This research work analyzes the relationship between environmental degradation, economic growth, trade openness, primary energy consumption, coal consumption, and hydroelectricity consumption in Turkey from 1971 to 2015 using the autoregressive distributed lag (ARDL) time series approach through the hypothesis of the environmental Kuznets curve (EKC). Carbon dioxide (CO₂) emissions and ecological footprint are both used as indicators of environmental degradation, which employs six different models. According to the results found in this study, while trade openness increases CO₂ emissions, it decreases ecological footprint in the long-run. Coal consumption raises both CO₂ emissions and ecological footprint. While hydroelectric energy reduces CO₂ emissions, it has no effect on the environment. The results demonstrate that the EKC hypothesis is correct for both CO₂ emissions and Turkey’s ecological footprint. The threshold points are investigated as $18,704, $16,361, and $13,571 in models, where CO₂ emissions are the dependent variable. In models where the ecological footprint is the dependent variable, the investigated threshold points of $11,824, $11,821, and $15,476 are higher than the gross domestic product (GDP) per capita during the analysis periods. Furthermore, the findings highlight the importance of renewable energy use in reducing environmental degradation and coal use in increasing environmental degradation. These findings can shed light on the importance of transition to renewable energy sources (i.e., hydroelectricity consumption), from fossil fuels (i.e., coal consumption), related to future planning in energy diversification for Turkey.

Forecasting the electricity price and load has been a critical area of concern for researchers over the last two decades. There has been a significant economic impact on producers and consumers. Various techniques and methods of forecasting have been developed. The motivation of this paper is to present a comprehensive review on electricity market price and load forecasting, while observing the scientific approaches and techniques based on wind energy. As a methodology, this review follows the historical and structural development of electricity markets, price, and load forecasting methods, and recent trends in wind energy generation, transmission, and consumption. As wind power prediction depends on wind speed, precipitation, temperature, etc., this may have some inauspicious effects on the market operations. The improvements of the forecasting methods in this market are necessary and attract market participants as well as decision makers. To this end, this research shows the main variables of developing electricity markets through wind energy. Findings are discussed and compared with each other via quantitative and qualitative analysis. The results reveal that the complexity of forecasting electricity markets’ price and load depends on the increasing number of employed variables as input for better accuracy, and the trend in methodologies varies between the economic and engineering approach. Findings are specifically gathered and summarized based on researches in the conclusions.