DSO Strategies Proposal for the LV Grid of the Future

Mroczek, Bartłomiej; Pijarski, Paweł

doi:10.3390/en14196327

Cited by 4 publications

(2 citation statements)

References 47 publications

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“…To maintain correct network operation with the required quality of supply, DSOs are motivated to look for solutions that enable energy management in the network. Commonly applied voltage regulation methods are based on the change of active and reactive power flow in the network [5], e.g., by a change in the power generation of PV inverters.…”

Section: Introductionmentioning

confidence: 99%

Hardware-in-the-Loop Validation of an Energy Management System for LV Distribution Networks with Renewable Energy Sources

et al. 2022

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This paper presents the use of real-time digital simulator (RTDS) and hardware-in-the-loop (HIL) methods for the validation of an energy management system designed for real low-voltage (LV) distribution networks with a high penetration of renewable energy sources. The system is used to address voltage violations and current overloading issues and allows the network operator to maintain safe and controllable network operations. The applied control strategy and the system software were verified by means of simulations. In this paper, the next stage of system validation using the HIL method is presented. A testbed was designed and developed to test the operation of prototype controllers of the system in flexible and reproducible conditions before installing them in the network. The presented testing platform not only includes the LV network simulator with the power amplifiers needed for closed-loop setup but also additional elements of a real network to which the system is dedicated, i.e., the advanced metering infrastructure, photovoltaic source, and energy storage inverters and load devices. Furthermore, the real cellular network of the distribution network operator is used in the communication between the controllers. In addition, the article contains discussions on communication issues, including limitations related to selected protocols. Finally, examples of the experimental validation of the controller prototypes are presented.

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Section: Introductionmentioning

confidence: 99%

Hardware-in-the-Loop Validation of an Energy Management System for LV Distribution Networks with Renewable Energy Sources

et al. 2022

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“…Based on their research, they concluded that the linear and conic methods are optimal for small and medium-sized systems. In [252], the authors used nonlinear optimisation to propose an optimal strategy for the distribution system operator (DSO) to provide flexibility services in areas with a large amount of distributed renewable sources. The authors of [253] used a single-step method for tracing power flows, which combines the accuracy of linear optimisation and the speed of heuristic methods for removing current overloads in power lines.…”

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confidence: 99%

Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue

Pijarski,

Belowski

2024

Energies

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The challenges currently faced by network operators are difficult and complex. Presently, various types of energy sources with random generation, energy storage units operating in charging or discharging mode and consumers with different operating characteristics are connected to the power grid. The network is being expanded and modernised. This contributes to the occurrence of various types of network operating states in practice. The appearance of a significant number of objects with random generation in the power system complicates the process of planning and controlling the operation of the power system. It is therefore necessary to constantly search for new methods and algorithms that allow operators to adapt to the changing operating conditions of the power grid. There are many different types of method in the literature, with varying effectiveness, that have been or are used in practice. So far, however, no one ideal, universal method or methodology has been invented that would enable (with equal effectiveness) all problems faced by the power system to be solved. This article presents an overview and a short description of research works available in the literature in which the authors have used modern methods to solve various problems in the field of power engineering. The article is an introduction to the special issue entitled Advances in the Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering. It is an overview of various current problems and the various methods used to solve them, which are used to cope with difficult situations. The authors also pointed out potential research gaps that can be treated as areas for further research.

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Machine Learning in Operating of Low Voltage Future Grid

Mroczek

Pijarski

2022

Energies

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The article is a continuation of the authors’ ongoing research related to power flow and voltage control in LV grids. It outlines how the Distribution System Operator (DSO) can use Machine Learning (ML) technology in a future grid. Based on supervised learning, a Selectively Coherent Model of Converter System Control for an LV grid (SCM_CSC) is proposed. This represents a fresh, new approach to combining off and on-line computing for DSOs, in line with the decarbonisation process. The main kernel of the model is a neural network developed from the initial prediction results generated by regression analysis. For selected PV system operation scenarios, the LV grid of the future dynamically controls the power flow using AC/DC converter circuits for Battery Energy Storage Systems (BESS). The objective function is to maintain the required voltage conditions for high PV generation in an LV grid line area and to minimise power flows to the MV grid. Based on the training and validation data prepared for artificial neural networks (ANN), a Mean Absolute Percentage Error (MAPE) of 0.15% BESS and 0.51–0.55% BESS 1 and BESS 2 were achieved, which represents a prediction error level of 170–300 VA in the specification of the BESS power control. The results are presented for the dynamic control of BESS 1 and BESS 2 using an ANN output and closed-loop PID control including a 2nd order filter. The research work represents a further step in the digital transformation of the energy sector.

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DSO Strategies Proposal for the LV Grid of the Future

Cited by 4 publications

References 47 publications

Hardware-in-the-Loop Validation of an Energy Management System for LV Distribution Networks with Renewable Energy Sources

Hardware-in-the-Loop Validation of an Energy Management System for LV Distribution Networks with Renewable Energy Sources

Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue

Machine Learning in Operating of Low Voltage Future Grid

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