Distributed Linear Programming Models In A Smart Grid
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Distributed Linear Programming Models in a Smart Grid
This book showcases the strengths of Linear Programming models for Cyber Physical Systems (CPS), such as the Smart Grids. Cyber-Physical Systems (CPS) consist of computational components interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. A fundamental challenge in the design and analysis of CPS is the lack of understanding in formulating constraints for complex networks. We address this challenge by employing collection of Linear programming solvers that models the constraints of sub-systems and micro grids in a distributed fashion. The book can be treated as a useful resource to adaptively schedule resource transfers between nodes in a smart power grid. In addition, the feasibility conditions and constraints outlined in the book will enable in reaching optimal values that can help maintain the stability of both the computer network and the physical systems. It details the collection of optimization methods that are reliable for electric-utilities to use for resource scheduling, and optimizing their existing systems or sub-systems. The authors answer to key questions on ways to optimally allocate resources during outages, and contingency cases (e.g., line failures, and/or circuit breaker failures), how to design de-centralized methods for carrying out tasks using decomposition models; and how to quantify un-certainty and make decisions in the event of grid failures.
Integration of Distributed Resources in Smart Grids for Demand Response and Transactive Energy
The proliferation of renewable energy enhances the sustainability of power systems, but the inherent variability also poses great challenges to the planning and operation of large power grids. The corresponding electric power deficiencies can be compensated by fast ramping generators and energy storage devices. However, frequent ramp up/down power adjustments can increase the operation and the maintenance cost of generators. Moreover, storage devices are regarded as costly alternatives. Demand response (DR) and transactive energy can address this problem owing to its attractive and versatile capability for balancing the supply-demand, improving energy efficiency, and enhancing system resilience. Distributed resources are the typical participants of DR and transactive energy programs, which greatly contribute to keep the supply and demand in a balance. Thermostatically controlled loads (TCLs) (i.e., air conditioners, water heaters, and refrigerators) represent an example of distributed resources, the ratio of which to the total power consumption in developed countries is up to 30%–40%. Providing tremendous potentials in adjustable power consumption, TCLs have attracted major interests in DR and transactive energy opportunities. It has highlighted the advantages of TCLs in responding to uncertainties in power systems. This book provides an insight of TCLs as typical distributed resources in smart grids for demand response and transactive energy to address the imbalance between supply and demand problems in power systems. The key points on analysis of uncertainty parameters, aggregated control models, battery modelling, multi-time scale control, transactive control and robust restoration of TCLs are all included. These are the research points of smart grids and deserve much attention. We believe this book will offer the related researcher a better understanding on the integration of distributed resources into smart grid for demand response and transactive energy. And it will be helpful to address the problems in practical projects.
Energy Systems Modeling and Policy Analysis
Energy Systems Modeling and Policy Analysis covers a wide spectrum of topics including policy analysis and the optimal operational planning of integrated energy systems using a systems approach. This book details the importance of energy modeling and policy analysis, system dynamics and linear programming, modeling of energy supplies, energy demand, and environmental impact. Integrated energy systems at micro- and macro-levels, the application of simulation techniques for integrated rural energy systems, and integrated electric power systems/smart grids are covered as well. Features: Covers topics such as modeling, optimization and control of energy systems, and data analysis collected using a Supervisory Control and Data Acquisition (SCADA) system Uses system dynamics methodology (based on control systems theory) as well as other modeling tools Focuses on energy and environmental issues Provides optimal operational planning and management of integrated electric power systems and smart grids Covers the simulated planning and management of integrated national electric power systems using system dynamics This book is aimed at graduate students in electrical engineering, energy technology, microgrids, energy policy, and control systems.