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This course provides an introduction of the use of Internet of Energy in Smart Cities. It introduces EU Companies and experts in the knowledge and management of smart grids. The introduction of best practices about energy management within the smart grid scenario allows EU companies and experts to improve their competitiveness by optimizing energy efficiency, costs and environmental impact and is providing information considering the Integration of electric mobility with the grid.
Moreover, its purpose is to introduce the big data terminology, features, characteristics and specific applications to energy sector and to describe the machine learning main features and their applications to the energy sector. Additionally, it provides an overview of the main algorithms and tools for energy forecasts and predictive management in the energy sector. Finally, another goal is to support companies in understanding the networking and communication requirements as well as the security vulnerabilities that may apply to these environments. |
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Basics of IT competences. Basics of electrical engineering and power networks. |
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Knowledge
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Skills
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Competences
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Big Data Analytics and Machine learning techniques
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Describe big data and machine learning characteristics, showing impact on organization's development
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Manage and control the technical implementation of big data and machine learning classification techniques in line with the organizational context
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Comprehensive, specialized, factual theoretical knowledge of the main forecasting models in the energy sector
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Apply methods and tools for forecasting and simulation in the energy sector
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Manage energy networks based on the outcomes of predictive algorithms and tools
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- Conceptual models of smart grid
- AC and DC Distributed Micro-grid architectures
- Smart and advanced metering infrastructures
- Role of agents and prosumers
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- Design of smart energy systems
- Management of micro-grid applications on the basis of hierarchical control schemes
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Competences in power architectures design and in the analysis of optimal energy management strategies related to energy production, storage and consumption in a smart city context
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Networking and communication protocols for IoE environments
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Advice IoE users on the proper networking and communication protocol to be implemented in Smart Grids environment
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Manage and supervise the technical implementation of the different networking and communication protocols
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IoE security basics, Security risks regarding the implementation of networking and communication protocols
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Identify and analyse approaches and instruments for performing analysis to identify the concrete risks related to networking and communication protocols
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Support the coordination of the risk analysis for IoE environments, according with the organization’s guidelines, provide advice for addressing the risks
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Module 1 - Introduction to IoE: Introduction to IoT and IoE, Background and Perspectives, IoE technology, IoE Business, IoE business analysis, IoE business strategy
Module 2 - Smart Grids: Electric Distributed Architectures, Smart grid concept, Microgrid architectures, DC microgrid laboratory case study, Remotable microgrid demonstrator
Module 3 - Integration of electric mobility with the grid: Power requirements of electric mobility, Main electric/hybrid vehicle configurations, Electric vehicle charging modes
Module 4 - IoE data analysis: Big data for IoE, Machine learning for IoE, Prediction and simulation models for IoE
Module 5 - Basics of networking and security: Introduction to Networking for IoE environments, Connectivity in Smart Grids, Introduction to IoE security, Smart grids/cities vulnerabilities |
Prof.
Sergio Martin
- Universidad Nacional de Educación a Distancia
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