Improving the Electricity Market with VCG
In “An Incentive-Compatible Energy Pricing Mechanism for Electricity-Gas Interconnected System Using Vickrey-Clarke-Groves Mechanism Design Theory,” Guo et al. discuss the potential of applying VCG to the electricity market as its current system (locational marginal pricing or LMP) of finding market-clearing prices does not incentivize truthful bidding as would be the case under VCG. The paper also mentions some of the other benefits of price-setting under VCG like making the process decentralized. This way, no one player would be too powerful, and – as we have seen in relationship and trading networks – one especially powerful node in a graph can make its partners end up with little to no surplus. Guo et al.’s explanation of VCG is similar to what we saw in class where it is based on the harm that removing one natural gas well causes to the rest of the system. While some of the more advanced calculations in the paper were a little over my head, I felt that a lot of us Networks students could follow along with most of what it was getting at in terms of market-clearing, social optimality, encouraging truthful bidding, and some of the general logic about calculating prices. On top of this, the paper also includes a nodal network of a natural gas system to illustrate some of the relationships as we had used when discussing things like FaceBook friends or how different pages link to each other on the Web.
In our class, we have seen the benefits of VCG over similar methods of finding market-clearing prices like GSP. For me, it was interesting to see such an established market not using this more efficient method of market-clearing. Guo et al. explain that the current LMP method of pricing has been in use for about 30 years but it still has its inefficiencies in dishonest behavior by market players. In class, we only really saw VCG in the context of selling slots for online advertisements but it can clearly be applied to many different types of matching markets. For me, I found it interesting that by combining some of the simpler components we ran into earlier in the year – market clearing algorithm, sealed second-price auctions – we were able to find a mechanism that allows us to optimally market-clear in very complex situations like this electricity and power market that is riddled with restraints. To me, this paper is an example of the real-world applications of some of the theoretical calculations we have been plugging through in this class and how the world can be a bit more optimized and run a bit more smoothly when there are people attempting to apply these network concepts.
Source: https://ieeexplore.ieee.org/document/9220680?arnumber=9220680