Investigations on PMBLDCG for Micro Hydro Power Generation

2021 ◽  
Author(s):  
Nikhil Bhati ◽  
Ujjwal Kumar Kalla
Keyword(s):  
Power Generation ◽  
Hydro Power

scholarly journals Power Generation In Nigeria: The Past, Present And The Future

2020 ◽  
pp. 1-8
Author(s):  
Adeoye Samuel ◽  
◽  
Oladimeji TT ◽  
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
Electrical Energy ◽  
Power Imbalance ◽  
Power Demand ◽  
Electrical Power System ◽  
Hydro Power ◽  
The Future

The goal of power sector in Nigeria is to efficiently and reliably transmit electrical power to all parts of the country which are made up of thirty-six states of the federation and the federal capital territory. The constituents of electrical power system are the generation, transmission, distribution and the utilization of electrical energy. There is gross power imbalance between the generation and the required power demand which has culminated into a defective economy in the last three decades. This paper therefore examines the power imbalance between the generation and power demand by the consumers and therefore stresses the need to harness the opportunity of renewable energy generation close to the gap between the power generation and power demand. This will help in transmitting and distributing efficient, effective, reliable power to consumers and improve both human and capital development. The availability of renewable energy sources such as sun, wind and small hydro power will be explored for the future of power generation in the country to fill in the gap between power generation and demand in Nigeria

scholarly journals Integrating the PV-Diesel Hybrid System for Reliability Improvement in Distribution System

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
Cho Cho Myint ◽  
Ohn Zin Lin ◽  
Soe Soe Ei Aung
Keyword(s):  
Power Generation ◽  
Distributed Generation ◽  
Hybrid System ◽  
System Reliability ◽  
Distribution System ◽  
Voltage Drop ◽  
Load Condition ◽  
Voltage Profile ◽  
Hydro Power ◽  
Reliability Indices

In Myanmar, as the main power generation is hydro power generation. the utility cannot supply sufficient power to customers during the dry season. Besides interruptions occur frequently due to aging system and lack of prospered protection. Therefore, reliability is an urgent issue in Myanmar. As a result of unbalance between generation and load, the distribution system is getting poor voltage profile, instability and high power losses in high load condition. According to network characteristics, the failure of a component always leads to consequence interruption in a radial distribution system.  Therefore, it is a must consideration to mitigate these challenges to enhance the system reliability. There are many techniques to solve the reliability problems such as reclosers, switching devices (manual and automated switches), system reconfiguration, feeder re-conducting and integration of distributed generation (DG). In this paper, system reliability assessment is evaluated in detail with the integration of the distributed generation such as PV-Diesel Hybrid System. The location of DG is chosen according to the expected energy not supply (EENS) and the voltage drop in proposed system. Next, the optimal sizing of DG is chosen depends on the penetration level of generator. Reliability indices can be evaluated depending on the failure rate(λ), repair time(r) and annual outage time(U) in Electrical Transient and Analysis Program (ETAP) software. The case study of this thesis is carried out in 33/11 kV network which is connected Kyatminton Substation, Kyaukse, Middle Myanmar.

scholarly journals Reconstruction of Multidecadal Country-Aggregated Hydro Power Generation in Europe Based on a Random Forest Model

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1786
Author(s):  
Linh T. T. Ho ◽  
Laurent Dubus ◽  
Matteo De Felice ◽  
Alberto Troccoli
Keyword(s):  
Power Generation ◽  
Random Forest ◽  
Model Performance ◽  
Absolute Error ◽  
Random Forest Model ◽  
Low Carbon ◽  
Climate Data ◽  
Hydro Power ◽  
Forest Model ◽  
Continental Scale

Hydro power can provide a source of dispatchable low-carbon electricity and a storage solution in a climate-dependent energy mix with high shares of wind and solar production. Therefore, understanding the effect climate has on hydro power generation is critical to ensure a stable energy supply, particularly at a continental scale. Here, we introduce a framework using climate data to model hydro power generation at the country level based on a machine learning method, the random forest model, to produce a publicly accessible hydro power dataset from 1979 to present for twelve European countries. In addition to producing a consistent European hydro power generation dataset covering the past 40 years, the specific novelty of this approach is to focus on the lagged effect of climate variability on hydro power. Specifically, multiple lagged values of temperature and precipitation are used. Overall, the model shows promising results, with the correlation values ranging between 0.85 and 0.98 for run-of-river and between 0.73 and 0.90 for reservoir-based generation. Compared to the more standard optimal lag approach the normalised mean absolute error reduces by an average of 10.23% and 5.99%, respectively. The model was also implemented over six Italian bidding zones to also test its skill at the sub-country scale. The model performance is only slightly degraded at the bidding zone level, but this also depends on the actual installed capacity, with higher capacities displaying higher performance. The framework and results presented could provide a useful reference for applications such as pan-European (continental) hydro power planning and for system adequacy and extreme events assessments.

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