IDEAS home Printed from https://ideas.repec.org/a/sae/engenv/v29y2018i6p1004-1021.html
   My bibliography  Save this article

Performance estimation of Ntaruka hydropower plant and its comparison with the prediction results obtained by SPSS

Author

Listed:
  • Samuel Bimenyimana
  • Godwin Norense Osarumwense Asemota
  • Paula Jeanne Ihirwe
  • Cicilia Kemunto Mesa
  • Lingling Li

Abstract

Hydroelectricity has long been used in Rwanda. The Ntaruka hydropower plant was constructed during the colonial period in the northern part of Rwanda and it is still in operation. This paper evaluates the annual performance of this power plant and highlights several factors, which are vital for future predictions in the energy generation. Literature search and review coupled with energy generation analysis and forecasting were used for the study. Data were collected through site visits and discussions with the staff of the Rwanda Energy Group. Analysis were made by considering some performance factors of the power plant such as net capacity factor, plant use factor, power factor, voltage profile, frequency profile, general energy profile, and annual energy generation profile taking cognizance of hydropower plant installed capacity. Based on the available monthly operation hours of the power plant and its annual energy generation data between 2011 and 2014, predictions were made using the Statistical Package for Social Sciences (SPPS version 20.0) to forecast future energy generation for the power plant. Results show that the annual energy generation of the power plant varies between 1277 and 4524 MWh, with an average of 2912 MWh within the above years, which is much closer to the average real energy generation obtained between 2011 and 2015 and, therefore, the power plant is in good operating condition. Further research is recommended to consider using staffing levels, plant availability factors, and economic efficiency to determine the economic effectiveness and performance indices of the hydropower plant.

Suggested Citation

  • Samuel Bimenyimana & Godwin Norense Osarumwense Asemota & Paula Jeanne Ihirwe & Cicilia Kemunto Mesa & Lingling Li, 2018. "Performance estimation of Ntaruka hydropower plant and its comparison with the prediction results obtained by SPSS," Energy & Environment, , vol. 29(6), pages 1004-1021, September.
    • Handle: RePEc:sae:engenv:v:29:y:2018:i:6:p:1004-1021
    DOI: 10.1177/0958305X18765961
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0958305X18765961
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0958305X18765961?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stanley Smith & Terry Sincich, 1988. "Stability over time in the distribution of population forecast errors," Demography, Springer;Population Association of America (PAA), vol. 25(3), pages 461-474, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J Reilly, 1997. "A Method of Assigning Population and a Progress Report on the Use of a Spatial Simulation Model," Environment and Planning B, , vol. 24(5), pages 725-739, October.
    2. Jeff Tayman & Stanley Smith & Jeffrey Lin, 2007. "Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(3), pages 347-369, June.
    3. Jason Thomas & Samuel J. Clark, 2011. "More on the Cohort-Component Model of Population Projection in the Context of HIV/AIDS: A Leslie Matrix Representation and New Estimates," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(2), pages 39-102.
    4. Rodier, Caroline J. & Johnston, Robert A., 2002. "Uncertain socioeconomic projections used in travel demand and emissions models: could plausible errors result in air quality nonconformity?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(7), pages 613-631, August.
    5. Shobande Olatunji Abdul & Shodipe Oladimeji Tomiwa, 2020. "Re-Evaluation of World Population Figures: Politics and Forecasting Mechanics," Economics and Business, Sciendo, vol. 34(1), pages 104-125, February.
    6. Stefan Rayer & Stanley Smith, 2014. "Population Projections by Age for Florida and its Counties: Assessing Accuracy and the Impact of Adjustments," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 33(5), pages 747-770, October.
    7. Tom Wilson & Huw Brokensha & Francisco Rowe & Ludi Simpson, 2018. "Insights from the Evaluation of Past Local Area Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(1), pages 137-155, February.
    8. Stefan Rayer, 2007. "Population forecast accuracy: does the choice of summary measure of error matter?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(2), pages 163-184, April.
    9. Jeff Tayman, 2011. "Assessing Uncertainty in Small Area Forecasts: State of the Practice and Implementation Strategy," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 30(5), pages 781-800, October.
    10. Isengildina, Olga & Irwin, Scott H. & Good, Darrel L., 2006. "Empirical Confidence Intervals for WASDE Forecasts of Corn, Soybean and Wheat Prices," 2006 Conference, April 17-18, 2006, St. Louis, Missouri 18995, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    11. Jeff Tayman & Stanley Smith & Stefan Rayer, 2011. "Evaluating Population Forecast Accuracy: A Regression Approach Using County Data," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 30(2), pages 235-262, April.
    12. Tafirenyika Sunde & Olusegun A. Akanbi, 2016. "Sources of unemployment in Namibia: an application of the structural VAR approach," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 8(2), pages 125-143.
    13. Stanley Smith & Terry Sincich, 1991. "An Empirical Analysis of the Effect of Length of Forecast Horizon on Population Forecast Errors," Demography, Springer;Population Association of America (PAA), vol. 28(2), pages 261-274, May.
    14. Stefan Rayer & Stanley Smith & Jeff Tayman, 2009. "Empirical Prediction Intervals for County Population Forecasts," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 28(6), pages 773-793, December.
    15. Charles, Coleman, 1999. "Nonparametric Tests For Bias In Estimates And Forecasts," MPRA Paper 77841, University Library of Munich, Germany.
    16. Hana Sevcikova & Adrian E. Raftery & Patrick Gerland, 2018. "Probabilistic projection of subnational total fertility rates," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(60), pages 1843-1884.
    17. Stanley Smith & Jeff Tayman, 2003. "An evaluation of population projections by age," Demography, Springer;Population Association of America (PAA), vol. 40(4), pages 741-757, November.
    18. Isengildina-Massa, Olga & Irwin, Scott H. & Good, Darrel L., 2008. "Quantile Regression Methods of Estimating Confidence Intervals for WASDE Price Forecasts," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6409, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Sevcíková, Hana & Raftery, Adrian E. & Waddell, Paul A., 2007. "Assessing uncertainty in urban simulations using Bayesian melding," Transportation Research Part B: Methodological, Elsevier, vol. 41(6), pages 652-669, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:engenv:v:29:y:2018:i:6:p:1004-1021. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.