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Analytics and optimization for renewable energy integration
The scope of this book covers the modeling and forecast of renewable energy and operation and planning of power system with renewable energy integration. The first part presents mathematical theories of stochastic mathematics; the second presents modelling and analytic techniques for renewable energy generation; the third provides solutions on how to handle the uncertainty of renewable energy in power system operation. It includes advanced stochastic unit commitment models to acquire the optimal generation schedule under uncertainty, efficient algorithms to calculate the probabilistic power, and an efficient operation strategy for renewable power plants participating in electricity markets.
Book
Renewable Energy Integration - Practical Management of Variability, Uncertainty, and Flexibility in Power Grids
This book is a ground-breaking new resource - the first to offer a distilled examination of the intricacies of integrating renewables into the power grid and electricity markets. It offers informed perspectives from internationally renowned experts on the challenges to be met and solutions based on demonstrated best practices developed by operators around the world. The book's focus on practical implementation of strategies provides real-world context for theoretical underpinnings and the development of supporting policy frameworks. The book considers a myriad of wind, solar, wave and tidal integration issues, thus ensuring that grid operators with low or high penetration of renewable generation can leverage the victories achieved by their peers.
eBook
Principal Mismatch Patterns Across a Simplified Highly Renewable European Electricity Network
Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system’s required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system’s backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network.
Journal Article
Hosting capacity in distribution grids: A review of definitions, performance indices, determination methodologies, and enhancement techniques
For the past few years, the world has seen a great shift toward renewable energy resources from conventional ones. But the ever‐increasing integration of distributed generation (DG) to the electrical network leads to integration limiting constraints like overvoltage, under voltage, harmonics, equipment ampacity violations, and failure of protection schemes. Therefore, an extensive investigation of the methodologies in which DGs can be incorporated into the electrical network is presented in this manuscript. This article provides an extensive review of all the hosting capacity (HC) terms, references, limiting constraints of the studied networks, geographical segregation, and their determination methodologies. Moreover, the factors defining the HCs of various networks and the architectures employed to increase them, are also explained briefly in the conducted review study. An extensive investigation of the methodologies in which distributed generations (DGs) can be incorporated into the electrical network without having any adverse effect on the system is required which leads to the hosting capacity (HC) studies. In this regard, this article provides an extensive review of all the HC terms, references, limiting constraints of the studied networks, geographical segregation, and their determination methodologies. Moreover, the factors defining the HCs of various networks and the architectures employed to increase them, are briefly explained. Lastly, existing gaps in the literature and future visible recommendations are defined with respect to the HC aspects of DGs.
Journal Article
Transmission expansion for renewable energy scale-up
Scaling up renewable energy, such as wind and solar, goes hand-in-hand with the expansion of transmission infrastructure. The richest solar and wind renewable energy sites are often located far away from consumption centers or existing transmission networks. Unlike fossil fuel-based power sources, renewable energy sources are greatly site-constrained and, for this reason, transmission networks need to be expanded to reach the renewable energy sites. Delivering transmission is a challenge, given the dispersion and granularity of renewable sources. Tapping a few hundred megawatts of renewable energy sources, such as wind and solar power, will likely require delivering transmission to several sites. Furthermore, transmission is also required to smooth out the variability of new renewable sources in a large geographical area. For these reasons, countries' renewable energy scale-up efforts are being challenged by the need for timely and efficient delivery of transmission networks. The objective of this report is to present emerging lessons and recommendations on approaches to efficiently and effectively expand transmission networks for renewable energy scale-up. The report focuses on the planning and regulatory aspects of transmission expansion that are relevant to transmission utilities and electricity regulators.
eBook
The Energy Internet
With the potential to transform the infrastructure of the electric grid, the book challenges existing power systems, presenting innovative and pioneering theories and technologies that will challenge existing norms on generation and consumption. Researchers, academics, engineers, consultants and policymakers will gain a thorough understanding of the Energy Internet that includes a thorough dissemination of case studies from the USA, China, Japan, Germany and the U.K. The book's editors provide analysis of various enabling technologies and technical solutions, such as control theory, communication, and the social and economic aspects that are central to obtaining a clear appreciation of the potential of this complex infrastructure.
