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Hydropower Generation Plant Reliability Engineering

Abstract on Hydropower Generation Plant Reliability Engineering

Electricity is one of the main influencing factors in the advancement of a nation. There are multiple resources of electricity around the globe, both renewable and non-renewable. Renewable energy sources are regarded as more ecologically friendly. Hydropower generation plant is recognized as the most valuable electricity supply of all the alternative electricity sources. It is a component of renewable energy extracting electrical energy from the flow of water. Relative to other sources of renewable energy, hydropower has minimal social and environmental effects. The effective operation of the hydropower plant is very essential for generating full power by integrating the available potential. The present research was conducted to study the operational reliability of hydropower plants leading to the production of electricity with minimal maintenance costs as well as minimal environmental impact.

It has been found that the hydroelectric power has minimal maintenance costs and the water discharge, turbine and generator are the variables that influence the operation reliability.

Table of Contents

Introduction.

Maintenance Management

v Reliability.

v Maintenance.

v Maintenance Cost of hydro-power generation plant (MCtotal).

Operation of Hydro Power Generation Plant

Conclusion.

References.

Introduction to Hydropower Generation Plant Reliability Engineering

Reliability holds a very significant role in the safety, operation, and maintenance of the hydro-power generation plant. Rausand and Hoyland (2004) described reliability as a product's ability to accomplish a necessary task, under specified environmental and operating circumstances, and for a defined period. It involves observations such as performance, error frequency, and duration to recover. In today's world, when the fog has become more severe, the nation needs to change the climate by installing a hydropower generation plant.

Hydroelectric power generation plant is a power plant in the emerging power and sustainable resources with excellent operation reliability, broad dynamic range, long operational existence, relatively low cost and maintenance costs, and superior energy storage capability (Han, Liu, & Liu, et al., 2019). It has a wide variety of reliable, effective, and smooth device of power generation. It is, therefore necessary that these plants work properly to produce maximum operational reliability at low maintenance costs (Singh, & Singal, 2017). The main aim is to include the study of the reliability of hydro power plant operation, considering all the elements and variables that affect the operation.

The rest of this paper is organized as follows. In Section II, the variables used for hydropower generation will be discussed. In Section III, the operation of the hydro power plant will be discussed. Finally, Section IV concludes the paper.

Maintenance Management

Maintenance is essential to accomplish the operation of a machine. For cost-effectiveness and reliability, it is necessary to maintain proper maintenance. It is a term that involves details of how maintenance cost impacts on equipment and its reliability.

It describes:

v Reliability

Haugen, Barros, and Gulijk (2018) discussed the various metrics required for reliability is availability, dropout rate, and recovery time.

It affects additional aspects like circumstances, data management, maintenance, business case, spares, error and failure analysis, counterfeit components, productivity, and obsolescence.

Park and Cho (2008) investigated that the reliability of the details can be improved the data management by recording during the first 121 memory sections. Whenever a 1-bit error happens in the initial memory area, a storage segment of the very first document file is exchanged with an allocated data block, ensuring a likelihood of a 1-bit error existing on one page evenly and therefore, the reliability of data management can be enhanced by managing errors in the storage area.

De Francesco, Francesco and Petritoli (2018) discussed the benefit of using reliability in obsolescence by incorporating the area variable that is the large proportion of the area included. They consider reliability to the strength of the human aspect that helps in increasing the mechanical performance in turn. Reliability significantly increases productivity by minimizing manual management.

Availability (A) is an essential measure of reliability. It integrates both the outage time when a disruption happened and the disturbance intensity. It is the potential of an object to conduct the necessary task at a specified moment or over a defined duration of time under integrated variables of reliability, maintainability, and maintenance support.

Inherent availability (Ai) is the immediate likelihood of an object moving up or down. It considers the only downtime for maintenance to the faults (Koval, Zhang, & Propst, et al., 2003). It is represented as:

------------------------------------------------------------ (1)

Where,

MTBF (Mean Time between Failures): It implies the average time of exposure during errors. The failure or fault rate corresponds to the number of losses per unit time. When errors are spread uniformly, dropout rate becomes stable over time and is represented by:

Failure Mode and Effect Analysis (FMEA) can be employed in reliability analysis. It assists in locating all the forms the machine can fail, including determining essential elements for machine reliability.

