• Energy Research

Integrating renewable energy sources (RES) into power systems presents significant challenges due to their diverse nature and operational characteristics. This study addresses these challenges through an innovative strategy that simulates solar and wind farms, storage systems, fuel cell generators of hydrogen energy (via electrolysis), and hydrogen storage, all governed by an intelligent controller. Alongside a mathematical model defining the system's dynamics, a multi‐objective optimization model is employed, exploring the system's operational, financial, and environmental impacts. While the mathematical model has limitations, the advanced model captures the system's dynamic behavior with exceptional precision. This intelligent simulation simplifies the complex interrelationships between various resources in the system, highlighting the viability of RES integration for enhanced benefits. Multi‐objective optimization of a real case study of Iowa 240‐Bus power system in the Midwest United States has resulted in an annual savings of $126 147.8, along with a significant CO2 reduction of 951 035.6 kg compared with the basecase. The total annual energy costs, including capital costs and electricity sales, are reported to be $157 430.4, and the total annual CO2 emissions are −4453.8 kg. Financial indicators highlight an annual cost reduction of 10.3% and an annual emission reduction of 100.5%. The simple and detailed project break‐even years are 18 and 1, respectively, with the project savings to cost minimization scenario ratio at 1.04. The optimization process efficiently handled a complex problem involving 5921 iterations, 299 247 variables, 11 854 discrete variables, and 342 167 equations, completing the entire operation in 12.7 s. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

AbstractThe purpose of this study is to provide a hybrid group decision-making approach to evaluate fintech-based financial alternatives for green energy investment projects. First, the multidimensional factors of due diligence for fintech-based financing alternatives of green energy investment projects are identified. In this regard, the balanced scorecard perspectives are considered. Next, consensus-based group decision-making analysis is performed. Second, impact-relation directions for fintech-based financing alternatives of green energy investment projects are defined. For this purpose, the spherical fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is applied. The novelty of this study is its proposal of a new outlook to due diligence of fintech-project financing for renewable energy investments by using the group and integrated decision-making approaches with spherical fuzzy DEMATEL. The findings indicate that customer expectations are the most essential factor for the revenue sharing and rewarding models. Additionally, this study identified that organizational competency plays the most important role with respect to the peer-to-business debt model. In contrast, the conclusion was reached that financial returns have the greatest importance for the equity sharing model.

The energy storage process becomes very important due to the imbalances in energy supply and demand. Therefore some factors need to be considered to increase the efficiency of the energy storage system, such as cost–benefit analysis and technological improvements. This study aims to examine the inventive problem-solving capacities for renewable energy storage investments. A new model is suggested for this objective by considering fuzzy decision-making methodology. It is concluded that prior action and dynamicity are the most essential capacities of renewable energy storage investments. Additionally, dynamicity plays the most critical role when all factors are considered in renewable energy investment projects in a collaborative manner. Hence, it is recommended that the companies should mainly consider the initial developments of the storage facilities. Moreover, location selection for effective energy storage should also be considered to increase the performance of these investments.

This study aims to find out the significant stages of new product development process for the industrial decarbonization of sustainable economies by using interval type-2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL). The findings demonstrate that commercialization is the most significant process of new product generation process of industrial decarbonization. Moreover, it is also concluded that with respect to the sub-criteria, cost analysis, and performance evaluation have the highest weights. An effective cost analysis is required in the new product development process. The costs of the product development process can in some cases be much higher than anticipated. This situation eliminates the effectiveness of the newly developed product. In this context, companies need to make the necessary plans for the costs of these new products correctly. On the other hand, it is important to follow the costs in detail during the process. Otherwise, the product that does not provide a cost advantage will not be preferred by industrial companies. This will cause the actions to be taken to reduce carbon emissions to fail.

Carbon emissions are a prominent issue for sustainable energy production and management. Energy policies under the growing competitive environment could change the priorities of emission reduction and investment decisions. This paper aims to forecast carbon emissions from China and to rank the importance of carbon emissions with interval type 2 (IT2) fuzzy sets (FS) for sustainable energy investments. For this purpose, the quadratic model is applied to measuring emission trends and the Qualitative Flexible Multiple Criteria Method (QUALIFLEX) is used for measuring sustainable energy investment alternatives by the several emission levels. Forecasted values of 29 provinces in China are converted into the linguistic and fuzzy numbers based on IT2 FS respectively to measure the priorities of emission reduction for sustainable economies. The novelty of this paper is to propose a hybrid decision-making approach based on quadratic modeling and the QUALIFLEX method and to discuss the overall energy emission trend and policies for sustainable economic growth. The results demonstrate that emission reduction policies are the most important phenomenon and the environmental factors should be widely considered to construct sustainable energy investments and production.