Renewable Energy Sources (RES) Utilization and Adaptation Technologies using Artificial Intelligence Expert Systems to Support and Secure RES Projects, Investments and Initiatives (original) (raw)
Related papers
Assessing renewables-to-electricity systems: a fuzzy expert system model
Energy Policy, 2006
The assessment of Renewables-to-Electricity Systems is a complex, time-consuming task and requires skilled, experienced engineers. This paper describes the on-going research effort that takes place in the development of a new Intelligent Approach, an efficient decision making tool in this problem based on the employment of the Expert Systems and Fuzzy Logic techniques. As far as expert knowledge representation is concerned, the proposed approach is based on Expert System techniques (rule-based methodology). Moreover, trying to assess a Renewables-to-Electricity project or several alternative ones, the analysis has to face, in general, a series of uncertainties. To handle effectively these uncertainties, a new methodology is proposed (by use of Fuzzy Sets Theory and Fuzzy Logic Techniques). The proposed Fuzzy Project Priority Index for each Renewables-to-Electricity System is very useful especially in decision-makers.
The Impact of Artificial Intelligence on Renewable Energy Systems
NeuroQuantology, 2022
Efficient use of energy in the context of technology, particularly renewable energy in the public sector, is essential, as buildings are the largest energy users, particularly government facilities, such as educational, health, and government facilities, as well as other public institutions with a high frequency of usage. However, recent advancements in artificial intelligence within the context of Big Data have not been fully leveraged in this sector. Renewable Energy Systems are critical components of the Smart City. Integrating renewable energy sources is beneficial for resolving the supply of energy and demand concerns. Their correct scale is required to adapt to integrating renewable energy sources in the future and maintain a steady condition of energy consumption. Different algorithms are required to execute the consolidated renewable energy system to meet technological, economic, and size issues. These sections discuss an in-depth examination of various issues regarding power production for Smart Cities using Renewable Energy Systems. Particular difficulties related to the integration of various energy sources, the usage of smart grids for integration, and techniques for scaling renewable energy utilizing software and artificial intelligence algorithms.
Fuzzy Based Expert System for Renewable Energy Management
The aim of this work is determine the most appropriated period for connecting a particular generation source fuelled by biogas on a distribution network. The main electrical characteristics of the network are evaluated. The proposed simulations provided data for analyzing the quantitative parametersvoltage levels, power losses and load current. A group of decision makers was selected for establishing scores applied to the qualitative parameter evaluationavailability of ancillary services supportaccording to each period in analysis. The fuzzy-based expert system is then applied for selecting and ranking the most appropriated period for connecting the distributed generation source. The definition of the ranking is the outcome according to the final prioritiesquantitative and qualitative analysis. .
The promotion of renewable energy sources (RES) and ecologically clean technologies to reduce greenhouse gas emissions is a key policy of the European Commission. In isolated regions with great and unexploited RES potential, RES technologies can exploit local resources for electricity supply and substantial energy savings. The use of decision support systems (DSS) aims the multidimensional decision-making process regarding the choice of RES for energy supply in isolated regions. The network integration issues for the distributed energy resources (RES in our case) are challenging, since, in particular, the design of hybrid systems is strongly influenced by two components: one is the amount of energy that is expected from the renewable resources and the other is the ability of the power system to maintain a balance of power between generation and consumption. This paper reviews the DSS for the choice of RES in isolated regions and proposes some future developments.
Successful large-scale renewables integration in portugal: Technology and intelligent tools
CSEE Journal of Power and Energy Systems, 2017
Portugal is seen worldwide as a case of success in the large-scale integration of renewables in its power system, especially for wind power. Consistent policies and sound management decisions are fundamental, but a sustainable process is not possible without the development of endogenous knowledge. This paper summarizes a set of models, both applied by the industry and representing actual technologic advancement, denoting the context of research and innovation in the country that helps to explain such success. Novelties arise in reliability assessment for systems with renewables, active and reactive power control, integration of wind farms, storage, electric vehicle integration, wind and solar power forecasting and distribution operation and state estimation taking advantage of smart grid structures. In all cases, one relevant trait is evident: the pervasive use of computational intelligence tools.