MTTR (Mean Time to Repair): It is the average period to substitute or repair a failed device. It is given by symbol “r”.
The relationship between availability, dropout rate, and recovery time is given by:

Ai = 1- Unavailability (U) = 1- (λ*r) ----------------------------------- (2)

v Maintenance

 As per the Swedish Standard, maintenance is defined as a mixture of all mechanical, functional, and operational activities over the development process of a device constructed to stabilize it in or rebuild it to a condition where it can carry out the necessary tasks. Two significant maintenance optimizing parameters are reliability and cost.

It should be designed in such a manner that the reliability is high, and the device operation and reliability are maintained at the lowest possible net cost. It makes use of the RCAM technique.

Reliability Centered Asset Management, RCAM

The goal of RCAM is to correlate proactive maintenance to the overall cost of maintenance and device reliability. It is employed concerning reliability and cost while analyzing various preventive maintenance techniques (Shayetesh, & Hilber, 2016).

The primary phases of the RCAM method are as follows:

  • Device reliability analysis: It describes the device and investigates significant elements that influence the reliability of the device.
  • Element reliability modeling: It reviews the modules in-depth and describes the quantitative correlation between reliability and corrective maintenance activities with the help of adequate input variables.
  • Operation reliability and maintenance cost analysis: It investigates the effectiveness of device maintenance on reliability as well as cost involvement.

v Maintenance Cost of Hydro-Power Generation Plant (MCtotal)

A maintenance cost model for hydro-power generation plant has been described as:

MCtotal= CGL+CCM+CPM ---------------------------------------- (3)

Where,

  • CGL (EUR/Wh): It is the cost of generation loss. In the generation of power, the cost of delay is the cost of power generation loss, which in turn given by:

CGL = CPB*ENS ---------------------------------------------------- (4)

Where CPB is the cost per energy unit times,

ENS (Energy Not Supplied) is not transferred power in a year (WH) and is represented as:

ENS = x*8760*U ------------------------------------------------- (5)

Where x is the number of MWh/h, 8760 is the number of hours per year and U is the unavailability.

  • CCM is the cost for corrective maintenance, and
  • CPMis the cost of preventive maintenance.

Operation of Hydro Power Generation Plant

The fundamental concept of generating hydropower (HP) is the impulse-momentum. HP is extracted by utilizing the potential energy or the gravitational force of the running water stream.

A typical architecture of a Hydro power plant is shown in figure 1. An HP plant has to be installed in a region of running water to extract the HP power. The elements of an HP are a reservoir, penstock tube, water turbine, and generator (Min, et al., 2018).

Here, water potential is converted into mechanical power by spinning the engine, and mechanical energy is further transformed into electrical energy by using a generator.

The water is collected in a dam or reservoir and discharged downwards across a tube called the penstock the potential energy generated is utilized to conduct the operation. As, the water then strikes the turbine blades and spins the mechanical shaft, which transforms potential energy into mechanical energy that runs a generator at the power plant and generates electricity/power afterward (Kadier et al., 2017).

Hence, the operational reliability of the hydroelectric power station's generating units will be such that it must be ready for generating whenever the grid demands (Sharma, et al., 2015).

Hydropower integrates head and stream and is proportional to their product (Min, et al., 2018). Appropriate head and discharge calculations are essential for determining site capacity, choosing a suitable turbine, and constructing the power plant (Kumar et al., 2011).

The general form for hydro power generation unit is given by equation (6) (Singh, & Singal, 2017):

P = h*q*g*ρ*η -------------------------------------------------------- (6)

Where,

P is the mechanical power generated at the turbine shaft,

h: head in m,

q: water discharge in m3/s,

g: gravitational acceleration in m/s2,

η: the hydraulic efficiency of the turbine and

ρ: the density of water in kg/m3.

As per the Hydropower Status Report (2020), a new installation of hydropower plant by region is shown below:

The cost of maintenance for hydropower varies considerably based on the location, construction preferences, and local labor and equipment costs (Gielen, 2012). Hydropower has no cost of fuel and the low cost of the electricity generation unit. Hence, the maintenance costs are considerably low.

