Energy Markets and Responsive Grids

This volume consists of selected essays by participants of the workshop Control at Large Scales: Energy Markets and Responsive Grids held at the Institute for Mathematics and its Applications, Minneapolis, Minnesota, U.S.A. from May 9-13, 2016. The workshop brought together a diverse group of experts to discuss current and future challenges in energy markets and controls, along with potential solutions. The volume includes chapters on significant challenges in the design of markets and incentives, integration of renewable energy and energy storage, risk management and resilience, and distributed and multi-scale optimization and control. Contributors include leading experts from academia and industry in power systems and markets as well as control science and engineering. This volume will be of use to experts and newcomers interested in all aspects of the challenges facing the creation of a more sustainable electricity infrastructure, in areas such as distributed and stochastic optimization and control, stability theory, economics, policy, and financial mathematics, as well as in all aspects of power system operation.

Introduction.- How to Manage the Complexity of the Grid.- Naïve Electicity Markets.- Capacity Markets: Rationale, Designs and Trade-offs.- Redesign of U.S. Electricity Capacity Markets.- A Swing-Contract Market Design for Flexible Service Provision in Electric Power Systems.- A Dynamic Framework for Electricity Markets.- Fast Market Clearing Algorithms.- Small Resource Integration Challenges for Large-Scale SCUC.- Multi-Grid Schemes for Multi-Scale Coordination of Energy Systems.- Graphical Models and Belief Propagation Hierarchy for Physics-Constrained Network Flows.- Profit Maximizing Storage Integration in AC Power Networks.- Virtual Inertia Placement in Electric Power Grids.- A Hierarchy of Models for Inverter-Based Microgrids.- Asynchronous Coordination of Distributed Energy Resources with Packetized Energy Management.- Ensemble Control of Cycling Energy Loads: Markov Decision Approach.- Distributed Control Design for Balancing the Grid Using Flexible Loads.- Disaggregating Load by Type from Distribution System Measurements in Real-Time.- Risk-Aware Demand Management of Aggregators Participating in Energy Programs with Utilities.- Towards Resilience-Aware Resource Allocation and Dispatch in Electricity Distribution Networks.- A Cautionary Tale: On the Effectiveness of Inertia-Emulating Load as a Cyber-Physical Attack Path.