Flexibility Driven Operation For Low Carbon Power And Energy Systems

"The integration of higher shares of renewable generation is essential for decarbonizing electricity generation. However, the main challenge of integrating renewable energy sources into a power system is the management of the increased disturbances in power balancing. These disturbances are caused by the inherent variability and uncertainty of renewable energy sources, which can put significant stress on reserve requirements in the system. Traditional power system operation paradigms are becoming less capable of handling this challenge, and this has spurred interest in studying the concept of power system flexibility. Flexibility-based operational planning algorithms typically rely on robust optimization to offer guarantees on the ability of the operator to meet a wide array of possible scenarios. The main downside of these approaches is their conservative results whose operating costs and/or carbon footprint may be sub-economical. Such results come by because these approaches immunize their solutions for the required level of security against realizations of potential events within their uncertainty set. Moreover, these approaches also often ignore the inherent time and spatial couplings of wind and solar generation variability. To tackle this issue, this thesis proposes a modeling technique for uncertainty sets which is called the spatio-temporal flexibility requirement envelope. It reduces the over-conservatism of the robust solution by comprehensively capturing and representing the temporal trends and spatial correlation of multisite renewable generation and load demand. A mathematical program is also developed for applying this envelope to power system unit commitment and dynamic dispatch through projections of the spatio-temporal envelopes, where we mainly focus on microgrid type power systems. We illustrate the effectiveness of the spatio-temporal flexibility requirement envelopes through several case studies. Furthermore, flexibility-based operational planning approaches are usually formulated based on model predictive control paradigms, which requires the online solution of a mixed-integer optimization problem at each sampling time. Such approaches are not amenable to most remote microgrid and practical field microgrid implementations, where controls are typically implemented by industrial controllers with limited computational power and the dispatch algorithm faces stringent execution time for real time operation. To tackle this challenge, in this thesis we also develop rigorous machine learning approaches for simplifying and accelerating the flexibility-based microgrid dispatch algorithms, so that they can be implemented in practical settings for real time operation. The proposed machine learning approaches are able to preserve as much as possible the control performance obtained by full mixed-integer optimization. At the same time, they can provide feasible dispatch decisions. We conduct comprehensive performance evaluations to demonstrate the effectiveness of the proposed machine learning approaches"--

The global energy system is undergoing a profound transformation from a system based mainly on fossil fuels to a low-carbon one based on variable renewable energy (VRE), such as wind power and solar power, to achieve the 2050 Paris Agreement. By 2050, solar and wind power, with more than 14,500 GW installed capacity, would account for three-fifths of global electricity generation. This transformation comes with significant challenges since high VRE shares will greatly increase system flexibility requirements for balancing supply and demand. Accordingly, all sectors of the power system need to unlock further requisite flexibility through technology, business, and policy innovations, including power supply, transmission, distribution, storage, and demand.

Due to the inherent volatility and randomness, the increasing share of energy from renewable resources presents a challenge to the operation of multi-energy systems with heterogeneous energy carriers such as electricity, heat, hydrogen, etc. These factors will make the systems hard to adjust their supply and demand flexibly to maintain energy balance to ensure reliability. Further, this hinders the development of a low-carbon and economically viable energy system. By making full use of the synergistic interaction of generation, transmission, load demand, and energy storage, a three-fold approach focused on quantifying demand flexibility, evaluating supply capabilities, and enhancing resilience can unlock the flexibility potential across various sectors of new energy systems. This approach provides an effective means of facilitating the transition from conventional energy systems to low-carbon, clean-energy-oriented paradigms. However, huge challenges arising from renewable energy pose great obstacles to the aforementioned solution pathway. The main objectives of this Research Topic are： 1. Develop advanced carbon emission accounting and measurement techniques for emerging multi-energy systems 2. Design effective methods for predicting renewable electricity generation 3. Proposed efficient methods for quantitative assessment of uncertainty from renewables and loads 4. Put forward advanced evaluation, optimization, and planning strategies incorporating diverse flexibility resources 5. Design multifaceted market mechanisms and collaborative frameworks balancing economics and low carbon footprint 6. Develop operational control and resilience-enhancement techniques for distribution networks under large-scale distributed energy integration

With the development of renewable electricity and the expected important surpluses of production, how can the use of hydrogen improve the green energy portfolio? Power-to-Gas covers the production of hydrogen through electrolysis and its storage or conversion in another form (gas, chemicals or fuels). It emphasises the need for new technologies with global energy consumption, markets, and logistics concepts. Pilot projects around the world are discussed as well as how policy and economics influence the real use of these energy harvesting and conversion technologies.

