Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy

Foreword
Preface
Acknowledgment
Contents
About the Editors
General Approaches to Assessing Electrical Load of Agro-industrial Complex Facilities When Justifying the Parameters of the Photovoltaic Power System
1 Introduction
2 Materials and Methods
3 Results and Discussion
3.1 Construction of Annual and Daily Charts of Electric Loads by the Calculation Method
3.2 Construction of Annual and Daily Schedules of Electrical Loads According to the Guidelines
3.3 Construction of Annual and Daily Schedules of Electrical Loads by Monitoring the Actual Consumed Electricity
3.4 Analysis of Operation Modes of Photovoltaic Modules Considering Load Graph of the Consumer
4 Conclusions
References
RBFNN for MPPT Controller in Wind Energy Harvesting System
1 Introduction
2 Wind Energy Harvesting System
2.1 Model of Wind Turbine
2.2 Modeling of the PMSG
3 Proposed Control Strategies
3.1 Radial Basis Function (RBF)
4 Simulation Results and Discussion
5 Conclusion
References
Simulation Optimum Performance All-Wheels Plug-In Hybrid Electric Vehicle
1 Introduction
2 Plug-In Hybrid Electric Vehicle Components
3 Plug-In Hybrid Electric Control Methodology
3.1 EV Mode
3.2 Series Mode
3.3 Parallel Mode
3.4 Recuperation Brake Energy Mode
3.5 Motor Start/Stop Automatic (MSA) Mode
3.6 Freewheeling Mode
3.7 Mechanical Braking Mode
4 AWD-PHEV Plant Model
5 Application
5.1 Simulation Results
6 Conclusions
References
Artificial Intelligence Application to Flexibility Provision in Energy Management System: A Survey
1 Introduction
2 Conventional Approach to Flexibility Management
2.1 Demand-Side (Load) Management
2.2 Energy Storage Systems (ESSs)
2.3 Electric Vehicles: V2G and G2V Technologies
2.4 Grid Reinforcement
3 Review of Artificial Intelligence and Its Application to Flexibility Management in Energy System
4 Planning Integrated Flexibility Management with Artificial Intelligence
5 Conclusions
References
Machine Learning Applications for Renewable Energy Systems
1 Introduction
2 Related Work
3 Key Applications
3.1 Forecasting
3.1.1 Weather Forecasting
3.1.2 Wind and Solar Power Production Forecasting
3.1.3 Load Forecasting
3.2 Integrating AI with Smart Grids
3.2.1 Applications of AI in Smart Grids
3.3 Condition Monitoring and Fault Prognostics of Renewable Energy Systems
3.3.1 Hydropower Projects
3.3.2 Wind Power Projects
3.3.3 Solar Power Projects
4 Resources (ML Algorithms and Datasets)
4.1 AI/ML Algorithms
4.1.1 Fuzzy Logic
4.1.2 Hidden Markov Models (HMMs)
4.1.3 Conventional ML Algorithms
4.1.4 Artificial Neural Networks (ANNs)
4.2 Datasets
4.2.1 Forecasting Energy Supply, Demand, and Weather
4.2.2 Smart Grids
4.2.3 Condition Monitoring and Prognostics Maintenance
5 Challenges and Open Research Issues
6 Conclusions
References
New Technologies and Equipment for Smelting Technical Silicon
1 Introduction
2 Materials, Equipment, and Methods
2.1 Materials
2.2 Methods
2.3 Experimental Equipment
3 Results and Discussion
4 Conclusion
References
Reconfiguration of Distribution Network Considering Photovoltaic System Placement Based on Metaheuristic Algorithms
1 Introduction
2 Model of the RDN-PVSP Problem
2.1 Power Generation of PVS
2.2 The Main Objective of the RDN-PVSP
2.3 The Constraints of the RDN-PVSP Problem
3 Optimal Solution Searching Method for the RDN-PVSP Problem
3.1 Application of GJO for the RDN-PVSP Problem
3.2 The RDN-PVSP Method Based on PSO
4 Simulation Results and Discussion
4.1 The 33-Buses DN
4.2 The 69-Buses DN
5 Conclusion
References
Technology of Secondary Cast Polycrystalline Silicon and Its Application in the Production of Solar Cells
1 Introduction
2 Smelting, Composition, and Electrophysical Properties of SCPS
3 Models for Calculating the Efficiency of Solar Cells in the Conditions of Mass Production
4 Discussion of Results and Conclusions
References
Machine Learning Applications for Renewable-Based Energy Systems
Abbreviations
1 Introduction: Importance of Forecasting in Renewable-Based Energy Systems
2 Novel Forecasting Methods for Renewable Energy Generation
3 Modern Approaches for Electric Energy Consumption Forecasting
4 Predictive Outage Estimation for Renewable-Based Power Systems
5 Conclusions
References
Bi-objective Optimal Scheduling of Smart Homes Appliances Using Artificial Intelligence
1 Introduction
1.1 Contribution of Research Work
2 Mathematical Modeling
2.1 Objective Function for Minimization of Electricity Cost
2.2 Objective Function for Peak Demand Management
2.3 Proposed Objective Function for Cost of Electricity
2.4 Operational Constraints [18–23]
3 Solution Methods
3.1 Cuckoo Search (CS) Method
3.2 Particle Swarm Optimization
3.3 Hybrid GA-PSO Algorithm
4 System Data
4.1 Pricing Data for Case Study I (Tehran Power Distribution Company, Iran)
4.2 Pricing Data for Case Study II (Kerala State Electricity Board, India)
5 Optimal Results of Simulation Study
5.1 Scenario 1: Minimization of Cost of Monthly Electricity Bill
5.2 Scenario 2: Minimization of Peak Demand and Electricity Cost Simultaneously
6 Conclusion
References
Optimal Placement of Photovoltaic Systems and Wind Turbines in Distribution Systems by Using Northern Goshawk Optimization Algorithm
1 Introduction
2 Problem Formula
2.1 The Main Goal and Its Mathematical Expression
2.2 Renewable Energy Sources
2.2.1 The Electricity Generation of Photovoltaic Power Generators (PVGs)
2.2.2 The Electricity Generation of Wind-Based Generators
2.3 The Operational Constraints
3 The Northern Goshawk Optimization
3.1 The Main Inspiration
3.2 The Candidate Solution-Searching Process of NGO
3.2.1 The Update Mechanism
3.2.2 The Terminated Condition
4 Numerical of Results
4.1 The Determination of the Best Method for Solving the Considered Problem
4.2 The Investigation on Quantity of PVGs and WGs to Power Loss Value
5 Conclusion
Appendix
References
Granulated Silicon and Thermal Energy Converters on Its Basis
1 Introduction
2 The Physical Mechanism of the Observed Effects
3 Application of Granular Silicon in New Types of Thermal Energy Converters
4 Ways to Improve the Energy Characteristics of Heat Energy Converters Based on Granular Silicon
5 Conclusions
References
Security-Constrained Unit Commitment with Wind Energy Resource Using Universal Generating Function
Abbreviations
1 Introduction
2 Mathematical Formulation of the Unit Commitment Problem
2.1 Constraints
2.1.1 Generation Limit
2.1.2 Power Balance
2.1.3 Minimum Uptime
2.1.4 Minimum Downtime
2.2 Transition Cost
2.2.1 Startup Cost
2.2.2 Shutdown Cost
2.3 Wind Curtailment
2.4 Objective Function
3 Wind Modelling
3.1 Universal Generating Function
4 Methodology
4.1 Genetic Algorithm
4.2 Particle Swarm Optimisation
5 Results
6 Conclusion
Appendix
References
Index