A huge amount of data is currently generated by sensors, smart meters and a multitude of other devices and data sources, and this trend is expected to exponentially increase in the near future. Exploiting these data for different use cases spanning multiple application scenarios is of utmost importance to capture their full value and build smart and innovative building services. In this context, this paper presents a high-level architecture for big data management in the building domain which aims to foster data sharing, interoperability and the seamless integration of advanced services based on data-driven techniques. This work focuses on the functional descriptio...
IEEE Open Journal of Instrumentation and Measurement
The real-time monitoring of electric distribution grids via state estimation is a fundamental req... more The real-time monitoring of electric distribution grids via state estimation is a fundamental requirement to deploy smart automation and control in the distribution system. Due to the large size of distribution networks and the poor coverage of measurement instrumentation on the field, designing fast state estimation algorithms and achieving accurate results are two major challenges associated to distribution system state estimation. In this paper, an efficient and accurate solution for performing state estimation in multi-feeder radial distribution grids is presented. The proposed algorithm is based on a two-step approach. In the first step, state estimation is performed in parallel on the different feeders suitably processing the available measurements and pseudo-measurements and taking into account their uncertainty characteristics. In the second step, the results on each feeder are post-processed to refine the estimations and to improve the accuracy performance. To this purpose, the second step considers how measurement uncertainties propagate towards the final estimates and how measurements shared among the feeders could adversely affect the final estimation. Performed tests show that the conceived design leads to accuracy performance very close to those achievable by running state estimation on the full grid. At the same time, the parallelization of the estimation process on the different feeders allows decentralizing the state estimation problem, with the associated benefits in terms of computation time and distribution of the communication and storage requirements.
The ramping trend of cheap and performant single board computers (SBC) is growingly offering unpr... more The ramping trend of cheap and performant single board computers (SBC) is growingly offering unprecedented opportunities in various domains, taking advantage of the widespread support and flexibility offered by an operating system (OS) environment. Unfortunately, data acquisition systems implemented in an OS environment are traditionally considered not to be suitable for reliable industrial applications. Such a position is supported by the lack of hardware interrupt handling and deterministic control of timed operations. In this study, the authors fill this gap by proposing an innovative and versatile SBC-based open-source platform for CPU-independent data acquisition. The synchronized measurement unit (SMU) is a high-accuracy device able to perform multichannel simultaneous sampling up to 200 kS/s with sub-microsecond synchronization precision to a GPS time reference. It exhibits very low offset and gain errors, with a minimum bandwidth beyond 20 kHz, SNR levels above 90 dB and THD...
Advanced control techniques for modern distribution grids are becoming fundamental for the reduct... more Advanced control techniques for modern distribution grids are becoming fundamental for the reduction of grid reinforcements while maintaining network performances. In particular, as shown in literature, distributed algorithms for voltage control have gained much interests in comparison with the typical centralized formulation for its feasibility. Distributed model predictive control (MPC) is shown to optimally manage the Distributed Generators (DGs) over time and it can be implemented locally at the controllable sources. For this purpose, this paper adopts a distributed algorithm recently presented in the literature for solving a constraint-coupled optimization problem for model predictive voltage control. A detailed reformulation of the original MPC problem for the specific application is presented. Besides, this paper provides a calculation of the convergence limit for the value of the iteration step size of the algorithm, supported by numerical results. The proposed distributed solution of model predictive voltage control is compared with a centralized formulation via numerical simulation in terms of the percentage of error with the centralized solution and number of iteration for the convergence.
Advanced control techniques for modern distribution grids are becoming fundamental for the reduct... more Advanced control techniques for modern distribution grids are becoming fundamental for the reduction of grid reinforcements while maintaining network performances. In particular, as shown in literature, distributed algorithms for voltage control have gained much interests in comparison with the typical centralized formulation for its feasibility. Distributed model predictive control (MPC) is shown to optimally manage the Distributed Generators (DGs) over time and it can be implemented locally at the controllable sources. For this purpose, this paper adopts a distributed algorithm recently presented in the literature for solving a constraint-coupled optimization problem for model predictive voltage control. A detailed reformulation of the original MPC problem for the specific application is presented. Besides, this paper provides a calculation of the convergence limit for the value of the iteration step size of the algorithm, supported by numerical results. The proposed distributed solution of model predictive voltage control is compared with a centralized formulation via numerical simulation in terms of the percentage of error with the centralized solution and number of iteration for the convergence.
Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, 2017
Final customers are expected to play an active role in the Smart Grid scenario by offering their ... more Final customers are expected to play an active role in the Smart Grid scenario by offering their flexibility to allow a more efficient and reliable operation of the electric grid. Among the household appliances, heat pumps used for space heating are commonly recognized as flexible loads that can be suitably handled to gain benefit in the Smart Grid context. This paper proposes an optimization algorithm, based on a Mixed-Integer Linear Programming approach, designed to achieve power peak shaving in the distribution grid while providing at the same time the required thermal comfort to the end-users. The developed model allows considering a continuous operation mode of the heat pumps and different comfort requirements defined by the users over the day. Performed simulations prove the proper operation of the proposed algorithm and the technical benefits potentially achievable through the devised management of the heating devices.
This Special Issue aims at collecting new research contributions and perspectives on the topic of... more This Special Issue aims at collecting new research contributions and perspectives on the topic of the monitoring and automation of modern power systems [...]
2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016
This paper presents the application of a fast twostep multi-area approach for state estimation in... more This paper presents the application of a fast twostep multi-area approach for state estimation in wide-area distribution systems. In a previous paper [10], the authors have assessed the possibility to perform Distribution System State Estimation (DSSE) in a multi-area framework, designing the methodology according to the configuration of the measurement infrastructure. In this paper, constraints associated to the measurement placement are removed and the methodology proposed in [10] has been generalized to deal with every possible measurement system. A new second step procedure has been also designed to obtain a more computationally efficient refinement of the voltage profile. The proposed multi-area method can be performed in a decentralized way and with parallel processing, relying on limited data communication. Test results, obtained on the 123-bus IEEE test network, are presented and discussed.
Hybrid AC/DC distribution systems are becoming a popular means to accommodate the increasing pene... more Hybrid AC/DC distribution systems are becoming a popular means to accommodate the increasing penetration of distributed energy resources and flexible loads. This paper proposes a distributed and robust state estimation (DRSE) method for hybrid AC/DC distribution systems using multiple sources of data. In the proposed distributed implementation framework, a unified robust linear state estimation model is derived for each AC and DC regions, where the regions are connected via AC/DC converters and only limited information exchange is needed. To enhance the estimation accuracy of the areas with low measurement coverage, a deep neural network (DNN) is used to extract hidden system statistical information and allow deriving nodal power injections that keep up with the real-time measurement update rate. This provides the way of integrating smart meter data, SCADA measurements and zero injections together for state estimation. Simulations on two hybrid AC/DC distribution systems show that t...
2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2017
In the smart grid scenario, Demand Response (DR) and Demand Side Management (DSM) programs are co... more In the smart grid scenario, Demand Response (DR) and Demand Side Management (DSM) programs are considered as strategic to obtain a more efficient operation of the grid. The flexibility given by the final customers plays a key role to unlock the potential benefits offered by the application of these schemes. A classical example of flexible load that can be exploited for DR and DSM purposes is the electric heat pump. This paper aims at evaluating the main factors affecting the flexibility available in the management of electric heat pumps for space heating. The performed analysis allows identifying some indexes to quantify the available flexibility and highlights how the thermal comfort requirements of the customers affect the provided level of flexibility. Sample simulations show the impact of these flexibility terms on the results of a DSM program designed for power peak shaving at grid level. The possible use of the defined indexes for sorting the customers flexibility and for estimating the potential benefits offered by the adopted DSM scheme is also investigated and discussed.
Hybrid ac-dc grids are one of the possible solutions to support the integration of the increasing... more Hybrid ac-dc grids are one of the possible solutions to support the integration of the increasing renewable capacity into the ac grid thanks to the flexibility of voltage and power flow control that converters at the boundary buses offer. However, this requires coordinated control and accurate monitoring of the converter and the hybrid ac-dc network. State estimation is one of the traditional approaches in power systems to monitor the conditions of the grid. This paper proposes a method to include the built-in measurements of the converter controller into the state estimation of the hybrid ac-dc grid. To this purpose, the sources of measurement uncertainty in the converter controller are analyzed, and the uncertainty budget is evaluated for each of them. From this, the resulting uncertainty of the converter measurements to be considered in the state estimation model is derived. Test results on a sample hybrid ac-dc grid show the potential benefits achievable through the proposed integration of the converter measurements into state estimation-based monitoring tools.
