The impact of adoption of power factor correction technology on electricity peak demand in Uganda
Tóm tắt
This paper examines the impact of adoption of power factor correction technology on electricity peak demand in Uganda. Specifically, the paper examines the variability of peak electricity demand in the periods before and after the implementation of power factor improvement schemes and assesses the likely impact of power factor improvement schemes on peak demand. Results suggest that power factor correction technology implemented among industries and commercial enterprises increased the power factor in these industries from an average of 0.68 to 0.95 and saved up to 8.04 MVA of demand as at the end of 2014. Results further indicate that the implementation of the power factor correction scheme has reduced the growth rate and abated the variability of both total maximum/peak demand and domestic peak demand. Finally, with the implementation of power factor correction scheme, there is a noticeable reduction in electricity consumption at peak time of use (TOU) and growth in consumption of electricity at nonpeak time TOU, which was not the case before the implementation of the scheme.
Tài liệu tham khảo
ABB (2010) Power factor correction and harmonic filtering in electrical plants”, ABB technical application paper no. 8
Barker S, Mishra, A, Irwin, D, Shenoy, P, Albrecht, J (2012) Smartcap: flattening peak electricity demand in smart homes. In pervasive computing and communications (PerCom), 2012 IEEE International Conference on (pp. 67–75). IEEE
Bhatia A (2012) Power factor in electrical energy Management. PDH online course E144 (4 PDH)
Clogg CC, Petkova E, Haritou A (1995) Statistical methods for comparing regression coefficients between models. Am J Sociol 100:1261–1293
Eberhard A, Shkaratan M (2012) Powering Africa: meeting the financing and reform challenges. Energy Policy 42:9–18
Eberhard A, Foster V, Briceño-Garmendia C, Ouedraogo F, Camos D, Shkaratan M (2008) Underpowered: the state of the power sector in Sub-Saharan Africa, Africa infrastructure country diagnostic, background paper 6. World Bank, Washington
Gillingham K, Newell RG, Palmer K (2009) Energy efficiency economics and policy National Bureau of Economic Research, Research paper no. w15031
Gyamfi S, Krumdieck S, Urmee T (2013) Residential peak electricity demand response—highlights of some behavioural issues. Renew Sustain Energy Rev 25:71–77
Heffner G, Maurer L, Sarkar A, Wang X (2010) Minding the gap: World Bank’s assistance to power shortage mitigation in the developing world. Energy 35(4):1584–1591
International Energy Agency (IEA) (2013) Energy efficiency market report. IEA, Paris
Linares P, Labandeira X (2010) Energy efficiency: economics and policy. J Econ Surv 24(3):573–592
Lo AW, MacKinlay AC (1989) The Size and power of the variance ratio test in finite samples: a monte carlo investigation. J Econ 40:203–238
MacKinnon JG (2002) Bootstrap inference in econometrics. Can J Econ 35:615–645
Mawejje J, Munyambonera E, Bategeka L (2013) Powering ahead: the reform of the electricity sector in Uganda. Energy Environ Res 3(2):126–138
Mukherji S (2014) Uganda—Uganda: energy for rural transformation APL-2: P112334—implementation status results report : sequence 09. World Bank Group, Washington
Never B (2014) Making energy efficiency pro-poor: insights from behavioral economics for policy design. German Development Institute (DIE), Discussion Paper 11/2014, Bonn, Germany
Never B (2015) Behave and save? behaviour, energy efficiency and performance of MSEs in Uganda. German Development Institute (DIE), Discussion Paper, Bonn, Germany
Oldewurtel F, Ulbig A, Parisio A, Andersson, G, Morari, M (2010) Reducing peak electricity demand in building climate control using real-time pricing and model predictive control. In decision and control (CDC), 49th IEEE Conference on (pp. 1927–1932), IEEE
Potter K (2006) Methods for presenting statistical information: the box plot. University of Utah, School of Computing, Salt Lake City, UT
Psiloglou BE, Giannakopoulos C, Majithia S, Petrakis M (2009) Factors affecting electricity demand in Athens, Greece and London, UK: a comparative assessment. Energy 34(11):1855–1863
Royston P, Sauerbrei W (2008) Multivariable model-building: a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables. Vol 777. John Wiley & Sons, Chichester, England
Ryan L, Campbell N (2012) Spreading the net: the multiple benefits of energy efficiency improvements. International Energy Agency Insights Series 2012
Schneider Electric (2008) Energy efficiency in electrical distribution. Schneider Electric, Electrical Installation Guide, Rueil-Malmaison, France
World Bank (2012) Implementation completion and results report for power sector development operation (IDA-42970) report no: ICR2159. The World Bank, Washington
Worrell E, Laitner JA, Ruth M, Finman H (2003) Productivity benefits of industrial energy efficiency measures. Energy 28(11):1081–1098