Tidal electric power plants — Sources of inexpensive, ecologically pure, renewable energy (30th anniversary of the Kislogubsk Tidal Power Plant)

1998 ◽  
Vol 32 (12) ◽  
pp. 699-704 ◽  
Author(s):  
V. D. Novozhenin ◽  
I. N. Usachev ◽  
B. L. Érlikhman
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Electric Power ◽  
Power Plants ◽  
Tidal Power ◽  
Tidal Power Plant ◽  
Electric Power Plants ◽  
30Th Anniversary

scholarly journals ELECTRIC POWER PRODUCED BY NON-SELF-PROPELLED HYDRO POWER VESSEL

2018 ◽  
pp. 92-102
Author(s):  
Liudmila Fedorovna Borisova ◽  
Aleksandr Nikolaevich Korobko
Keyword(s):  
Power Plant ◽  
Electric Power ◽  
Power Plants ◽  
Structural Characteristics ◽  
Plant Design ◽  
Power Module ◽  
Tidal Power ◽  
Energy Potential ◽  
Tidal Power Plant ◽  
Hydro Power

The article contains the method of calculating the electric capacity by a non-self-propelled hydro power vessel which uses renewable tidal power to produce electricity. The vessel is built by means of reconstructing tankers that are in service or to be disposed and can be characterized as a power generating module of a floating non-self-propelled tidal power plant of continuous operation. To evaluate efficiency of the power generated module there has been worked out a method of calculating its generated energy, which allows for local energy potential of the tidal flow, structural characteristics of the module and its geographical position. Based on the developed method there has been given analysis of power generated by one electric power module which can be made by means of construction minor modifications of a standard tanker design. The calculation data obtained were analyzed in comparison with power capacity of small hydroelectric power plants operating in the north-west parts of Russia and with capacity of Kislogubskaya tidal power plant. The tidal power plants can generate electric power comparable with the capacities of tidal (marine) and river-type power plants. The economic benefit of the proposed power plant design is obtained due to significant reduction of costs for implementing floating tidal power plant, compared to the costs of the construction of tidal and hydroelectric stations. The floating tidal power plant is characterized by mobility and can be towed to any coastal zone where the tidal wave parameters are acceptable. When needed, capacity of the floating tidal power plant can be raised by means of attaching additional modules. Mounting and operating of tidal power plants are environmentally secure. The use of tidal power plants is a promising means of electrification for inaccessible and marginal coastal areas.

scholarly journals Destructiveness of Profits and Outlays Associated with Operation of Offshore Wind Electric Power Plant. Part 1: Identification of a Model and its Components

2018 ◽  
Vol 25 (2) ◽  
pp. 132-139 ◽  
Author(s):  
Andrzej Tomporowski ◽  
Józef Flizikowski ◽  
Weronika Kruszelnicka ◽  
Izabela Piasecka ◽  
Robert Kasner ◽  
...  
Keyword(s):  
Power Plant ◽  
Electric Power ◽  
Power Plants ◽  
Electric Power Industry ◽  
Offshore Wind ◽  
Electric Power Plant ◽  
Domestic Markets ◽  
Electric Power Plants ◽  
Environmental Objects ◽  
Development Prospects

Abstract This paper describes identification and components of destructiveness of energy, economic and ecologic profits and outlays during life cycle of offshore wind electric power plants as well as the most useful models for their design, assembly and use. There are characterized technical conditions (concepts, structures, processes) indispensable for increasing profits and/or decreasing energy, economic and ecological outlays on their operation as well as development prospects for global, European and domestic markets of offshore wind electric power industry. A preliminary analysis was performed for an impact of operators, processed objects, living and artificial environmental objects of a 2MW wind electric power plant on possible increase of profits and decrease of outlays as a result of compensation of destructiveness of the system, environment and man.

scholarly journals INVESTIGATIONS OF ELECTRIC POWER QUALITY IN AUTONOMOUS LOW POWER PLANT

2017 ◽  
Vol 3 ◽  
pp. 136
Author(s):  
Andrei Khitrov ◽  
Alexander Khitrov ◽  
Evgeny Veselkov ◽  
Vyacheslav Tikhonov
Keyword(s):  
Power Plant ◽  
Low Power ◽  
Electric Power ◽  
Power Quality ◽  
Power Plants ◽  
Low Voltage ◽  
Energy Sources ◽  
Variable Speed ◽  
Electric Power Plants ◽  
Electric Power Quality

Autonomous low power electric power plants working with variable speed energy sources or electric subsystems of cogeneration plants of some type need to increase the low speed or the low voltage of the system. In this paper the investigations and the results of the experiments conducted using different structures are given.

scholarly journals Assessment of Power Plant Based on Unsafe Behavior of Workers through Backpropagation Neural Network Model

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Juan Shi ◽  
Dingyi Chang
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Electric Power ◽  
Bp Neural Network ◽  
Power Plants ◽  
Indicator System ◽  
Assessment Model ◽  
Electric Power Plants ◽  
Assessment Indicator ◽  
Unsafe Behavior

Safety is an essential topic for electric power plants. In recent years, accidents caused by unsafe behaviors of electric power plant employees are frequent. To promote the sustainable development and safety of electric power plants, studies on the assessment of unsafe behavior are becoming increasingly important and urgent. In this study, accident statistical analysis, literature review, and expert survey are adopted to select more comprehensive and accurate assessment indicators of unsafe behavior of the workers in electric power plants. Data about indicator and unsafe behavior were obtained through a questionnaire survey, and 27 indicators were used as inputs, and the unsafe behavior was taken as the output of a backpropagation (BP) neural network based unsafe behavior assessment model. An assessment indicator system about power plant workers’ unsafe behavior composed of 4 first-level indicators and 27 second-level indicators was established and the weights of the assessment indicators were determined. A three-layer feedforward BP neural network assessment model of “27-13-1” layers was found to be a suitable model. The proposed model can demonstrate the nonlinear complex relationship between the assessment indicator and the unsafe behavior of power plant workers. The model can be helpful to evaluate, predict, and monitor the safety performance of electric power plants.

Statistical Analysis for Shipboard Electrical Power Plant Design

2013 ◽  
Author(s):  
James M. Wolfe ◽  
Morgan M. Fanberg
Keyword(s):  
Power Plant ◽  
Power Systems ◽  
Electric Power ◽  
Power Distribution ◽  
Power Plants ◽  
Electrical Power ◽  
Plant Design ◽  
Electric Power Plants ◽  
Power Load ◽  
False Sense

The traditional electric power load analysis (EPLA) uses a very basic routine of assigning demand factors to each connected electric load, then summing these to arrive at an estimated power plant load. This method is overly simplistic, gives a false sense of certainty, and does not accurately reflect vessel operations. This paper will describe an alternative to traditional methods of determining ratings and configurations for electric power plants during vessel concept and preliminary design. This method uses statistical methods to calculate a range of possible power plant demand. Resulting data can be used to evaluate power plant configurations with respect to design risk, vessel operating profiles, and potential limitations. The ability to better evaluate the complete range of required electric power across all operating profiles increases in importance as vessel power plants become more sophisticated with the introduction of variable speed generation, battery/hybrid power systems, DC power distribution, and distributed load centers.

Control of Electric Power Plants and Systems

1987 ◽  
Vol 20 (9) ◽  
pp. 53-64
Author(s):  
H. Glavitsch
Keyword(s):  
Electric Power ◽  
Power Plants ◽  
Electric Power Plants
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