Unit Commitment And Investment Valuation Of Flexible Biogas Plants In German Power Markets

Biogas plants become more flexible, scheduling their power generation with respect to market prices. For this purpose the electrical capacity of power units is extended to convert the continuously produced gas as well as the gas held in storage. This work has shown how gas plants with extended capacity located at a gas production site can be analyzed on the basis of unit commitment. Mixed integer linear programs (MILP) have been developed for the unit commitment of such plants in different use cases. The models developed consider gas plants at a gas production site participating in German power markets, switching between static and variable gas supply, providing secondary and tertiary control reserve, and claiming the German market and flexibility premium. The models can be applied to plan daily schedules for the operation of these gas plants. Furthermore, the models can be applied to analyze the benefits of extending the electrical or storage capacity of gas plants located at a gas production site. The models calculate the optimized gross income that can be applied as cash flow for determining the net present value (NPV) of investments in extended electrical and storage capacity.

Provides an overview of the different pathways to produce Synthetic Natural Gas Covers technological, and economic aspects of this Synthetic Natural Gas Details the most popular technologies and state-of-the-art of SNG technologies while also covering recent and future research trends Covers the main process steps during conversion of coal and dry biomass to SNG: gasification, gas cleaning, methanation and gas upgrading Describes a number of novel processes for the production of SNG with their specific combination of process steps as well as the boundary conditions Covers important technical aspects of Power-to-Gas processes

This book presents the state of art of the several advanced approaches to beneficiation of coal. The influence of recent technology attains the advantages of processing coal, purification studies, rheological behavior, and the mineral beneficiation. The experts collected in this volume have contributed significantly to the enrichment in the in depth knowledge not only in context of working knowledge, but also future prospects of clean coal technology.

Biomass is a vital source of renewable energy, because it offers a wide range of established and potential methods for energy generation. It is also an important facet of the progression toward a sustainable energy future. The need for further development in the provision of bioenergy is underlined by challenges affecting the biomass resource base, including rising demand for biomass for food, feed, materials and fuel. This is underlined by significant concerns over factors relating to land, such as soil, nutrients and biodiversity. This book examines and analyzes Germany's decade-long initiative toward implementation of an active policy for the transition of the energy system to make greater use of renewable energy sources, which has resulted in a significant increase in the amount of biomass used for electricity, heat and transport fuel. The book begins with a review of market and resource base issues and moves on to analyze the technical options for a more integrated bioenergy use. The analysis spans the entire bioenergy provision chain including solid, liquid and gaseous biofuels. A case study offers a detailed model of the effects of smart biomass energy on the German energy system. The book closes with a view of the most promising fields and an appraisal of needed elements for a successful transition.

From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.

This book provides an in-depth economic analysis of the challenges associated with bioenergy use and production. Drawing on New Institutional Economics and the theory of economic policy, it develops theory-based recommendations for a bioenergy policy that strives for efficiency and sustainability. Further, it shows how to deal with diverse uncertainties and constraints, such as institutional path dependencies, transaction costs, multiple and conflicting policy aims, and interacting market failures, while also applying the resulting theoretical insights to a case study analysis of Germany’s bioenergy policy. As such, the book aims to bridge the gap between practical bioenergy policymaking on the one hand, and neoclassical theory-based concepts that strictly focus on a minimization of greenhouse gas mitigation costs on the other.