2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2018
With the transition towards the smart grid paradigm, end-users are expected to play a more and mo... more With the transition towards the smart grid paradigm, end-users are expected to play a more and more active role by offering their flexibility to support the efficient operation of electric networks. This paper investigates the potential given by a Demand Side Management program for the control of electric heat pumps combined with thermal storage aimed at reducing the power peaks in the grid. To this purpose, the assessment of the building thermal loads is performed according to the standard ISO 13790 and a mixed integer linear programming optimization is applied to schedule the operation of the electric heat pumps. Preliminary results show that decoupling thermal load and electricity consumption by using the thermal storage guarantees a large flexibility, which can be exploited to achieve important benefits at grid level without affecting the thermal comfort of final customers.
2017 IEEE International Workshop on Applied Measurements for Power Systems (AMPS), 2017
Phasor Measurement Units have become more and more interesting for monitoring applications in dis... more Phasor Measurement Units have become more and more interesting for monitoring applications in distribution grids. For a large exploitation in medium and low voltage networks, however, a limited cost is required. Such specification, however, should not impact excessively the accuracy requirements, as it is expected that automatic control functionalities will run based on state estimation algorithms, which can be fed by PMU information. In this paper the design of a low cost PMU for distribution grids is proposed, and tested versus the IEEE c37.118.1-2011 standard for accuracy. The development of the low cost PMU is part of the Modular Intelligent Node (MIND) project, where distribution grid components and functionalities are implemented as modular interconnected nodes that run on general purpose hardware.
2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2017
In electrical distribution networks many automation applications, such as voltage and power contr... more In electrical distribution networks many automation applications, such as voltage and power control, require to access the status of the system. Such information can be obtained by aggregating the heterogeneous measurements available in the grid and then applying state estimation algorithms. Different factors may have an impact on the estimation errors when the grid status evolves dynamically. The scope of this paper is to point out the different contributions affecting the global uncertainty of state estimation results when fast dynamics are present in the grid, for example due to fast variations of renewable energy sources generation or customers power consumption. The so-called "4 quadrants' method" is proposed to quantify and decompose such uncertainty components. The results of the 4 quadrants method may be useful in the process of design of the monitoring infrastructure.
Distribution grids are becoming active and highly complex systems. In this scenario, monitoring o... more Distribution grids are becoming active and highly complex systems. In this scenario, monitoring of the distribution network is key to ensure its efficient and reliable operation. While distribution state estimation techniques have been proposed to this purpose, their practical use in the field is challenging, mainly due to the lack of a redundant measurement infrastructure. This issue often prevents the operation of bad data detection and identification functions, which are essential to filter out possible bad measurements that would lead to misleading estimation results. This paper aims at investigating the bad data detection and identification capabilities of distribution system state estimation algorithms when a measurement infrastructure composed of end-user smart meters is used. A mathematical analysis is performed to understand the achievable results depending on number and accuracy of the smart meter devices. Analytical findings are then validated by means of ad hoc simulations.
2019 IEEE 10th International Workshop on Applied Measurements for Power Systems (AMPS), 2019
State Estimation is a key function for the control and secure operation of automated systems. Dis... more State Estimation is a key function for the control and secure operation of automated systems. Distribution system operators exploit the state estimation algorithms to merge the available measurements and to obtain the most likely state of the system. The knowledge of the expected uncertainty of the state estimator is critical to fine-tune the applications based on state estimation results or to determine type and placement of instruments. This paper extends the existing methodologies to derive the state estimation uncertainty by considering the case of non-ideal measurement reporting due to possible delays and/or asynchronous measurements. The developed uncertainty propagation models are validated via Monte Carlo analysis using a sample distribution network as test system.
2019 International Conference on Smart Energy Systems and Technologies (SEST), 2019
Many distribution grid management functions rely upon power flow algorithms to analyse the behavi... more Many distribution grid management functions rely upon power flow algorithms to analyse the behaviour of the grid under specific conditions. The knowledge of the grid parameters is usually the starting point for the definition of the models behind power flow algorithms. However, in the distribution system scenario, several factors can affect the level of confidence with which these parameters are known. This paper aims at investigating the main sources of uncertainty in the modelling of distribution lines, taking into account the specific characteristics of the distribution system, and it studies the impact of those uncertainties on the power flow results. The goal is to identify which factors can potentially bring severe degradations of the power flow results, so that the distribution grid model can be improved accordingly or their impact can be duly considered when evaluating the results.
