The ISO Problem: Decentralized Stochastic Control via Bidding Schemes

TL;DR

This paper presents a decentralized bidding scheme for smart-grid energy management, enabling agents to optimize demand and renewable generation without revealing private system information, through an iterative ISO-agent interaction.

Contribution

It introduces a simple iterative bidding procedure that converges to the optimal solution for decentralized stochastic control in smart grids without sharing private data.

Findings

Converges to the optimal energy allocation under certain conditions.

Enables demand response for stochastic loads.

Optimizes renewable and fossil fuel generation utilization.

Abstract

We consider a smart-grid connecting several agents, modeled as stochastic dynamical systems, who may be electricity consumers/producers. At each discrete time instant, which may represent a 15 minute interval, each agent may consume/generate some quantity of electrical energy. The Independent System Operator (ISO) is given the task of assigning consumptions/generations to the agents so as to maximize the sum of the utilities accrued to the agents, subject to the constraint that energy generation equals consumption at each time. This task of coordinating generation and demand has to be accomplished by the ISO without the agents revealing their system states, dynamics, or utility/cost functions. We show how and when a simple iterative procedure converges to the optimal solution. The ISO iteratively obtains electricity bids by the agents, and declares the tentative market clearing prices. In response to these prices, the agents submit new bids. On the demand side, the solution yields an optimal demand response for dynamic and stochastic loads. On the generation side, it provides the optimal utilization of stochastically varying renewables such as solar/wind, and generation with fossil fuel based generation with dynamic constraints such as ramping rates. Thereby we solve a decentralized stochastic control problem, without agents sharing any information about their system models, states or utility functions.