메뉴 건너뛰기




Volumn 9, Issue 11, 2017, Pages

Short-term multiple forecasting of electric energy loads for sustainable demand planning in smart grids for smart homes

Author keywords

Demand; Electricity; Energy; Forecast; Load; Modelling; Smart grid; Smart home

Indexed keywords

DECISION ANALYSIS; DEMAND ANALYSIS; DEMAND-SIDE MANAGEMENT; ELECTRICITY; ENERGY USE; FORECASTING METHOD; FUTURE PROSPECT; MODELING; SCENARIO ANALYSIS; SMART GRID; SUSTAINABLE DEVELOPMENT;

EID: 85032394358     PISSN: None     EISSN: 20711050     Source Type: Journal    
DOI: 10.3390/su9111972     Document Type: Article
Times cited : (28)

References (35)
  • 1
    • 84926193230 scopus 로고    scopus 로고
    • A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting
    • Xiao, L.; Wang, J.; Hou, R.; Wu, J. A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting. Energy 2015, 82, 524-549.
    • (2015) Energy , vol.82 , pp. 524-549
    • Xiao, L.1    Wang, J.2    Hou, R.3    Wu, J.4
  • 2
    • 84870024579 scopus 로고    scopus 로고
    • A hybrid annual power load forecasting model based on generalized regression neural network with fruit fly optimization algorithm
    • Li, H.; Guo, S.; Li, C.; Sun, J. A hybrid annual power load forecasting model based on generalized regression neural network with fruit fly optimization algorithm. Knowl.-Based Syst. 2012, 37, 378-387.
    • (2012) Knowl.-Based Syst. , vol.37 , pp. 378-387
    • Li, H.1    Guo, S.2    Li, C.3    Sun, J.4
  • 3
    • 84899129918 scopus 로고    scopus 로고
    • A hybrid neural network and genetic algorithm based model for short term load forecast
    • Islam, B.; Baharudin, Z.; Raza, Q.; Nallagownden, P. A hybrid neural network and genetic algorithm based model for short term load forecast. Res. J. Appl. Sci. Eng. Technol. 2014, 7, 2667-2673.
    • (2014) Res. J. Appl. Sci. Eng. Technol. , vol.7 , pp. 2667-2673
    • Islam, B.1    Baharudin, Z.2    Raza, Q.3    Nallagownden, P.4
  • 5
    • 84871720465 scopus 로고    scopus 로고
    • Short-term load forecasting using SVR (support vector regression)-based radial basis function neural network with dual extended Kalman filter
    • Ko, C.-N.; Lee, C.-M. Short-term load forecasting using SVR (support vector regression)-based radial basis function neural network with dual extended Kalman filter. Energy 2013, 49, 413-422.
    • (2013) Energy , vol.49 , pp. 413-422
    • Ko, C.-N.1    Lee, C.-M.2
  • 6
    • 80053572327 scopus 로고    scopus 로고
    • A methodology for electric power load forecasting
    • Almeshaiei, E.; Soltan, H. A methodology for electric power load forecasting. Alex. Eng. J. 2011, 50, 137-144.
    • (2011) Alex. Eng. J. , vol.50 , pp. 137-144
    • Almeshaiei, E.1    Soltan, H.2
  • 8
    • 85032362580 scopus 로고    scopus 로고
    • (accessed on 24 February 2017).
    • US Electricity Operating Data. U.S. ELECTRIC SYSTEM OPERATING DATA Available online: https://www.eia.gov/beta/realtime_grid/#/data/ graphs?end=20170402T00&start=20170326T00 (accessed on 24 February 2017).
    • U.S. ELECTRIC SYSTEM OPERATING DATA
  • 10
    • 84899701114 scopus 로고    scopus 로고
    • Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques
    • Fan, C.; Xiao, F.; Wang, S. Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques. Appl. Energy 2014, 127, 1-10.
    • (2014) Appl. Energy , vol.127 , pp. 1-10
    • Fan, C.1    Xiao, F.2    Wang, S.3
  • 13
    • 85032352476 scopus 로고    scopus 로고
    • (accessed on 24 November 2016).
    • OpenEI. Smart Energy Data: Terni Energy Consumption Profiles Available online: https://data.lab.fiware.org//dataset/b6ac9ad2-7b9e-4247-a785-81a88021995c/resource/3994b4ba-788a-4def-852f-043c71a20084/download/ternienergyconsumptionprofilecustomerindustrial1.csv (accessed on 24 November 2016).
    • Smart Energy Data: Terni Energy Consumption Profiles
  • 14
    • 0000320366 scopus 로고    scopus 로고
    • Application of least absolute value parameter estimation based on linear programming to short-term load forecasting
    • Soliman, S.A.; Persaud, S.; El-Nagar, K.; El-Hawary, M.E. Application of least absolute value parameter estimation based on linear programming to short-term load forecasting. Int. J. Electr. Power Energy Syst. 1997, 19, 209-216.
    • (1997) Int. J. Electr. Power Energy Syst. , vol.19 , pp. 209-216
    • Soliman, S.A.1    Persaud, S.2    El-Nagar, K.3    El-Hawary, M.E.4
  • 15
    • 84889668254 scopus 로고    scopus 로고
    • Comparison of conventional and modern load forecasting techniques based on artificial intelligence and expert systems
