In this talk I will be presenting a complete framework devised for the operation of agent cooperatives offering large-scale electricity demand shifting services. In our framework, individuals, represented by rational agents, form cooperatives to offer demand shifting from peak to non-peak intervals, incentivized by the provision of a better electricity price for the consumption of the shifted peak load, similar to economy of scale schemes.
We equip the cooperatives with a novel, directly applicable, and effective consumption shifting scheme, that allows for the proactive balancing of electricity supply and demand. Our scheme employs several algorithms to promote the formation of the most effective shifting coalitions. It takes into account the shifting costs of the individuals, and rewards them according to their shifting efficiency. In addition, it employs internal pricing methods that guarantee individual rationality, and allow agents with initially forbidding costs to also contribute to the shifting effort. The truthfulness of agent statements is ascertained via the incorporation of a strictly proper scoring rule, CRPS. Moreover, by employing stochastic filtering techniques for effective individual performance monitoring, the scheme is able to better anticipate and tackle the uncertainty surrounding the actual agent shifting actions. We provide a thorough evaluation of our approach on a simulations setting constructed over a real-world dataset. Our results clearly demonstrate the benefits arising from the use of agent cooperatives in this domain - specifically, enhanced consumption reduction performance, and increased financial gains for the cooperative.
Moreover, given time, I will briefly present an extension of our framework that addresses the problem of decentralised coordinated consumption shifting for electricity prosumers, via the adoption of a cryptocurrency mechanism. I will show that individual optimization with respect to electricity prices does not always lead to minimized costs, thus necessitating a cooperative approach. We thus propose the employment of an internal cryptocurrency mechanism can thus be employed for coordinating members decisions, and distributing the collectively generated profits. The mechanism generates cryptocoins in a distributed fashion, and awards them to participants according to various criteria, such as contribution impact and accuracy between stated and final shifting actions. In particular, when a CRPS-based distribution method is employed, participants are incentivized to be accurate. When tested on a large dataset with real-world production and consumption data, our approach is shown to provide incentives for accurate statements and increased economic profits for the cooperative.
Related bibliography: 1. Charilaos Akasiadis and Georgios Chalkiadakis: Agent Cooperatives for Effective Power Consumption Shifting. In Proc. of the 27th AAAI Conference on Artificial Intelligence (AAAI-2013), Bellevue, WA, USA, July 2013. 2. Charilaos Akasiadis and Georgios Chalkiadakis: Stochastic Filtering Methods for Predicting Agent Performance in the Smart Grid. In Proc. of the 21st European Conference on Artificial Intelligence (ECAI-2014), Prague, Czech Republic, August 2014 [short paper]. An extended version of this paper, entitled Predicting Agent Trustworthiness for Large-Scale Power Demand Shifting , appeared in The AI for the Smart Grid Workshop (AI4SG) @ The 9th Hellenic Conference on Artificial Intelligence (SETN-2016), Thessaloniki, Greece, May 2016. 3. Charilaos Akasiadis and Georgios Chalkiadakis: Decentralized Large-Scale Electricity Consumption Shifting by Prosumer Cooperatives. In Proc. of the 21st European Conference on Artificial Intelligence (ECAI-2016), The Hague, The Netherlands, August 2016.
Contact person: Alessandro Farinelli