Increased production of energy from renewable sources leads to a need for both new and enhanced capacities for energy transmission and intermediate storage. The book first compares different available storage options and then introduces the power-to-gas concept in a comprehensive overview of the technology. The state of the art, advancements, and future requirements for both water electrolysis and methanation are described. The integration of renewable hydrogen and methane into the gas grid is discussed in terms of the necessary technological measures to be taken. Because the power-to-gas system is very flexible, providing numerous specific applications for different targets within the energy sector, possible business models are presented on the basis of various process chains taking into account different plant scales and operating scenarios. The influence of the scale and the type of the integration of the technology into the existing energy network is highlighted with an emphasis on economic consequences. Finally, legal aspects of the operation and integration of the power-to-gas system are discussed.

This Working Group III contribution to the IPCC Sixth Assessment Report provides a comprehensive and transparent assessment of the literature on climate change mitigation. The report assesses progress in climate change mitigation options for reducing emissions and enhancing sinks. With greenhouse gas emissions at the highest levels in human history, this report provides options to achieve net zero, as pledged by many countries. The report highlights for the first time the social and demand-side aspects of climate mitigation, and assesses the literature on human behaviour, lifestyle, and culture, and its implications for mitigation action. It brings a wide range of disciplines, notably from the social sciences, within the scope of the assessment. IPCC reports are a trusted source for decision makers, policymakers, and stakeholders at all levels (international, regional, national, local) and in all branches (government, businesses, NGOs). Available as Open Access on Cambridge Core.

Advances in Clean Energy Technologies presents the latest advanced approaches toward a cleaner and more sustainable energy environment. Editor Kalam Azad and his team of expert contributors focus on recent developments in the field of clean energy technologies, sustainable zero emission resources, energy efficiency and environmental sustainability, as well as clean energy policy and markets. This well-rounded reference includes an authoritative view on control and storage solutions specific to medium and large-scale industries, advanced approaches to modeling, and experimental investigations on clean energy technologies. Those working in and researching clean energy and sustainability will obtain detailed understanding of a variety of zero emission energy production and conversion approaches, as well as important socio-economic and environmental considerations that can be applied to their own unique power generation settings. Presents an exclusive analysis on advanced approaches of modeling and experimental investigations of clean energy technologies, including solar, wind, ocean, and hybrid systems Includes an authoritative and cross-disciplinary view on energy policy and energy markets Helps readers develop an understanding of concepts and solutions to global issues surrounding sustainability in medium-large scale energy industries Offers detailed understanding of a variety of zero emission energy production and conversion approaches

The surge in renewable and distributed energy sources has posed significant challenges for smart power distribution network (SPDN). These challenges fall into two main categories: the unpredictability of renewable energy sources and the complexities introduced by numerous electrical devices and their interdependencies, affecting forecasting and operational performance. As the emphasis on SPDN's economic and environmental aspects grows, this book focuses on the vital themes of sustainability and cost-efficiency in SPDN forecasting, planning, and operation. It is structured into three key parts: 1. SPDN Situation Awareness: This section assesses prior research methods, analyzes their shortcomings while dissecting SPDN's unique situation awareness characteristics. Then, some forecast and virtual collection methods are presented. 2. Boosting SPDN Planning: Addressing optimal planning challenges in SPDN, this part introduces advanced modelling and algorithm solving techniques, tailored to mitigate SPDN's inherent uncertainty. 3. Enhancing SPDN Operation: Considering a variety of equipment types and controllable loads, this section explores strategies to boost SPDN operational performance. It covers control methodologies for electric vehicles, flexible loads, energy storage, and related equipments, etc. Tailored for university researchers, engineers, and graduate students in electrical engineering and computer science, this book is a valuable resource for comprehending SPDN's situation awareness, planning, and operation intricacies in the context of sustainability and economic efficiency.

Wind power and solar photovoltaics (PV) are crucial to meeting future energy needs while decarbonizing the power sector. Deployment of both technologies has expanded rapidly in recent years, one of the few bright spots in an otherwise bleak picture of clean energy progress. However, the inherent variability of wind power and solar PV raises unique and pressing questions. Can power systems remain reliable and cost-effective while supporting high shares of variable renewable energy (VRE)? And if so, how? Based on a thorough review of the integration challenge, this publication gauges the economic significance of VRE integration impacts, highlights the need for a system-wide approach to integrating high shares of VRE and recommends how to achieve a cost-effective transformation of the power system. This book summarizes the results of the third phase of the Grid Integration of VRE (GIVAR) project, undertaken by the IEA over the past two years. It is rooted in a set o