The maintenance cost of hydro power generation unit can be measured by using equation (7):

COST (per kW) = α*P1-β*Hβ1 ……………………………….. (7)

Where,

P is the power in kW of the turbines,

H is the head in meters,

α is a constant, and

β and β1 are the coefficients for power and head, respectively.

Utilizing reliability as a metric, decision-makers can evaluate the architecture of the framework more accurately so that it can maximize operations and thereby increase productivity greatly (Nicholds, & Mo, 2018).

Conclusion on Hydropower Generation Plant Reliability Engineering

The summary report has been implemented to study the effect of reliability and maintenance cost of hydro power generation plant. It has been observed that head, release, turbine, and generator are the variables that affect the operation reliability of the hydropower plant. The maintenance cost of a hydropower plant is very low.

References for Hydropower Generation Plant Reliability Engineering

Bratanova, A., Robinson, J., & Wagner, L. (2016). New technology adoption for Russian energy generation: What does it cost? A case study for Moscow. Applied Energy, 162, 924-939. 10.1016/j.apenergy.2015.10.102.

De Francesco, E., Francesco, R., & Petritoli, E. (2017). Obsolescence of the MIL-HDBK-217: A critical review. IEEE International Workshop on Metrology for Aerospace, 282-286. 10.1109/MetroAeroSpace.2017.7999581

Gielen, D. (2012). Renewable energy technologies: cost analysis series. International Renewable Energy Agency.

Han, Q., Liu, Z. L., Liu, S. L., & Xu, N. (2019). Analysis on operation reliability of hydropower units in China. International Conference on New Energy and Future Energy System, 354. 10.1088/1755-1315/354/1/012032

Haugen, S., Barros, A., & Gulijk C. V. (2018). Safety and Reliability – Safe Societies in a Changing World. London: CRC Press. https://doi.org/10.1201/9781351174664

Hydropower status report (2020). International Hydropower Association. https://www.hydropower.org/statusreport

Kumar, R., Singal, S.K., Dwivedi, G., & Shukla, A. K. (2020). Development of maintenance cost correlation for high head run of river small hydro power plant. International Journal of Ambient Energy. 10.1080/01430750.2020.1804447

Kadier, A., Kalil, M. S., Pudukudy, M., Hasan, H. A., Mohamed, A., & Hamid, A. A.

(2017). Pico hydropower (PHP) development in Malaysia: Potential, present status,

barriers and future perspectives. Renewable and Sustainable Energy Reviews, 81,

2796-2805.

Koval, D. O., Zhang, X., Propst, J., Coyle, T., Arno, R., & Hale, R. S. (2003). Reliability methods applied to the IEEE gold book standard network. IEEE Industry Applications Magazine, 9(1), 32-41. 10.1109/MIA.2003.1176457.

Min, H. S., Wagh, S., Kadier, A. & Gondal, I. A., Azim, N., & Mishra, M. (2018). Renewable Energy Technologies. Ideal International E – Publication Pvt. Ltd.

Nicholds, B.A., & Mo, J. P.T. (2018). Reliability analysis of productivity enhancement initiatives. Journal of Manufacturing Technology Management, 29(6), 1003-1024. https://doi.org/10.1108/JMTM-12-2016-0187

Park, J. Y., & Cho, H. D. (2008). Data management technique for improving data reliability. US Patent.

Singh, V. K., & Singal, S. K. (2017). Operation of hydro power plants-a review. Renewable and Sustainable Energy Reviews, 69, 610–619. http://dx.doi.org/10.1016/j.rser.2016.11.169

Sharma, R. N., Chand, N., Sharma, V., & Yadav, D. (2015). Decision support system for operation, scheduling and optimization of hydro power plant in Jammu and Kashmir region. Renew Sustain Energy Rev, 43, 1099–113.

Shayesteh, E., & Hilber, P. (2016). Reliability-centered asset management using component reliability importance. International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 1-6. 10.1109/PMAPS.2016.7764173.

Rausand, M., & Hoyland, A. (2004). System Reliability Theory, Second Edition, New Jersey.

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