    • Badar, E.; Islam, U. Comparison of conventional and modern load forecasting techniques based on artificial intelligence and expert systems. Int. J. Comput. Sci. Issues 2011, 8, 504-513.
    • (2011) Int. J. Comput. Sci. Issues , vol.8 , pp. 504-513
    • Badar, E.1    Islam, U.2
  • 18
    • 67349154089 scopus 로고    scopus 로고
    • Electric load forecasting methods: Tools for decision making
    • Hahn, H.; Meyer-Nieberg, S.; Pickl, S. Electric load forecasting methods: Tools for decision making. Eur. J. Oper. Res. 2009 , 199, 902-907.
    • (2009) Eur. J. Oper. Res , vol.199 , pp. 902-907
    • Hahn, H.1    Meyer-Nieberg, S.2    Pickl, S.3
  • 19
    • 9244240793 scopus 로고    scopus 로고
    • Load forecasting using support vector Machines: A study on EUNITE competition 2001
    • Chen, B.-J.; Chang, M.-W.; Lin, C.-J. Load forecasting using support vector Machines: A study on EUNITE competition 2001. IEEE Trans. Power Syst. 2004, 19, 1821-1830.
    • (2004) IEEE Trans. Power Syst. , vol.19 , pp. 1821-1830
    • Chen, B.-J.1    Chang, M.-W.2    Lin, C.-J.3
  • 23
    • 85020889231 scopus 로고    scopus 로고
    • Performance comparison of short term load forecasting techniques
    • Cheepati, K.R.; Prasad, T.N. Performance comparison of short term load forecasting techniques. Int. J. Grid Distrib. Comput. 2016, 9, 287-302.
    • (2016) Int. J. Grid Distrib. Comput. , vol.9 , pp. 287-302
    • Cheepati, K.R.1    Prasad, T.N.2
  • 24
    • 79960898986 scopus 로고    scopus 로고
    • The comparison of fuzzy inference systems and neural network approaches with ANFIS method for fuel consumption data
    • Bursa, Turkey, 7-11 November.
    • Atmaca, H. The comparison of fuzzy inference systems and neural network approaches with ANFIS method for fuel consumption data. In Proceedings of the Second International Conference on Electrical and Electronics Engineering Papers ELECO, Bursa, Turkey, 7-11 November 2001; Volume 6, pp. 1-4.
    • (2001) Proceedings of the Second International Conference on Electrical and Electronics Engineering Papers ELECO , vol.6 , pp. 1-4
    • Atmaca, H.1
  • 26
    • 84920137471 scopus 로고    scopus 로고
    • A hybrid model for integrated day-ahead electricity price and load forecasting in smart grid
    • Wu, L.; Shahidehpour, M. A hybrid model for integrated day-ahead electricity price and load forecasting in smart grid. IET Gener. Transm. Distrib. 2014, 8, 1937-1950.
    • (2014) IET Gener. Transm. Distrib. , vol.8 , pp. 1937-1950
    • Wu, L.1    Shahidehpour, M.2
  • 27
    • 85032371800 scopus 로고    scopus 로고
    • Probabilistic scenario analysis
    • Yoe, C. Probabilistic scenario analysis. Princ. Risk Anal. 2011 , 399-420.
    • (2011) Princ. Risk Anal , pp. 399-420
    • Yoe, C.1
  • 28
    • 84937764904 scopus 로고    scopus 로고
    • Probabilistic solar power forecasting in smart grids using distributed information
    • Bessa, R.J.; Trindade, A.; Silva, C.S.; Miranda, V. Probabilistic solar power forecasting in smart grids using distributed information. Int. J. Electr. Power Energy Syst. 2015, 72, 16-23.
    • (2015) Int. J. Electr. Power Energy Syst , vol.72 , pp. 16-23
    • Bessa, R.J.1    Trindade, A.2    Silva, C.S.3    Miranda, V.4
  • 31
    • 85032389300 scopus 로고    scopus 로고
    • Chapter 6 Probabilistic Approaches: Scenario Analysis
    • Analysis, S. Chapter 6 Probabilistic Approaches: Scenario Analysis; Financial Times. pp. 1-61.
    • Financial Times , pp. 1-61
    • Analysis, S.1
  • 32
    • 85012297238 scopus 로고    scopus 로고
    • Entropy, Shannon's measure of information and Boltzmann's H-theorem
    • Ben-Naim, A. Entropy, Shannon's measure of information and Boltzmann's H-theorem. Entropy 2017, 19, 48.
    • (2017) Entropy , vol.19 , pp. 48
    • Ben-Naim, A.1
  • 33
    • 0002431740 scopus 로고    scopus 로고
    • Automatic construction of decision trees from data: A multi-disciplinary survey
    • Sreerama, K.M. Automatic construction of decision trees from data: A multi-disciplinary survey. Data Min. Knowl. Discov. 1998, 2, 345-389.
    • (1998) Data Min. Knowl. Discov , vol.2 , pp. 345-389
    • Sreerama, K.M.1
  • 35
    • 85032350255 scopus 로고    scopus 로고
    • UF Department of Statistics: Gainesville, FL, USA.
    • UF Department of Statistics. Statistical Tables; UF Department of Statistics: Gainesville, FL, USA, 2002; Volume II, pp. 1-26.
    • (2002) Statistical Tables , vol.2 , pp. 1-26


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.