Today, with the success of projects like Brooklyn Microgrid, local neighborhoods and communities are eagerly looking towards the microgrid technology. The idea behind a microgrid is to minimize power transmission losses due to the co-location of producers and consumers of energy. In a microgrid, along with consumers, there are also prosumers – those who install solar panels, wind turbines, etc. and share produced green energy locally – improving the sustainability of electric power distribution.

bcdc energy, aleksandr zavodovski, university of helsinki, computer science, migrogrid, renewable energy, prosumer

Consumers Meet Prosumers

As microgrids are becoming a reality, they also perplex us with the new challenges. Particularly, we are interested in the economic aspects of the relationship between prosumers and consumers. Installation of solar panels inflicts substantial costs, and while some of the prosumers might distribute excesses of energy with neighbors for gratis, others may want their investments to payback and even gain some monetary profit. How should prosumers trade with consumers, what will be the ideal market mechanism to determine the price?

Returning to our Brooklyn Microgrid example, according to E. Mengelkamp et al. [1], the situation is two-fold. On the one hand, there is an implementation of the double auction: a market mechanism where both sellers and buyers can submit their bids, which are then matched by the auction mechanism. The mechanism subsequently determines the clearing price. On the other hand, due to limitations of the trial period, participants traded at a fixed price, so the performance of the solution is not proven by real-life usage. W. Tushar et al. [2] publish screenshots of a trading application developed by LO3 Energy, where parties can specify their preferences, such as maximum (minimum) price limits to buy (sell) energy, and choose their counterparties. However, no further information concerning the market performance is exposed since technology is proprietary.

Market and Virtue: Harmony or Contention?

There are other subtleties related to the analysis of microgrid participants’ behavior. To give an example, let’s look at the following situations.

In the case of insufficient energy production, microgrids obtain electricity from the utility grid. Respectively, when all the produced energy cannot be consumed or stored, excesses are sold to the utility grid at the spot price. One might consider the spot price of the utility grid to function as an upper bound for a microgrid trading. However, rationality is not always about paying less, and some people would prefer to pay a higher electricity bill for the sake of supporting the acquisition of solar panels by their neighbors.

Another problem is market manipulation. Consumers may try to play the price down by reporting understated valuations, and prosumers may try to do the opposite with the selling prices. There is a solution to the problem, namely, truthful auction, in which participants get the best payoff by reporting their privately known valuations to the auctioneer. However, everything comes at a price, and R. Preston McAfee has shown in his design of a double auction mechanism [3], that there is a need to exclude some trades to preserve the attractive property of truthfulness. Is a design of a complex market strategy for a microgrid just an overkill? Will it be a nostrum for the proliferation of microgrids? Hopefully, the BCDC project will be able to contribute to the discussion since cooperation with Caruna Networks Oy will give us a possibility to evaluate the state of the art theoretical models on the real microgrid data.

Writer:

Aleksandr Zavodovski
Doctoral Student
BCDC Cloud Team
University of Helsinki, Department of Computer Science

 

[1] Mengelkamp, Esther, et al. ”Designing microgrid energy markets: A case study: The Brooklyn Microgrid.” Applied Energy 210 (2018): 870-880.

[2] W. Tushar, et al. ”Transforming Energy Networks via Peer-to-Peer Energy Trading: The Potential of Game-Theoretic Approaches,” in IEEE Signal Processing Magazine, vol. 35, no. 4, pp. 90-111, July 2018.

[3] McAfee, R. Preston. ”A dominant strategy double auction.” Journal of Economic Theory 56.2 (1992): 434-450.

Photo: iStock

The University of Oulu’s BCDC Energiablogi

Aiheeseen liittyviä artikkeleita