Forecasting the Future of Alternative Energy Technologies Using Economic Payback Curves

Author： Nowakowski Gary A.   Hahn Michael P.  

Publisher： Taylor & Francis Ltd

ISSN： 2156-3306

Source： Distributed Generation & Alternative Energy Journal, Vol.28, Iss.3, 2013-07, pp. : 28-52

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Forecasting monthly electric load and energy for a fast growing utility using an artificial neural network

By Islam S.M.   Al-Alawi S.M.   Ellithy K.A.  

Electric Power Systems Research, Vol. 34, Iss. 1, 1995-07 ,pp. : 1-9

Elsevier

Access to resources Recommend Favorite

Long-term Sector-wise Electrical Energy Forecasting Using Artificial Neural Network and Biogeography-based Optimization

By Kumaran Jayaraman   Ravi Govindasamy  

Electric Power Components and Systems, Vol. 43, Iss. 11, 2015-07 ,pp. : 1225-1235

Taylor & Francis Ltd

Access to resources Recommend Favorite

High Temperature Low Sag Upgrades and Payback for the Economic Operation Improvement of Power Transmission Systems

By Tokombayev Askhat   Heydt Gerald Thomas  

Electric Power Components and Systems, Vol. 43, Iss. 3, 2015-02 ,pp. : 345-355

Taylor & Francis Ltd

Access to resources Recommend Favorite

Transmision capability enhancement using power electronics technologies for the future power system in Japan

By Hayashi T.   Takasaki M.  

Electric Power Systems Research, Vol. 44, Iss. 1, 1998-01 ,pp. : 7-14

Elsevier

Access to resources Recommend Favorite

The future of renewable energy industries

By Silverman M.   Worthman S.  

The Electricity Journal, Vol. 8, Iss. 2, 1995-03 ,pp. : 12-31

Elsevier

Access to resources Recommend Favorite