Rapid algorithm prototyping and implementation for power quality measurement

Kołek, Krzysztof; Piątek, Krzysztof

doi:10.1186/s13634-015-0192-3

Cited by 8 publications

(7 citation statements)

References 20 publications

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“…The model duplicates the functional blocks described in the standard and operates in the same way as the standardised instrument to ensure complete consistency of results. Some implementation issues and flicker calculation algorithms are presented in [17][18][19][20][21][22][23][24][25]. Various hardware platforms have been applied for implementing and testing the flickermeter: LabView [5], low-cost embedded systems [26] and digital signal processors [27].…”

Section: Algorithm Of Flickermeter and Implementation Issuesmentioning

confidence: 99%

Analysis of the Practical Implementation of Flicker Measurement Coprocessor for AMI Meters

et al. 2021

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Monitoring power quality (PQ) indicators is an important part of modern power grids’ maintenance. Among different PQ indicators, flicker severity coefficients Pst and Plt are measures of voltage fluctuations. In state-of-the-art PQ measuring devices, the flicker measurement channel is usually implemented as a dedicated processor subsystem. Implementation of the IEC 61000-4-15 compliant flicker measurement algorithm requires a significant amount of computational power. In typical PQ analysers, the flicker measurement is usually implemented as a part of the meter’s algorithm performed by the main processor. This paper considers the implementation of the flicker measurement as an FPGA module to offload the processor subsystem or operate as an IP core in FPGA-based system-on-chip units. The measurement algorithm is developed and validated as a Simulink diagram, which is then converted to a fixed-point representation. Parts of the diagram are applied for automatic VHDL code generation, and the classifier block is implemented as a local soft-processor system. A simple eight-bit processor operates within the flicker measurement coprocessor and performs statistical operations. Finally, an IP module is created that can be considered as a flicker coprocessor module. When using the coprocessor, the main processor’s only role is to trigger the coprocessor and read the results, while the coprocessor independently calculates the flicker coefficients.

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Section: Algorithm Of Flickermeter and Implementation Issuesmentioning

confidence: 99%

Analysis of the Practical Implementation of Flicker Measurement Coprocessor for AMI Meters

et al. 2021

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“…In particular, the problem of new hardware with adequate computational capability and time intensive, cost-ineffective manual implementations in advanced power quality metering algorithms is studied in [6]. In fact, a model-based design approach to rapidly implement power quality metering algorithms is proposed that is able to focus on the design, validation, and testing stages while skipping over implementation issues.…”

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confidence: 99%

“…In [5], a data processing network for an in-house low-voltage smart grid is considered. The aim of the paper is the proposal of a high-rate measurement architecture for data processing, monitoring, and management in a smart grid characterized by real-time measurements and sophisticated control integrating fluctuating renewable power sources and/or prosumers (such as electrical vehicles and storage systems).Papers [6][7][8] are focused on different aspects of power quality in smart grids. In particular, the problem of new hardware with adequate computational capability and time intensive, cost-ineffective manual implementations in advanced power quality metering algorithms is studied in [6].…”

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Guest editorial introduction to the special issue on “advanced signal processing techniques and telecommunications network infrastructures for smart grid analysis, monitoring, and management”

Bracale

Barros

Cacciapuoti

et al. 2015

EURASIP J. Adv. Signal Process.

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Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users and vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems. This evolution of power distribution networks involves also an increasingly complex and performing Information and Communication Technology (ICT) infrastructure. An increasing and continuous flow of information will be exchanged among the various levels of such systems in order to ensure an optimized operation of the network and an efficient management of distributed resources. Then, SGs operate with two-way flows of both electricity and information. The necessary communication resources heavily depend on the choices related to the required signal processing for analysis, monitoring, and management of the network.Many research contributions have been published recently in the relevant literature, covering the innovative topics associated with this new concept of functional power systems. However, few papers have addressed the problems inherent to the study of the advanced signal processing techniques and telecommunications network infrastructures which are needed for the modern SGs. This is the reason for this special issue.There are many aspects where signal processing plays a crucial role for planning and operation of SGs. This special issue focuses on some of them, addressing in particular the development of new, advanced, signal processing methods for studying the characteristics of highly non-stationary waveforms involved in the analysis, monitoring and management of the electrical quantities at nodes/branches of the smart grids.Our call for papers attracted numerous submissions worldwide. In response to the call for papers for this special issue, after the review process, 12 were accepted for publication, with co-authors from Asia, Europe, South America, and the USA These papers are briefly described in the following.In [1], the authors use higher-order statistics-based feature extraction and regression algorithms implemented in artificial neural networks (ANNs) to classify power quality disturbances. The novel aspect of the method proposed is the use of a feature vector based on the combination of time and frequency d...

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“…The implementation of the S-APF controller was made according to the Model-Based Design (MBD) principle. The MBD focuses on the modelling and validation of a model by simulation while the implementation details are hidden and performed automatically [27][28][29]. The design and simulation stages are conducted in Simulink and after the validation of the model, the C-code of the real-time controller, which is functionally equivalent to the model, is automatically generated.…”

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A New Optimal Current Controller for a Three-Phase Shunt Active Power Filter Based on Karush–Kuhn–Tucker Conditions

Kołek

Firlit

2021

Energies

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This paper presents an algorithm for finding the optimal control for a current controller that operates as a part of a control system of a shunt active power filter. The algorithm is based upon the Karush–Kuhn–Tucker conditions for finding an optimal value where control signal is limited and constraints create a cube. The explicit solution of the Karush–Kuhn–Tucker problem is presented and simplified calculations are given to lower calculation complexity. The presented Karush–Kuhn–Tucker algorithm is compared with a classical PI controller. It is given the algorithm for finding the optimal parameters of the PI controller and the behavior of the PI controller is compared with the presented algorithm. Attention has been paid to the saturation of controllers in commutation states of load currents, which has a negative impact on the final performance of the controllers and the controlled shunt active power filter. The paper also presents the software and hardware platforms applied to run the presented algorithms in real-time. For both controllers, the shunt active power filter response is shown using real experimental results. The results of the experiments prove better behavior regarding the presented algorithm, especially in the case of commutative load currents, where the output signals from other regulators become saturated.

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Rapid algorithm prototyping and implementation for power quality measurement

Cited by 8 publications

References 20 publications

Analysis of the Practical Implementation of Flicker Measurement Coprocessor for AMI Meters

Analysis of the Practical Implementation of Flicker Measurement Coprocessor for AMI Meters

Guest editorial introduction to the special issue on “advanced signal processing techniques and telecommunications network infrastructures for smart grid analysis, monitoring, and management”

A New Optimal Current Controller for a Three-Phase Shunt Active Power Filter Based on Karush–Kuhn–Tucker Conditions

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