Optimal auction for the deregulated electricity market using augmented Lagrangian and surrogate optimization

Deregulated electricity markets use a market clearing price (MCP) auction mechanism to pay market participants for energy and ancillary service products. Currently most independent system operators (ISO's) determine MCP's by using a traditional unit commitment approach that minimizes the offered costs. This is not appropriate because the costs minimized are not the purchase costs to be paid by customers. How to correctly set the MCP's is an open and challenging issue, and no solution has yet been reported in the literature. This paper presents an effective method to solve the new pay-at-MCP problem. In view of the specific features of the new problem including the nonseparability of the objective function and the discontinuity of offer curves, the standard Lagrangian relaxation technique cannot be applied. Our key idea is to use the augmented Lagrangian relaxation approach, but to form and solve MCP and offer subproblems by using an advanced surrogate optimization framework. Potential pitfalls and intricacies of our method are intuitively illustrated. Numerical testing results demonstrate that the method is effective, and the resulting costs are significantly lower than what are obtained by using the unit commitment approach.