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Over the past few years, the Midwest Independent Transmission System Operator, Inc. (MISO) has transformed the electric utility industry in 13 Midwestern US states through the development and implementation of energy and ancillary services markets. MISO uses mixed-integer programming to determine when each power plant should be on or off. Operations research methods set energy output levels and establish the prices at which energy trades. These new markets increased the efficiency of the existing electric infrastructure (power plants and transmission lines) in the Midwest, improved the reliability of the grid, and reduced the need for future infrastructure investments. These advances enabled the MISO region to realize between $2.1 billion and $3.0 billion in cumulative savings from 2007 through 2010. We expect additional savings of $6.1 billion to $8.1 billion through 2020.

Competitive bidding for ancillary services (A/S), in addition to bidding for energy, is increasingly recognized as an important part of electricity markets. In this paper, an LP-based approach is presented for solving the multi-product (i.e. energy and A/S products), multi-zone/area physical market dispatch problem. The approach can explicitly represent various constraints, such as reserve requirement constraints, network security limits, and sharing of constrained resource capacity (e.g. maximum unit generation) between energy and reserve. The joint dispatch method, which dispatches energy and reserve market concurrently, is extended to allow inter-zonal reserve trading in a multi-zone competitive pool. Numerical examples are included to demonstrate the salient characteristics of the joint dispatch solution.

This paper reports upon the mathematical models and implementation of the Scheduling, Pricing and Dispatch (SPD) application for the New Zealand Electricity Market (NZEM). SPD analyzes bids for energy offers, reserve offers and energy demands, and recognizes explicitly the effects on bid clearing due to transmission congestion, network losses, reserve requirements, and ramp rate limits. Advanced LP solution methods are utilized to solve the large-scale constrained optimization problem. Results on a 67-bus test system and the NZEM are included.

The purpose of this paper is to analyze various approaches to incorporate short-term stored energy resources into the Midwest ISO co-optimized energy and ancillary service market. Based on the analysis, the best approach is to utilize short-term stored energy resources for regulating reserve with the real-time energy dispatch to be set in such a way that the maximum regulating reserve can be cleared. Results on a five-bus system are used to illustrate the clearing and pricing on short-term stored energy resources with the proposed approach. Monte Carlo simulation on the five-bus system is used to illustrate the AGC regulation deployment.

This paper reports upon the security-constrained commitment and dispatch algorithms and their implementation for Midwest ISO's day-ahead co-optimized energy and ancillary service markets. The MIP method is utilized to solve the DA market and the RA commitment problems and the LP method solves the DA market clearing problem. Demand response resources are qualified for provision of energy and ancillary services. AS demand curves are introduced to allow for efficient pricing of energy and AS capacities by location. Efficient price signals are expected to induce new generation additions, demand response participations and thus improve grid reliability.