Proceedings of the 8th conference on Applied …, 2008
Renewable Energy production is becoming more important day by day due to a rapid increase for reliable, sufficient, timely, and economic and environmentally energy production. Public awareness about environment has a great impact on choosing the renewable resources for the renewable based electricity production systems. The Commission on Environment of the Turkish Grand National Assembly approved the Kyoto Protocol on Global Warming in June 2008, which makes the importance of renewable energy one step more important for Turkey. When all the potential renewable energy sources of Turkey is considered, hydraulic and wind and solar energies can meet almost 1/3 of the total demand and a very high percentage of the electricity production in the country. However country-wide planning of production and distribution is vital just because the potential of renewable resources diversed among the geographical regions and according to the time of the year in Turkey. The current structure of Turkey's energy policies, latest developments, and renewable energy potentials has analyzed. For planning and distribution scenarios five different regions of Turkey is used for sample data in means of wind, hydro and solar renewable energy potentials. A road map and a fuzzy expert system for a possible planning and distribution road map has been proposed.
International Journal For Multidisciplinary Research, 2024
This integrative literature review (ILR) delves deeply into the role of artificial intelligence (AI) in enhancing grid stability and managing renewable energy sources in France. The central issue in this study is the difficulty in integrating intermittent renewable sources such as wind and solar electricity, which impacts the energy grid's stability and efficiency. The review looks into how artificial intelligence might improve the prediction and optimization of energy output from these volatile sources, enhancing supply- and demand management. It demonstrates AI's potential to improve grid stability, minimize waste, and promote sustainable energy practices. The study also cites essential barriers such as data protection, infrastructural sufficiency, and the substantial investments required to modernize existing systems for AI integration. Based on a thorough examination of existing research, the review underlines the need for solid legislative frameworks to support ethical AI deployment in line with France's environmental and energy goals. This research paper is critical for policymakers because it provides insights into the strategic application of AI to promote a more efficient and resilient energy industry. The study's findings and recommendations urge further AI research and practical applications to guide France and other nations to a more sustainable and stable energy future.
2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2021
This paper’s main objective is to examine the state of the art of artificial intelligence (AI) techniques and tools in power management, maintenance, and control of renewable energy systems (RES) and specifically to the solar power systems. The findings would allow researchers to innovate the current state of technologies and possibly use the standard and successful techniques in building AI-powered renewable energy systems, specifically for solar energy. Various peer-reviewed journal articles were examined to determine the condition and advancement of the AI techniques in the field of RES, specifically in solar power systems. Different theoretical and experimental AI techniques often used and reliable techniques determined were the Artificial Neural Network (ANN), Backpropagation Neural Network (BPNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Genetic Algorithm (GA). These techniques are widely used in different types of solar predictions based on the findings of this review. However, ANN stood out as the best of these techniques. ANN’s specific advantages over its competition include short computing time, higher accuracy, and generalization capabilities over other modeling techniques. This would translate to cost efficiency over other modeling techniques.
Renewable Energy Problems: Exploring the Methods to Support the Decision-Making Process
Sustainability, 2020
In the current scenario of increasing energy demand and encouraging sustainable development in countries, the energy sector’s planning has become more complex, involving multiple factors, such as technical, economic, environmental, social, and political. The decision process plays a vital role in structuring and evaluating complex decision situations related to the sector, considering various criteria and objectives, encouraging adopting policies to promote energy efficiency actions by increasing research on renewable energy sources and strategic energy decisions. The high number of multi-criteria decision support methods (MCDM) available and their efficiency in solving highly complex problems results in an impasse with their selection and application in specific decision situations. Thus, the scientific community requires methodological approaches that help the decision-maker select the method consistent with his problem. Accordingly, this paper conducts a Systematic Literature Rev...