에너지경제연구 Korean Energy Economic Review Volume 15, Number 1, March 2016 : pp. 99 ~ 137 공휴일전력수요에관한산업별분석 1) 99
100
~ 101
102
103
max m ax 104
[ 그림 1] 제조업및서비스업대표업종전력사용량추이 105
106
[ 그림 2] 2014 년일별전자및전자기기업종 AMR 전력사용량 107
[ 그림 3] 2014 년 1 월전자및전자기기업종 AMR 전력사용량추이 log log 108
109
기온 110
cos sin cos sin log log cos sin 111
log log log log 112
log log log log 공휴일효과 113
114
< 표 1> 산업별공휴일효과의최대값 115
116
117
< 표 2> 공휴일효과 : A 군 118
< 표 3> 공휴일효과 : B 군 119
< 표 4> 공휴일효과 : C 군 120
< 표 5> 공휴일효과 : D 군 121
< 표 6> 공휴일효과 : E 군 122
~ 123
접수일 (2016 년 2 월 26 일 ), 게재확정일 (2016 년 3 월 13 일 ) 124
,, (2011),, 59(4): 199-228. Burns, A.F. and Mitchell, W.C. 1946, Measuring Business Cycles, National Bureau of Economic Research, New York. Clark, P. K. 1973, A Subordinated Stochastic Process with Finite Variance for Speculative Prices, Econometrica 41: 135-156. Fan, S. and Hyndman, R. J. 2011, The price elasticity of electricity demand in South Australia, Energy Policy (39): 3709-3719. Gallant, A. R. 1981, On the bias in flexible functional forms and an essentially unbiased form: the Fourier flexible form, Journal of Econometrics 15: 211-245. Kim, I.-M. 2003, Operational Time of the Korea Stock Markets, Economics Letters 78: 181-185. Maddala, G. S. and Kim, I.-M. (1998), Unit roots, cointegration, and structural change. Cambridge University Press. Moral-Carcedo, J. and Vicens-Otero, J. 2005, Modeling the non-linear response of Spanish electricity demand to temperature variations. Energy Economics 27: 477-494. Ng, S., and Perron, P. 1995, Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag, Journal of the American Statistical Association, 90(429): 268-281. Pardo, A., Meneu, V. and Valor, E. 2002, Temperature and seasonality influences on Spanish electricity loads, Energy Economics 24: 55-70. Park, J. Y. 1992, Canonical Cointegrating Regressions, Econometrica, 60: 119-143. Schwert, G. W. 1989, Tests for Unit Roots: A Monte Carlo Investigation, Journal of Business & Economic Statistics 7(2): 147-159. 125
Stock, J.H. 1987, Measuring Business Cycle Time, Journal of Political Economy 95: 1240-1261. Stock, J.H. 1988, Estimating Continuous-Time Processes Subject to Time Deformation: An Application to Postwar U.S. GNP, Journal of the American Statistical Association 83: 77-85. Valor E., Meneu. V., Caselles. V. 2001, Daily Air Temperature and Electricity Load in Spain, Journal of Applied Meterology 40: 1413-1421. 126
<A 1> AMR 전력사용량자료분류 -1 127
<A 1> AMR 전력사용량자료분류 -2 128
<A 1> AMR 전력사용량자료분류 -3 129
<A 2> 전력사용량분해모형추정결과 -1 130
<A 2> 전력사용량분해모형추정결과 -2 131
<A 2> 전력사용량분해모형추정결과 -3 132
<A 2> 전력사용량분해모형추정결과 -4 133
<A 2> 전력사용량분해모형추정결과 -5 134
<A 2> 전력사용량분해모형추정결과 -6 135
<A 2> 전력사용량분해모형추정결과 -7 136
ABSTRACT This paper, using AMR (Automatic Meter Reading) electricity data accurately measured by sectors in real time, analyses holiday effect on the industrial electricity usage. For this goal, the paper constructs and estimates a model which captures the properties of AMR time series including long-term trends, mid-term temperature effects, and short-term special day effects. Based on the estimated holiday effect, we categorize the whole industry into five groups according to the size of holiday effect and further investigate the characteristics and patterns of holiday effect in each group. These empirical results carry practical policy implications on the fulfillment real time electricity demand management and on the evaluation of the temporary price cut in saturday electricity usage. Key Words : Industrial electricity usage, Holiday effect, Electricity demand management, Canonical cointegrating regression 137