The use of the words "partner" and "partnership" herein is intended to indicate a mutually beneficial collegial relationship, rather than a partnership as defined under state law.

Abstract-Wholesale power markets operating over transmission grids subject to congestion have distinctive features that complicate the detection of market power and operational inefficiency. This study uses a wholesale power market test bed with strategically learning traders to experimentally test the extent to which market performance measures commonly used for other industries are informative for the dynamic operation of restructured wholesale power markets. Examined measures include the Herfindahl-Hirschman Index (HHI), the Lerner Index, the Residual Supply Index, the Relative Market Advantage Index, and the Operational Efficiency Index. It is also shown that the objective function commonly used to manage these markets deviates systematically from the standard economic measure of market efficiency when grid congestion is present.

Flexibility from residential loads presents an enormous potential to provide various services to the smart grid. In this paper, we propose a unified hierarchical framework for aggregation and coordination of various residential loads in a smart community, such as Thermostatically Controlled Loads (TCLs), Distributed Energy Storages (DESs), residential Pool Pumps (PPs), and Electric Vehicles (EVs). A central idea of this framework is a virtual battery model, which provides a simple and intuitive tool to aggregate the flexibility of distributed residential loads. Moreover, a multi-stage Nash-bargainingbased coordination strategy is proposed to coordinate different aggregations of flexible loads for demand response. Case studies are provided to demonstrate the efficacy of our proposed framework and coordination strategy in managing peak power demand in a smart residential community.

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