<p>Investment cost associated to the generation of renewable energy such as wind and solar is generally estimated to be higher. As the wind and solar energy generation do not require any fuel, the marginal cost of electricity generation through renewable energy technologies is very low. Therefore, in the long run, the prices are expected to get reduced, once investment cost is recovered; whereas, in the short run, the expected energy price of electricity increases. However, the final electricity price depends on several factors such as distribution cost, operating cost, storage cost (if any), load factor, and cost associated to switching of technology for electricity generation through total energy mix. In case of solar and wind energy generation, the technologies have grid priorities, but solar and wind are highly sensitive to weather conditions. Therefore, to make the system efficient, an energy system also depends on coal fired plant, gas fired plants, nuclear plants, biomass, hydro, etc. for meeting the energy supply needs. Based on overall capacities, investment costs, energy imports and fuel prices, the final electricity prices are decided. With the current trends in advancement of technologies, and priority for one technology over the other, the prices can still fluctuate in the future. In the current energy literature, methods available for price forecasting followed the modelling approaches that use range of variables for forecasting the possible scenarios. These scenarios and forecasting might affect an investment decisions of investors. However, the challenging future scenario in European energy mix addresses the issue of falling electricity price while the renewable energy technologies getting cheaper; which tends to freeze further investments, unless sufficient government support is available. The current study aims to explore the various economic forecasting methods presented in the literature for the purpose of energy price modelling, in different contexts, such as geographies, demand, supply, marketing, strategy, etc. The results suggest a large variation in the methodologies being used by scientists to address the issues in different countries. A wide range of variable selection approach has been observed. Our study suggests that the current market has not researched well on long run forecasting methods. This study also aims to present some thoughts on energy marketing in the context of emerging economies, such as India for the energy policy framing. © 2015 The Authors. Published by Elsevier Ltd.</p>
cited By 0; Conference of International Conference on Alternative Energy in Developing Countries and Emerging Economies, AEDCEE 2015 ; Conference Date: 28 May 2015 Through 29 May 2015; Conference Code:121580
G. Sab Sisodia, Soares, Ic, Banerji, Sa, and Van Den Poel, Db, “The Status of Energy Price Modelling and its Relevance to Marketing in Emerging Economies”, in Energy Procedia, 2015, vol. 79, pp. 500-505.