The building sector is undergoing a deep transformation to contribute to meeting the climate neut... more The building sector is undergoing a deep transformation to contribute to meeting the climate neutrality goals set by policymakers worldwide. This process entails the transition towards smart energy-aware buildings that have lower consumptions and better efficiency performance. Digitalization is a key part of this process. A huge amount of data is currently generated by sensors, smart meters and a multitude of other devices and data sources, and this trend is expected to exponentially increase in the near future. Exploiting these data for different use cases spanning multiple application scenarios is of utmost importance to capture their full value and build smart and innovative building services. In this context, this paper presents a high-level architecture for big data management in the building domain which aims to foster data sharing, interoperability and the seamless integration of advanced services based on data-driven techniques. This work focuses on the functional descriptio...
IEEE Open Journal of Instrumentation and Measurement
The real-time monitoring of electric distribution grids via state estimation is a fundamental req... more The real-time monitoring of electric distribution grids via state estimation is a fundamental requirement to deploy smart automation and control in the distribution system. Due to the large size of distribution networks and the poor coverage of measurement instrumentation on the field, designing fast state estimation algorithms and achieving accurate results are two major challenges associated to distribution system state estimation. In this paper, an efficient and accurate solution for performing state estimation in multi-feeder radial distribution grids is presented. The proposed algorithm is based on a two-step approach. In the first step, state estimation is performed in parallel on the different feeders suitably processing the available measurements and pseudo-measurements and taking into account their uncertainty characteristics. In the second step, the results on each feeder are post-processed to refine the estimations and to improve the accuracy performance. To this purpose, the second step considers how measurement uncertainties propagate towards the final estimates and how measurements shared among the feeders could adversely affect the final estimation. Performed tests show that the conceived design leads to accuracy performance very close to those achievable by running state estimation on the full grid. At the same time, the parallelization of the estimation process on the different feeders allows decentralizing the state estimation problem, with the associated benefits in terms of computation time and distribution of the communication and storage requirements.
The ramping trend of cheap and performant single board computers (SBC) is growingly offering unpr... more The ramping trend of cheap and performant single board computers (SBC) is growingly offering unprecedented opportunities in various domains, taking advantage of the widespread support and flexibility offered by an operating system (OS) environment. Unfortunately, data acquisition systems implemented in an OS environment are traditionally considered not to be suitable for reliable industrial applications. Such a position is supported by the lack of hardware interrupt handling and deterministic control of timed operations. In this study, the authors fill this gap by proposing an innovative and versatile SBC-based open-source platform for CPU-independent data acquisition. The synchronized measurement unit (SMU) is a high-accuracy device able to perform multichannel simultaneous sampling up to 200 kS/s with sub-microsecond synchronization precision to a GPS time reference. It exhibits very low offset and gain errors, with a minimum bandwidth beyond 20 kHz, SNR levels above 90 dB and THD...
Advanced control techniques for modern distribution grids are becoming fundamental for the reduct... more Advanced control techniques for modern distribution grids are becoming fundamental for the reduction of grid reinforcements while maintaining network performances. In particular, as shown in literature, distributed algorithms for voltage control have gained much interests in comparison with the typical centralized formulation for its feasibility. Distributed model predictive control (MPC) is shown to optimally manage the Distributed Generators (DGs) over time and it can be implemented locally at the controllable sources. For this purpose, this paper adopts a distributed algorithm recently presented in the literature for solving a constraint-coupled optimization problem for model predictive voltage control. A detailed reformulation of the original MPC problem for the specific application is presented. Besides, this paper provides a calculation of the convergence limit for the value of the iteration step size of the algorithm, supported by numerical results. The proposed distributed solution of model predictive voltage control is compared with a centralized formulation via numerical simulation in terms of the percentage of error with the centralized solution and number of iteration for the convergence.
Advanced control techniques for modern distribution grids are becoming fundamental for the reduct... more Advanced control techniques for modern distribution grids are becoming fundamental for the reduction of grid reinforcements while maintaining network performances. In particular, as shown in literature, distributed algorithms for voltage control have gained much interests in comparison with the typical centralized formulation for its feasibility. Distributed model predictive control (MPC) is shown to optimally manage the Distributed Generators (DGs) over time and it can be implemented locally at the controllable sources. For this purpose, this paper adopts a distributed algorithm recently presented in the literature for solving a constraint-coupled optimization problem for model predictive voltage control. A detailed reformulation of the original MPC problem for the specific application is presented. Besides, this paper provides a calculation of the convergence limit for the value of the iteration step size of the algorithm, supported by numerical results. The proposed distributed solution of model predictive voltage control is compared with a centralized formulation via numerical simulation in terms of the percentage of error with the centralized solution and number of iteration for the convergence.
Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, 2017
Final customers are expected to play an active role in the Smart Grid scenario by offering their ... more Final customers are expected to play an active role in the Smart Grid scenario by offering their flexibility to allow a more efficient and reliable operation of the electric grid. Among the household appliances, heat pumps used for space heating are commonly recognized as flexible loads that can be suitably handled to gain benefit in the Smart Grid context. This paper proposes an optimization algorithm, based on a Mixed-Integer Linear Programming approach, designed to achieve power peak shaving in the distribution grid while providing at the same time the required thermal comfort to the end-users. The developed model allows considering a continuous operation mode of the heat pumps and different comfort requirements defined by the users over the day. Performed simulations prove the proper operation of the proposed algorithm and the technical benefits potentially achievable through the devised management of the heating devices.
This Special Issue aims at collecting new research contributions and perspectives on the topic of... more This Special Issue aims at collecting new research contributions and perspectives on the topic of the monitoring and automation of modern power systems [...]
2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016
This paper presents the application of a fast twostep multi-area approach for state estimation in... more This paper presents the application of a fast twostep multi-area approach for state estimation in wide-area distribution systems. In a previous paper [10], the authors have assessed the possibility to perform Distribution System State Estimation (DSSE) in a multi-area framework, designing the methodology according to the configuration of the measurement infrastructure. In this paper, constraints associated to the measurement placement are removed and the methodology proposed in [10] has been generalized to deal with every possible measurement system. A new second step procedure has been also designed to obtain a more computationally efficient refinement of the voltage profile. The proposed multi-area method can be performed in a decentralized way and with parallel processing, relying on limited data communication. Test results, obtained on the 123-bus IEEE test network, are presented and discussed.
Hybrid AC/DC distribution systems are becoming a popular means to accommodate the increasing pene... more Hybrid AC/DC distribution systems are becoming a popular means to accommodate the increasing penetration of distributed energy resources and flexible loads. This paper proposes a distributed and robust state estimation (DRSE) method for hybrid AC/DC distribution systems using multiple sources of data. In the proposed distributed implementation framework, a unified robust linear state estimation model is derived for each AC and DC regions, where the regions are connected via AC/DC converters and only limited information exchange is needed. To enhance the estimation accuracy of the areas with low measurement coverage, a deep neural network (DNN) is used to extract hidden system statistical information and allow deriving nodal power injections that keep up with the real-time measurement update rate. This provides the way of integrating smart meter data, SCADA measurements and zero injections together for state estimation. Simulations on two hybrid AC/DC distribution systems show that t...
2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2017
In the smart grid scenario, Demand Response (DR) and Demand Side Management (DSM) programs are co... more In the smart grid scenario, Demand Response (DR) and Demand Side Management (DSM) programs are considered as strategic to obtain a more efficient operation of the grid. The flexibility given by the final customers plays a key role to unlock the potential benefits offered by the application of these schemes. A classical example of flexible load that can be exploited for DR and DSM purposes is the electric heat pump. This paper aims at evaluating the main factors affecting the flexibility available in the management of electric heat pumps for space heating. The performed analysis allows identifying some indexes to quantify the available flexibility and highlights how the thermal comfort requirements of the customers affect the provided level of flexibility. Sample simulations show the impact of these flexibility terms on the results of a DSM program designed for power peak shaving at grid level. The possible use of the defined indexes for sorting the customers flexibility and for estimating the potential benefits offered by the adopted DSM scheme is also investigated and discussed.
Hybrid ac-dc grids are one of the possible solutions to support the integration of the increasing... more Hybrid ac-dc grids are one of the possible solutions to support the integration of the increasing renewable capacity into the ac grid thanks to the flexibility of voltage and power flow control that converters at the boundary buses offer. However, this requires coordinated control and accurate monitoring of the converter and the hybrid ac-dc network. State estimation is one of the traditional approaches in power systems to monitor the conditions of the grid. This paper proposes a method to include the built-in measurements of the converter controller into the state estimation of the hybrid ac-dc grid. To this purpose, the sources of measurement uncertainty in the converter controller are analyzed, and the uncertainty budget is evaluated for each of them. From this, the resulting uncertainty of the converter measurements to be considered in the state estimation model is derived. Test results on a sample hybrid ac-dc grid show the potential benefits achievable through the proposed integration of the converter measurements into state estimation-based monitoring tools.
