This article is the second of the author’s works devoted to a comprehensive study of the economic efficiency of Russian renewable energy (RE) projects. The main goal of this paper is to study the level of influence of political risk on the economic efficiency of RE projects that are implemented in the Russian energy market using a state support program. Fifty-two solar, wind and small hydropower projects, which have received support in the form of a capacity-based support scheme in 2018-2020, were selected as objects of research. The methodological basis of the work was the classical methods of investment analysis and specific industry approach. They were supplemented with the author’s tool for calculating the monetary equivalent of political risk that takes into account the probability of the termination of support from the state. The practice-based assessment utilized the developed scenarios depending on changes in foreign and domestic international credit ratings of the country. The study of the impact of political risk for three stages of RE projects was carried out. Based on the results of the analysis, conclusions were drawn about generally insignificant influence of political risk on the economic efficiency of Russian RE projects. Recommendations for the development of state support programs in the event of the impact of political risks only were generated. The obtained research results are of practical and methodological value. It will be used in studying the impact of other specific risks on the effectiveness of Russian RE projects, as well as in developing recommendations enabling the Russian RE market to give up state support.

The activity of the world community in the field of climate and environmental conservation is increasing every year. The Paris Agreement, signed in 2015 by the majority of governments, and the additional goals set on COP26 in 2021 set the objectives of maximum reduction of greenhouse gas emissions into the atmosphere and the transition to renewable energy sources (RES). Consequently, the energy sector, as the largest sector of the world economy and the largest environmental polluter, is undergoing the greatest change. The development and implementation of an effective policy in the field of RES, which is part of the energy development strategy, is one of the factors of renewable energy market’s rapid development and stimulating the transition to clean energy. However, despite the measures taken by the world community to reduce the environmental impact of the energy sector and the development of renewable energy, the volume of greenhouse gas emissions continues to show an upward trend: from 2000 to 2021, the volume of CO₂ emissions produced by the power sector increased by 74.7%. This trend might be associated with a low level of elaboration of the current renewable energy policy, with barriers to the development of the renewable energy market or with the specifics of the energy sector. The purpose of this study is to review and analyze renewable energy policies in the European Union, Russia, and the United States in order to identify specific approaches to the development of renewable energy, key tools, and barriers. The current state of the energy sectors of the considered countries was analyzed, their features were identified, and a review as well as a comparative analysis of their renewable energy policies were conducted.

An accurate technique of driving cycle development is important. Such a technique should be dominantly based on real-world driving behavior to ensure it represents the profile of the selected route. A driving cycle often is the combination of analyses of huge numbers of micro-trips under different conditions of traffic. This research is an initiative to improve the accuracy of the method of data collection; this contributes directly to one of the major procedures of driving cycle development, namely data collection. A driving cycle tracking device (DC-TRAD) is a device developed to improve the data collection strategy with integration of Internet-of-Things to manage the huge amount of data collected. A conceptual design of DC-TRAD is developed, and the flexibility of the device is made use in this research to compare and analyze the driving cycle of Kinta district.

The rapidly increasing energy demand and the inevitable negative effects on the environment caused by fossil-fuelled energy production have made renewable energy technologies increasingly important and preferred among the widely used energy sources during the last decades. Wind energy is one of the leading renewable energy technologies. Wind energy is a carbon-free, environmentally friendly and competitive technology. A step forward in production of wind energy is offshore and onshore wind turbines, with their numerous advantages. Today, the increasing energy needs make onshore and offshore wind turbine applications an increasingly widespread renewable energy source. However, with this change, challenges arise during the operation phases as being associated with the strength of the wind turbines. Potential failures must be known in advance so that they can be dealt with strongly and effectively in the design phase. Damages and failures have a negative effect on the continuation of the operation and cause material and economic impacts. In this paper, the findings from a collection of failure data are presented. The database is available on request. The novelty of this paper is to assess and analyse the damages to wind turbines onshore and offshore in order to reduce the risk of potential failures, damages and collapse of wind turbines. According to the results of these studies and analyses, the database of failures experienced is considered to represent the general failure rate in the industry. This paper brings solutions and suggestions for future studies by pointing out risks and the failure situations that wind turbines are exposed to. It can help innovative solutions with the presentation of a detailed view of risk and failure situations.

Due to the speeding up of climate change, there is an urgent need to switch from using fossil fuels to producing energy using renewable energy sources. This change has to happen as soon as feasibly possible. Thus, in this article, to forecast wind speed and wind energy output in Turkey, the Light Gradient Boosting Machine (LightGBM) approach was applied, the hyperparameters of the LightGBM were tuned to the grid search method, and finally some evaluation criteria such as root mean square error and R² were calculated to show the performances of the LightGBM. Fortunately, an R² value of 0.98 for forecasting wind speed was found after 25 s. Additionally, the assessment criterion R² =1 for predicting the production power of the wind turbine was attained after 90 s.

Growing concern about global climate change has led to considerable interest in investigating renewable energy sources such as the biological conversion of biomass to methane in an anaerobic environment. Through a series of complicated biochemical interactions, it uses various bacterial species to degrade biodegradable material in the feedstock. Due to the complex and interacting biochemical processes, anaerobic digestion has nonlinear dynamics. Anaerobic digestion is highly at risk of instabilities and uncertainties because of its dynamic and nonlinear behavior, uncertain feedstock quality, and sensitivity to the process’s environmental conditions. Therefore, effectively operating a biogas production unit necessitates a thorough understanding of the system’s uncertainties. The present study aims to identify and assess the sources and methods of coping with the uncertainties in anaerobic digestion processes through a narrative review. Moreover, the knowledge gap is also investigated to reveal the challenges and opportunities to have a robust model. The results indicate that the unpredictability of model parameters and input variables were the most significant source of uncertainty, and the Monte Carlo technique, confident interval, and interval observers, as well as sensitivity analysis were the most frequently used tools to cope with these uncertainties.