A Distributed anytime algorithm for Network Utility Maximization with application to real-time EV charging control

The control of Electric Vehicle (EV) charging to take full advantage of the available distribution network infrastructure represents a cornerstone for large-scale EV adoption and the reduction of greenhouse gas emissions. In this paper, we propose a novel distributed anytime algorithm to solve the Network Utility Maximization (NUM) problem with application to real-time EV charging control. We analyze its convergence conditions for synchronous and asynchronous execution. Beyond this, we evaluate our approach using real data and show its advantages against the standard dual decomposition approach. The control scheme in our approach is based on the notion of dynamic budgets defined by the protection devices and allocated to each EV charger. Given the system's current state, we solve EV charging as a NUM problem in a distributed manner and obtain closed form expressions for computations performed by EV chargers and protection devices. To cope with large EV numbers, their spatial distribution, and the highly dynamic state changes of the power grid, our approach allows for distributed computation capable of yielding feasible, albeit suboptimal, control values at any time.