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In India, solar tariff has been witnessing a continuous fall since the announcement of revised targets for the National Solar Mission (NSM) in the year 2015. This paper discusses components that decide the solar tariff and demonstrates the role of various incentives being provided in bridging the tariff gap between solar and conventional power. The paper concludes with a comparison of various incentives (viability gap funding (VGF), accelerated depreciation (AD), generation-based incentive (GBI), etc.) based on the cost-effectiveness index. Based on the analysis, it is recommended that as levelised cost of energy (LCOE) is coming down, the government may think of pulling back some of the incentive schemes such as VGF, AD, and GBI while some hidden incentive schemes such as waiver of inter and/or intrastate transmission charges and losses, etc may continue. [ABSTRACT FROM AUTHOR]

The demand for solar photovoltaic (SPV) systems is growing all over the world due to the continuous increase in the cost of conventional means of power. India has the advantage of around 300 clear sunny days in a year. However, the biggest problem is conversion efficiency. In this paper, an attempt has been made for evaluating the second law efficiency of 160 Wp stand-alone SPV systems installed in RKGIT Ghaziabad premises. The performance of a SPV system depends on climate conditions like temperature, air velocity and a number of sunny days. The solar energy striking the solar panels gets converted into electric and thermal energy. In this work, we have considered the effect of ambient temperature and air velocity on the efficiency of solar panels. The average second law efficiency of SPV systems was found to be 10.7%, whereas maximum second law efficiency was 13.8% at 9am on the same day. The efficiency of the SPV system can be improved by maintaining the temperature of the module. [ABSTRACT FROM AUTHOR]

In India, uniform price was assigned to renewable energy certificate (REC) irrespective of renewable energy (RE) type, technology, and location. Moreover REC price bands are higher than existing preferential tariff. There are distinct renewable purchase obligations (RPOs) specified for various RE types, whereas there is lack of efficient tools to check RPO compliance. Because of these reasons, REC market stabilisation is getting delayed. This paper proposes a method using plant performance multiplier to convert non-solar and solar REC to single equivalent REC with competitive REC pricing, which can be traded on unified REC market. The method combines solar and non-solar RPOs into a single composite RPO, to make RPO compliance and its checking simple and efficient. A sample illustration of the proposed method is given. The benefits offered by the proposed method in REC pricing, REC trading and RPO compliance are discussed. A comparative economic analysis of present and proposed method is reported. [ABSTRACT FROM PUBLISHER]

Solar energy is the primary resource for all biological, chemical and physical processes. The amount of global solar radiation is an important parameter for solar energy applications. It is common to estimate a monthly average of daily global solar radiation using different regression models. These models in turn exploit the correlation between solar radiation and various atmospheric factors. These factors are commonly derived from meteorological, geographical and climatological data that are readily available for majority of weather stations across the world. In this paper, a novel regression model that can predict location-independent daily global solar radiation is presented. The proposed exponential quadratic model captures the correlation between measured global solar radiation values, sunshine hour and Air Pollution Index for Indian cities. In addition to this, an extended study of several other regression models (e.g. linear, quadratic, exp.-linear and exp.-quadratic) is also presented. This analysis with real data from Indian cities suggests that air pollution is a more significant factor than location when predicting solar radiation. Finally, the model parameters (regression coefficients) for each model are listed out. Additionally, the generalised model equation for the best performing model is also presented. [ABSTRACT FROM PUBLISHER]