2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2018
With the transition towards the smart grid paradigm, end-users are expected to play a more and mo... more With the transition towards the smart grid paradigm, end-users are expected to play a more and more active role by offering their flexibility to support the efficient operation of electric networks. This paper investigates the potential given by a Demand Side Management program for the control of electric heat pumps combined with thermal storage aimed at reducing the power peaks in the grid. To this purpose, the assessment of the building thermal loads is performed according to the standard ISO 13790 and a mixed integer linear programming optimization is applied to schedule the operation of the electric heat pumps. Preliminary results show that decoupling thermal load and electricity consumption by using the thermal storage guarantees a large flexibility, which can be exploited to achieve important benefits at grid level without affecting the thermal comfort of final customers.
2017 IEEE International Workshop on Applied Measurements for Power Systems (AMPS), 2017
Phasor Measurement Units have become more and more interesting for monitoring applications in dis... more Phasor Measurement Units have become more and more interesting for monitoring applications in distribution grids. For a large exploitation in medium and low voltage networks, however, a limited cost is required. Such specification, however, should not impact excessively the accuracy requirements, as it is expected that automatic control functionalities will run based on state estimation algorithms, which can be fed by PMU information. In this paper the design of a low cost PMU for distribution grids is proposed, and tested versus the IEEE c37.118.1-2011 standard for accuracy. The development of the low cost PMU is part of the Modular Intelligent Node (MIND) project, where distribution grid components and functionalities are implemented as modular interconnected nodes that run on general purpose hardware.
2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2017
In electrical distribution networks many automation applications, such as voltage and power contr... more In electrical distribution networks many automation applications, such as voltage and power control, require to access the status of the system. Such information can be obtained by aggregating the heterogeneous measurements available in the grid and then applying state estimation algorithms. Different factors may have an impact on the estimation errors when the grid status evolves dynamically. The scope of this paper is to point out the different contributions affecting the global uncertainty of state estimation results when fast dynamics are present in the grid, for example due to fast variations of renewable energy sources generation or customers power consumption. The so-called "4 quadrants' method" is proposed to quantify and decompose such uncertainty components. The results of the 4 quadrants method may be useful in the process of design of the monitoring infrastructure.
Distribution grids are becoming active and highly complex systems. In this scenario, monitoring o... more Distribution grids are becoming active and highly complex systems. In this scenario, monitoring of the distribution network is key to ensure its efficient and reliable operation. While distribution state estimation techniques have been proposed to this purpose, their practical use in the field is challenging, mainly due to the lack of a redundant measurement infrastructure. This issue often prevents the operation of bad data detection and identification functions, which are essential to filter out possible bad measurements that would lead to misleading estimation results. This paper aims at investigating the bad data detection and identification capabilities of distribution system state estimation algorithms when a measurement infrastructure composed of end-user smart meters is used. A mathematical analysis is performed to understand the achievable results depending on number and accuracy of the smart meter devices. Analytical findings are then validated by means of ad hoc simulations.
2019 IEEE 10th International Workshop on Applied Measurements for Power Systems (AMPS), 2019
State Estimation is a key function for the control and secure operation of automated systems. Dis... more State Estimation is a key function for the control and secure operation of automated systems. Distribution system operators exploit the state estimation algorithms to merge the available measurements and to obtain the most likely state of the system. The knowledge of the expected uncertainty of the state estimator is critical to fine-tune the applications based on state estimation results or to determine type and placement of instruments. This paper extends the existing methodologies to derive the state estimation uncertainty by considering the case of non-ideal measurement reporting due to possible delays and/or asynchronous measurements. The developed uncertainty propagation models are validated via Monte Carlo analysis using a sample distribution network as test system.
2019 International Conference on Smart Energy Systems and Technologies (SEST), 2019
Many distribution grid management functions rely upon power flow algorithms to analyse the behavi... more Many distribution grid management functions rely upon power flow algorithms to analyse the behaviour of the grid under specific conditions. The knowledge of the grid parameters is usually the starting point for the definition of the models behind power flow algorithms. However, in the distribution system scenario, several factors can affect the level of confidence with which these parameters are known. This paper aims at investigating the main sources of uncertainty in the modelling of distribution lines, taking into account the specific characteristics of the distribution system, and it studies the impact of those uncertainties on the power flow results. The goal is to identify which factors can potentially bring severe degradations of the power flow results, so that the distribution grid model can be improved accordingly or their impact can be duly considered when evaluating the results.
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Papers by Marco Pau