Intelligent Control in Smart Energy Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".
Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 680
Special Issue Editors
Interests: electrical machines and drives; photovoltaic systems; applications of superconductors for electric power systems
Interests: soft computing; feature selection; fuzzy modeling; optimization; fuzzy optimization; metaheuristics; computational intelligence; knowledge discovery
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Special Issue Information
Dear Colleagues,
While there is no single standard that could be applied to support a claim that an energy system is “smart”, smart energy systems (SES) have been used to characterize broader approaches than the term “smart grid”. Smart grids focus mainly on the electricity sector. By contrast, smart energy systems focus on the inclusion of more sectors (electricity, heating, cooling, industry, buildings, and transportation), which allows for the identification of more achievable and affordable solutions to the transformation into future renewable and sustainable energy solutions. The term smart energy systems was first mentioned in 2009.
Intelligent control considers non-traditional modeling and control approaches to nonlinear systems. The main methods of intelligent control can include expert control, fuzzy control, neural network control, hierarchical intelligent control, anthropomorphic intelligent control, integrated intelligent control, combined intelligent control, chaos control, and wavelet theory, among other approaches. The IEEE first Symposium on Intelligent Control was held in 1985, where the principles and structure of an intelligent control system were discussed. Since then, intelligent control has matured gradually.
Intelligent control, together with smart energy systems, became today a relatively new but complementary marriage. Intelligence means learning, adaptation, and memory, and the current and future conditions in energy systems indicate the need to develop integrative approaches that will benefit from this symbiosis with intelligent control.
The world is abuzz with applications of machine learning in almost every field—commerce, transportation, banking, energy, and, more recently, healthcare. These breakthroughs are due to rediscovered algorithms, powerful computers to run them, and, most importantly, the availability of bigger and better data to train the algorithms.
In this Special Issue, entitled “Intelligent Control for Smart Energy Systems”, we want to look at a few of the latest applications using intelligent control applied to the areas in energy systems that will most benefit from this holistic approach, such as but not limited to:
1) Energy management systems capable of learning how to schedule the energy allocation at minimum cost on the base of the electricity market prices;
2) Integration of intelligent control strategies for microgrid systems to be capable of integrating and managing multiple distributed energy resources.
3) Intelligently integrated behavior and actions of all the actors (generators, consumers and prosumers, maintenance team) connected to the electric energy system to supply safe, economical, and sustainable electricity;
4) Combining two emerging technologies, smart buildings and microgrid systems, to include the improvements of indoor comfort and electric energy efficiency. Both should be obtained by developing an effective building energy management system to minimize power consumption without compromising the occupants’ comfort.
We invite the research community to submit original research papers in these topics:
- Intelligent control and optimization for reduction of electric energy consumption in buildings;
- Intelligent control based on soft-computing techniques in SES;
- Intelligent control and automation in SES;
- Technologies and applications of intelligent control in SES for manufacturing processes;
- Intelligent control strategies to improve SES performance (energy efficiency and resilience);
- Modeling, simulation, optimization for intelligent control of heating, cooling, lighting, ventilation, water usage, and other resource flows in built environments.
Dr. Paulo J. C. Branco
Dr. Susana Vieira
Guest Editors
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