This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.
Author(s): Rabindra Nath Shaw, Nishad Mendis, Saad Mekhilef, Ankush Ghosh
Series: Studies in Infrastructure and Control
Publisher: Springer
Year: 2021
Language: English
Pages: 121
City: Singapore
Preface
Contents
Editors and Contributors
1 A Day-Ahead Power Output Forecasting of Three PV Systems Using Regression, Machine Learning and Deep Learning Techniques
1 Introduction
2 Description of Site and Data Preprocessing
3 Methodology
3.1 Gaussian Process Regression
3.2 Support Vector Regression (SVR)
3.3 Principal Component Analysis (PCA)
3.4 Deep Learning Technique (RNN-LSTM)
3.5 Performance Parameters to Measure Forecasting Accuracy
4 Results and Discussion
5 Conclusion
References
2 Internet of Things and Internet of Drones in the Renewable Energy Infrastructure Towards Energy Optimization
1 Introduction
2 Latest Emerging Innovative Trends in Renewable Energy
2.1 Optimizing Offshore Wind in the U.S.
2.2 More Number of Electric Vehicles Running on Roads
2.3 Utilities and Corporations Investing in Solar Energy at Record Levels
2.4 Energy Efficiency Encouragement from Governments
2.5 Energy Storage Becoming a Significant Part of the Power Grid
3 IoT Applications Areas in Renewable Energy
3.1 Automation to Improve Overall Production
3.2 Smart Grids for Elevated Renewable Implementation
3.3 IoT Increasing the Adoption of Renewable Systems
3.4 Contribution from End Consumers
3.5 Balancing Supply and Demand
3.6 Cost-Effectiveness
4 Significant Role of Big Data Analytics in the Renewable Energy Sector
4.1 Data Forecasting
4.2 Efficient Resource Management
4.3 Intelligent Storage of Resources
4.4 Improving Safety and Reliability
4.5 Predicting Transformer Breakdowns and Prevention
5 Maharashtra Using Drones in EHV Power Transmission Lines and Towers
6 Long-Distance Drones Used for Surveillance to Avoid Network Failures
7 Conclusions
References
3 Reinforcement Learning Algorithm to Reduce Energy Consumption in Electric Vehicles
1 Introduction
1.1 Overview
2 Literature Review
3 Design and Analysis of Q-Learning-Based Algorithm
4 Result
5 Conclusions
References
4 Simulation and Performance Analysis of Standalone Photovoltaic System with Boost Converter Under Irradiation and Temperature
1 Introduction
2 Circuit Model of PV Module
3 Circuit Model of DC-DC Boost Converter
3.1 Choice of Inductor
3.2 Choice of Capacitor
4 Simulation Results
4.1 Simulation of PV Module
4.2 Simulation of MPPT DC-DC Boost Converter
5 Conclusions
References
5 Analysis of Variation in Locational Marginal Pricing Under Influence of Stochastic Wind Generation
1 Introduction
2 Problem Formulation
2.1 Problem Description
2.2 Methodology
3 Test Case, Data, and Assumptions
3.1 Test Case
3.2 Data Analysis
3.3 Assumptions
4 LMP Algorithm
4.1 Mathematical Calculation
5 Results
6 Discussion
7 Conclusion and Future Scope
7.1 Conclusion
7.2 Future Scope
References
6 Optimal Integration of Plug-in Electric Vehicles Within a Distribution Network Using Genetic Algorithm
1 Introduction
2 Problem Overview
2.1 Modeling PVE’s Driving Pattern
2.2 Distance Travelled Per Trip and Daily Mileage
3 Subsequent Trip Distance (STD)
3.1 PEVs Arrival and Departure Times
3.2 Initial SOC and Desired Departure Time SOC of PEVs
3.3 PEVs Energy Requirement
4 Problem Formulation
4.1 Charging Strategy A
4.2 Charging Strategy B
4.3 Smart Charging Strategy Constraints
5 Implementation of Charging Strategies
6 Results and Discussion
7 Conclusions
References
7 Frequency Control of 5 kW Self-excited Induction Generator Using Gravitational Search Algorithm and Genetic Algorithm
1 Introduction
2 Machine Modelling
3 Problem Formulation
3.1 Objective Function
3.2 Flowchart of Algorithm Used
4 Results and Discussion
Appendix 1: Specification of Self-excited Induction Generator
Appendix 2: Coefficients of Ztotal
References
8 Cloud Based Real-Time Vibration and Temperature Monitoring System for Wind Turbine
1 Introduction
2 Analysis of Electromagnetic Vibration Effects
3 Prototype Description
4 Experimental Results
5 Conclusion
References
9 Smart Solar-Powered Smart Agricultural Monitoring System Using Internet of Things Devices
1 Introduction
2 Proposed System Design and Working Principle
3 Sensor Description
4 Software Used
5 Conclusions
References
