We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

Preface, Notations 1.Introduction to Time-Delay Systems I.Frequency-Domain Approach 2.Systems with Commensurate Delays 3.Systems withIncommensurate Delays 4.Robust Stability Analysis II.Time Domain Approach 5.Systems with Single Delay 6.Robust Stability Analysis 7.Systems with Multiple and Distributed Delays III.Input-Output Approach 8.Input-output stability A.Matrix Facts B.LMI and Quadratic Integral Inequalities Bibliography Index

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Stability of Time-Delay Systems

Time-delay systems: an overview of some recent advances and open problems

The purpose of this article is to provide a tutorial overview of information consensus in multivehicle cooperative control. Theoretical results regarding consensus-seeking under both time invariant and dynamically changing communication topologies are summarized. Several specific applications of consensus algorithms to multivehicle coordination are described

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Information consensus in multivehicle cooperative control

Microgrids are now emerging from lab benches and pilot demonstration sites into commercial markets, driven by technological improvements, falling costs, a proven track record, and growing recognition of their benefits. They are being used to improve reliability and resilience of electrical grids, to manage the addition of distributed clean energy resources like wind and solar photovoltaic (PV) generation to reduce fossil fuel emissions, and to provide electricity in areas not served by centralized electrical infrastructure. This review article (1) explains what a microgrid is, and (2) provides a multi-disciplinary portrait of today's microgrid drivers, real-world applications, challenges, and future prospects.

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Microgrids: A review of technologies, key drivers, and outstanding issues

This paper expands on a method proposed in [1] for stabilizing oscillatory system with positive, delayed feedback. The closed-loop system obtained is shown (using the Nyquist criterion) to be stable for a range of delays.

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Delayed Positive Feedback Can Stabilize Oscillatory Systems

Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energy management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.

Energy Management and Optimization Methods for Grid Energy Storage Systems

A miniature mobile robot provides a relatively inexpensive mobile robot. A mobile robot for searching an area provides a way for multiple mobile robots in cooperating teams. A robotic system with a team of mobile robots communicating information among each other provides a way to locate a source in cooperation. A mobile robot with a sensor, a communication system, and a processor, provides a way to execute a strategy for searching an area.

Cooperating mobile robots

The valuation of an electricity storage device is based on the expected future cash ow generated by the device. Two potential sources of income for an electricity storage system are energy arbitrage and participation in the frequency regulation market. Energy arbitrage refers to purchasing (stor- ing) energy when electricity prices are low, and selling (discharging) energy when electricity prices are high. Frequency regulation is an ancillary service geared towards maintaining system frequency, and is typically procured by the independent system operator in some type of market. This paper outlines the calculations required to estimate the maximum potential revenue from participating in these two activities. First, a mathematical model is presented for the state of charge as a function of the storage device parameters and the quantities of electricity purchased/sold as well as the quantities oered into the regulation market. Using this mathematical model, we present a linear programming optimization approach to calculating the maximum potential revenue from an elec- tricity storage device. The calculation of the maximum potential revenue is critical in developing an upper bound on the value of storage, as a benchmark for evaluating potential trading strate- gies, and a tool for capital nance risk assessment. Then, we use historical California Independent System Operator (CAISO) data from 2010-2011 to evaluate the maximum potential revenue from the Tehachapi wind energy storage project, an American Recovery and Reinvestment Act of 2009 (ARRA) energy storage demonstration project. We investigate the maximum potential revenue from two dierent scenarios: arbitrage only and arbitrage combined with the regulation market. Our analysis shows that participation in the regulation market produces four times the revenue compared to arbitrage in the CAISO market using 2010 and 2011 data. Then we evaluate several trading strategies to illustrate how they compare to the maximum potential revenue benchmark. We conclude with a sensitivity analysis with respect to key parameters.

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Estimating the Maximum Potential Revenue for Grid Connected Electricity Storage: Arbitrage and Regulation

A test system for testing a controller provides a way to use large numbers of miniature mobile robots to test a cooperative search controller in a test area, where each mobile robot has a sensor, a communication device, a processor, and a memory. A method of using a test system provides a way for testing a cooperative search controller using multiple robots sharing information and communicating over a communication network.

Raymond H. Byrne

Papers

Delayed Positive Feedback Can Stabilize Oscillatory Systems

Energy Management and Optimization Methods for Grid Energy Storage Systems

Cooperating mobile robots

Estimating the Maximum Potential Revenue for Grid Connected Electricity Storage: Arbitrage and Regulation

Cooperative system and method using mobile robots for testing a cooperative search controller