Decision Support System to Determine the Replacement Ranking of the Aged Transformers in Electric Distribution Networks

Chelaru, Ecaterina; Grigoraș, Gheorghe

doi:10.1109/ecai50035.2020.9223122

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…Chelaru and Grigoras proposed in [40] a system expert-based decision-making framework to help the DNOs identify the most appropriate replacement transformer fleet solution according to the different priority categories. The expert system determines the order of the ageing transformers in a replacement ranking.…”

Section: Of 25mentioning

confidence: 99%

Expert System Integrating Rule-Based Reasoning to Voltage Control in PV-Rich Low Voltage Electric Distribution Networks

Dandea¹,

Grigoraș²

2023

Preprint

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Nowadays, in low voltage (LV) electric distribution networks (EDNs), the Distribution Network Operators (DNOs) are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic (PV) prosumers. The irregular behavior of the prosumers, together with the uncertainty degree of the requested and injected powers associated with all end-users from the LV EDN, can cause voltage variations with violations of the allowable limits. In this context, the paper developed an efficient and resilient expert system integrating the rule-based reasoning applied to the On-load Tap Changer (OLTC)-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators: the penetration degree of the PV prosumers, consumption evolution associated with the consumers, and energy production of the PV systems, has been performed to demonstrate the efficiency of the proposed expert system in an LV EDN from a rural area belonging to a Romanian DNO. The success rate of the expert system has been 86.7% (65 out of 75 scenarios didn't have voltage issues, all values being between the allowable limits in 100% of the time slots associated with the analyzed period). For the other scenarios (representing 13.3%), the values have been inside the range [-10%, +10%] at least 95% of the time slots, according to the European Power Quality Standard, and for the rest of the time slots up to 100% being very close to the upper and lower limits of the range, with highly mitigating of the voltage variations.

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Section: Of 25mentioning

confidence: 99%

Expert System Integrating Rule-Based Reasoning to Voltage Control in PV-Rich Low Voltage Electric Distribution Networks

Dandea¹,

Grigoraș²

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Chelaru and Grigoras proposed in [38] an expert-system-based decision-making framework to identify the most appropriate replacement transformer fleet solution. The expert system determines the order of the ageing transformers in a replacement ranking according to the different priority categories.…”

Section: Figurementioning

confidence: 99%

Expert System Integrating Rule-Based Reasoning to Voltage Control in Photovoltaic-Systems-Rich Low Voltage Electric Distribution Networks: A Review and Results of a Case Study

Dandea

Grigoraș

2023

Applied Sciences

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Nowadays, in low voltage electric distribution networks, the distribution network operators are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic prosumers. The intermittent nature of the prosumers, together with the degree of uncertainty of the requested and injected powers associated with all end-users from low voltage electric distribution networks, can cause voltage variations that violate the allowable limits. In this context, this paper developed an efficient and resilient expert system integrating rule-based reasoning applied to the on-load tap changer-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators—the penetration degree of the photovoltaic prosumers, the consumption evolution associated with the consumers, and the energy production of the photovoltaic systems—was performed to demonstrate the efficiency of the proposed expert system in a low voltage electric distribution network from a rural area belonging to a Romanian distribution network operator. The success rate of the expert system was 86.7% (65 out of 75 scenarios did not have voltage issues). All voltages were between the allowable limits in 100% of the time slots associated with the analysed period. For the other scenarios (representing 13.3%), voltages were inside the range [−10%, +10%] in at least 95% of the time slots.

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Using hybrid-CBR for intelligence monitoring and decision-making systems on SMART grid

Glukhikh

Ilya

Glukhikh

2022

IDT

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Smart grid systems are being actively developed and implemented all over the world. However, along with developed systems for monitoring and data analysis, decision support functions are not fully implemented. Wherein decision support is necessary due to the complexity of possible emergencies. In this work, we offer the concept of an intelligent decision support system (IDSS) for the SMART grid, which is based on the hybrid Case-Based Reasoning (CBR) method. This method combines models of knowledge-based systems and models of neural networks and machine learning, which simplifies realization on complex changing objects of the SMART grid. In the first part of the research, we describe the concept of the proposed hybrid-CBR method, the principle of formalizing the situation at the objects of the SMART grid systems and present the involved neural network architecture Comparator-Adder. The second parts of the research reveal the concept of applied IDSS and also show the results of an experiment of retrieving precedent from a knowledge base with using a neural network. Experimental results show that our architecture successfully copes with the task of selecting the most similar situation. We believe that the MAPE error in this incident does not play a key role; the efficiency of the neural network is confirmed primarily by the coherence with the results of the expert choice and the absence of collisions.

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Decision Support System to Determine the Replacement Ranking of the Aged Transformers in Electric Distribution Networks

Cited by 4 publications

References 14 publications

Expert System Integrating Rule-Based Reasoning to Voltage Control in PV-Rich Low Voltage Electric Distribution Networks

Expert System Integrating Rule-Based Reasoning to Voltage Control in PV-Rich Low Voltage Electric Distribution Networks

Expert System Integrating Rule-Based Reasoning to Voltage Control in Photovoltaic-Systems-Rich Low Voltage Electric Distribution Networks: A Review and Results of a Case Study

Using hybrid-CBR for intelligence monitoring and decision-making systems on SMART grid

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