scholarly journals Nodal and fixed price coexistence in distribution networks with optimal investment planning and tariff design

2020 ◽  
Author(s):  
Iacopo Savelli ◽  
Cameron Hepburn ◽  
Thomas Morstyn
Keyword(s):  
Optimal Investment ◽  
Distribution Networks ◽  
Investment Planning ◽  
Fixed Price

scholarly journals An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks

2016 ◽  
Vol 6 (3) ◽  
pp. 1294
Author(s):  
Dragan Mlakić ◽  
Srete N Nikolovski ◽  
Goran Knežević
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Low Voltage ◽  
Distribution Networks ◽  
Investment Planning ◽  
Smart Meters ◽  
Fuzzy Logic Systems ◽  
Inference System ◽  
Neuro Fuzzy

The losses in distribution networks have always been key elements in predicting investment, planning work, evaluating the efficiency and effectiveness of a network. This paper elaborates on the use of fuzzy logic systems in analyzing the data from a particular substation area predicting losses in the low voltage network. The data collected from the field were obtained from the Automatic Meter Reading (AMR) and Automatic Meter Management (AMM) systems. The AMR system is fully implemented in EPHZHB and integrated within the network infrastructure at secondary level substations 35/10kV and 10(20)/0.4 kV. The AMM system is partially implemented in the areas of electrical energy consumers; precisely, in accounting meters. Daily information gathered from these systems is of great value for the calculation of technical and non-technical losses. Fuzzy logic in combination with the Artificial Neural Networks implemented via the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used. Finally, FIS Sugeno, FIS Mamdani and ANFIS are compared with the measured data from smart meters and presented with their errors and graphs.

An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks

2016 ◽  
Vol 6 (3) ◽  
pp. 1294
Author(s):  
Dragan Mlakić ◽  
Srete N Nikolovski ◽  
Goran Knežević
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Low Voltage ◽  
Distribution Networks ◽  
Investment Planning ◽  
Smart Meters ◽  
Fuzzy Logic Systems ◽  
Inference System ◽  
Neuro Fuzzy

The losses in distribution networks have always been key elements in predicting investment, planning work, evaluating the efficiency and effectiveness of a network. This paper elaborates on the use of fuzzy logic systems in analyzing the data from a particular substation area predicting losses in the low voltage network. The data collected from the field were obtained from the Automatic Meter Reading (AMR) and Automatic Meter Management (AMM) systems. The AMR system is fully implemented in EPHZHB and integrated within the network infrastructure at secondary level substations 35/10kV and 10(20)/0.4 kV. The AMM system is partially implemented in the areas of electrical energy consumers; precisely, in accounting meters. Daily information gathered from these systems is of great value for the calculation of technical and non-technical losses. Fuzzy logic in combination with the Artificial Neural Networks implemented via the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used. Finally, FIS Sugeno, FIS Mamdani and ANFIS are compared with the measured data from smart meters and presented with their errors and graphs.

scholarly journals Optimal Investment Planning of Bulk Energy Storage Systems

2018 ◽  
Vol 10 (3) ◽  
pp. 610 ◽  
Author(s):  
Dina Khastieva ◽  
Ilias Dimoulkas ◽  
Mikael Amelin
Keyword(s):  
Energy Storage ◽  
Storage Systems ◽  
Optimal Investment ◽  
Investment Planning ◽  
Energy Storage Systems ◽  
Bulk Energy

Smart Planning: an innovative tool for the investment planning of smart distribution networks

2017 ◽  
Vol 2017 (1) ◽  
pp. 2539-2542 ◽  
Author(s):  
Parvathy Chittur Ramaswamy ◽  
Christophe Del Marmol ◽  
Damien Schyns ◽  
François-Xavier Bouchez ◽  
Stéphane Rapoport ◽  
...  
Keyword(s):  
Distribution Networks ◽  
Investment Planning ◽  
Innovative Tool

scholarly journals Research on Forecasting Method of Distribution Network Investment Scale of Municipal Power Supply Enterprise Considering Power Supply Division and Cost Difference Level

2021 ◽  
Vol 245 ◽  
pp. 01032
Author(s):  
Gou Quanfeng ◽  
Yang Jie ◽  
Zhou Fei ◽  
Hu Lin ◽  
Yu Guangxiu ◽  
...  
Keyword(s):  
Power Supply ◽  
Large Scale ◽  
Distribution Network ◽  
Forecast Model ◽  
Distribution Networks ◽  
Lean Management ◽  
Investment Planning ◽  
Management Level ◽  
Network Investment ◽  
The Impact

In recent years, in order to adapt to the situation of rapid economic and social development, my country’s power supply companies have invested large-scale funds to build distribution networks, and upgraded urban and rural power grids, effectively supporting the rapid growth of power demand and the reliability of power supply. Continuous improvement of power quality. While the scale of investment in the distribution network continues to remain high, problems such as focusing on investment and neglecting revenue, focusing on project establishment and neglecting management also exist to varying degrees. Therefore, reasonably predicting the scale of investment in the distribution network and improving the lean management level of the investment and construction of the distribution network have become key issues that power supply companies need to solve. This paper takes my country’s municipal power supply companies as the research object, combines the actual business development of the company’s distribution network investment planning, and fully considers the impact of the company’s power supply district management and the level of cost differences on the investment scale of the distribution network, and builds a fit on this basis. The distribution network investment planning forecast model of the actual business work of the enterprise guides the municipal power supply enterprises to improve the lean management level of the distribution network investment and construction.

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