eBook
Enhancing stability in renewable energy transmission using multi-terminal HVDC systems with grid-forming controls for offshore and onshore wind integration
This paper presents a thorough analysis of two-terminal VSC-HVDC links, and the effects of isolated faults have been extensively studied in multi-terminal HVDC (MTHVDC) networks systems that would enable the interconnection of substantial offshore wind farm energy resources to onshore power systems with emphasis on dynamic transmission performance during different fault and perturbation scenarios. The performance of the system was evaluated against three important scenarios: transient faults, sudden load drops, and wind speed changes. The work presented a comparative analysis of Grid-Following (GFL) and Grid-Forming (GFM) control strategies with a focus on their provisions in offering compliance with grid code requirements, particularly, in faults ride-through (FRT) performance. Transient stability and grid compliance has been performed through the study to take results as the GFM controller performance has been better as compared to GFL controller in the study. The GFM controller recovered more rapidly than its GFL counterpart, achieving voltage stability within 0.5 s and frequency stability within 0.6 s when subjected to fault and load disturbances, versus 1.2 s and 1.8 s for the GFL controller’s voltage and frequency, respectively. The difference in voltage and frequency deviation between the GFL and the GFM system was less than ± 4% and less than ± 0.3 Hz respectively, further verifying that the GFM system far outperformed the GFL system, which demonstrated a voltage stability of ±18% and a frequency stability of ± 0.9 Hz under load disturbance. The results demonstrated the GFM controller’s capability to stabilize power systems rapidly and fulfill grid code requirements even in the presence of compounded disturbances. The virtual inertia and dynamic dampness provided by GFM controller make the system resilient against fluctuations in both wind generation and grid faults. The results highlight the value of GFM-based MTHVDC systems as a dependable option for integrating offshore wind energy into the grid, creating a system with superior stability and efficiency in future large-scale renewable energy systems.
Journal Article
Advanced AI approaches for the modeling and optimization of microgrid energy systems
The present study examines AI techniques to reduce the cost and CO
2
emissions for designing and controlling microgrid at minimum cost and providing a power supply to a residential complex of 100 units. Three AI techniques, Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO), are employed to optimize the optimal composition of energy sources based on solar energy and wind energy, battery storage, and load profiles. GA, from natural selection, is constantly seeking the best configuration. ABC models honeybee foraging behavior to achieve efficient exploration, and ACO models ant colony decision-making to achieve optimal energy configuration. These AI models maximize the use of renewable energy, reduce wastage, and improve microgrid resilience and responsiveness to supply and demand fluctuations. Experiments demonstrate the revolutionary potential of AI to control microgrids. The optimization achieves the lowest electricity cost of 0.037 USD/kWh, a reduction by 67% from Fez’s reference cost (0.115 USD/kWh) and guarantees a supply of power. These results illustrate the ability of AI to power cheap and clean energy systems.
Journal Article
Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges
This paper reviews renewable energy integration with the electrical power grid through the use of advanced solutions at the device and system level, using smart operation with better utilisation of design margins and power flow optimisation with machine learning. This paper first highlights the significance of credible temperature measurements for devices with advanced power flow management, particularly the use of advanced fibre optic sensing technology. The potential to expand renewable energy generation capacity, particularly of existing wind farms, by exploiting thermal design margins is then explored. Dynamic and adaptive optimal power flow models are subsequently reviewed for optimisation of resource utilisation and minimisation of operational risks. This paper suggests that system-level automation of these processes could improve power capacity exploitation and network stability economically and environmentally. Further research is needed to achieve these goals.
Journal Article
Multi-agent reinforcement learning for fast-timescale demand response of residential loads
To integrate high amounts of renewable energy resources, electrical power grids must be able to cope with high amplitude, fast timescale variations in power generation. Frequency regulation through demand response has the potential to coordinate temporally flexible loads, such as air conditioners, to counteract these variations. Existing approaches for discrete control with dynamic constraints struggle to provide satisfactory performance for fast timescale action selection with hundreds of agents. We propose a decentralized agent trained with multi-agent proximal policy optimization with localized communication. We explore two communication frameworks: hand-engineered, or learned through targeted multi-agent communication. The resulting policies perform well and robustly for frequency regulation, and scale seamlessly to arbitrary numbers of houses for constant processing times.
Journal Article