Robust optimization policy benchmarks and modeling errors in natural gas

We demonstrate in this paper that when modeling errors are present, the policy benchmarks proposed earlier can backfire and are hence, as suspected, not well suited for regulation. We begin our analysis with a more general model than the one that has been used earlier by accommodating the LDC's ability to reduce cost by exerting effort, as in classical economics. We derive solutions to the LDCÕs problem, find closed form solutions for the regulator's optimal fee fraction along with risk sharing implications, and provide insights into the policy benchmark selection. We then construct a robust-optimization based policy benchmarking mechanism that inherits all the original benefits. We further demonstrate that these, unlike the earlier benchmarks, are robust against modeling errors.