Summary There is a constant growth in energy consumption and consequently energy generation around the world. During the recent decades, renewable energy sources took heed of scientists and policy makers as a remedy for substituting traditional sources. Wind and photovoltaic (PV) are the least reliable sources because of their dependence on wind speed and irradiance and therefore their intermittent nature. Energy storage systems are usually coupled with these sources to increase the reliability of the hybrid system. Environmental effects are one of the biggest concerns associated with the renewable energy sources. This study summarizes the last and most important environmental and economic analysis of a grid‐connected hybrid network consisting of wind turbine, PV panels, and energy storage systems. Focusing on environmental aspects, this paper reviews land efficiency, shaded analysis of wind turbines and PV panels, greenhouse gas emission, wastes of wind turbine and PV panels' components, fossil fuel consumption, wildlife, sensitive ecosystems, health benefits, and so on. A cost analysis of the energy generated by a hybrid system has been discussed. Furthermore, this study reviews the latest technologies for materials that have been used for solar PV manufacturing. This paper can help to make a right decision considering all aspects of installing a hybrid system. Copyright © 2017 John Wiley & Sons, Ltd.

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Summary Recent technological developments in renewable energy systems and significant growth of solar and wind energy have made these 2 renewable sources potential viable alternatives for conventional energy sources. However, due to intermittent nature, their reliability and availability are not similar to traditional sources. Hence, it is crucial to estimate the solar and wind availability and contribution more accurately. There are various factors affecting the generation capacity of renewable sources. There has been a vast research on the impact of factors related to climate condition such as wind speed, air temperature, and humidity on renewable energy generation. However, there are several other factors with indirect impact on renewable capacity and generation mostly overshadowed by the climate factors. In this study, a multi‐predictor regression model is developed and presented for solar and wind energy generation capacity across the USA. Our study of 50 states shows how the generation capacity can be affected by several indexes including human development index. Variables with the more significant impacts have been chosen using a regression analysis. A recommendation on the best transformation of the response variables and sensitivity analysis of the results has also been presented. The results provide a model to estimate the generation capacity using significant predictors. For instance, the impact of population growth on the wind turbine generation can be explored using these models.