Sanjay Chandlekar working with Dr. Sujit Gujar  presented the following two   papers at the 33rd International Joint Conference on Artificial Intelligence (IJCAI’24)) held in Jeju, South Korea from 3 to 9 August. 

• Towards Revolutionized Smart Grids: An AI-Driven Broker for Improved Operational Efficiency in Track: Doctoral Consortium – Sanjay Chandlekar and Sujit Gujar

 Here is the summary of the research work as explained by the authors:  

Smart grid system encompasses large power plants in the wholesale market and retail customers in the tariff market. An electricity broker liaises between the wholesale and tariff markets by procuring electricity from the power plants and selling it to subscribed customers. In our work, we address the prominent challenges in the smart grid system to achieve better efficiency. We discuss the wholesale market, for which we design efficient bidding strategies in periodic double auctions (PDAs), and the tariff market, which includes tariff contract generation strategies and peak demand mitigation strategies. We use the PowerTAC simulator as a test-bed; also utilise these strategies for our autonomous broker, VidyutVanika, which has been proven efficient in the PowerTAC tournaments. 

• Optimising Prosumer Policies in Periodic Double Auctions Inspired by Equilibrium Analysis in Main Track – Bharat Manvi; Sanjay Chandlekar and Easwar Subramanian, TCS Research

Here is the summary of the research work as explained by the authors:  

We consider a periodic double auction (PDA) wherein the main participants are wholesale suppliers and brokers representing retailers. The suppliers are represented by a composite supply curve and the brokers are represented by individual bids. Additionally, the brokers can also participate in small-scale selling by placing individual asks; hence, they act as prosumers. Specifically, in a PDA, the prosumers who are net buyers have multiple opportunities to buy or sell multiple units of a commodity with the aim of minimising the cost of buying across multiple rounds of the PDA. Formulating optimal bidding strategies for such a PDA setting involves planning across current and future rounds while taking into account the bidding strategies of other agents. In this work, we propose Markov perfect Nash equilibrium (MPNE) policies for a setup where multiple prosumers with knowledge of the composite supply curve compete to procure commodities. Thereafter, the MPNE policies are used to develop an algorithm called MPNE-BBS for the case wherein the prosumers need to re-construct an approximate composite supply curve using past auction information. The efficacy of the proposed algorithm is demonstrated on the PowerTAC wholesale market simulator against several baselines and state-of-the-art bidding policies.

August 2024