Marginal Pricing of Transmission Services Using Min-Max Fairness Policy

We consider the problem of allocating the cost of a transmission system among load and generator entities. It is a known instance of the classical cooperative game theoretic problem. To solve this problem is a formidable task, as we are dealing with a combinatorial game with transferable utilities. This is an NP hard problem. Therefore, it suffers from the curse of dimensionality. Marginal pricing is a pragmatic alternative to solve this problem since both Kirchhoff current law and voltage law are strictly adhered to. However, the generic complexity of cooperative game theoretic problems cannot be just wished away. It now manifests as the difficulty in choosing an economic slack bus, which may even be dispersed. We propose the application of min-max fairness policy to solve this problem and give an algorithm which will run in polynomial time. During network cost allocation, min-max fairness policy minimizes the maximum regret among participating entities at each step. Maximum regret is measured in terms of price, and lexicographic application of this principle leads to a fair and unique equilibrium price vector. Results on a large network demonstrate fairness as well as tractability of the proposed approach.