The electricity distribution grid --the low-voltage line networks that distribute power to end consumers--is about to undergo a major transformation. More and more consumers are becoming "prosumers", namely consumers and producers of power at the same time, by installing solar panels (PVs) on their home roofs and by purchasing electric vehicles, which may be used for energy storage. Traditionally, power in distribution grids has flown one way: from the substation to the end consumer. In the new world of prosumers, distribution grids need to accommodate flow in both directions. This is challenging the existing wire and transformer abilities to serve load at acceptable quality levels. Moreover, the increasing number of prosumers is resulting in dramatically higher uncertainty in demand forecasting, which, with further prosumer increase, may prove unsustainable and ultimately threaten the utility companies' operation and business viability. This research advances the fields of computation and economics as well as the power systems domain, by contributing with novel algorithmic and mechanism design problem formulations and techniques, and with solutions that can enable improved distribution grid planning and operation. In terms of broader impact, this research has the potential to improve aspects of the grid such as planning for increased integration of renewable energy resources, mitigation of risks associated with variability of renewables, better management of congestion in the face of strategic prosumers and ultimately provide for more reliable, cost effective and efficient operation of the grid.

The goal of this project is to help the distribution grid and its participants transition from its current functionality of serving mostly traditional consumers, to the future grid that needs to sustainably integrate prosumers, renewables and distributed energy resources, via: (1) Developing simplified mathematical models to solve combinatorial and incentive problems that will enable the future power grid to sustain massive growth in renewables and distributed energy resources; (2) Designing new algorithmic and mechanism design approaches that reduce congestion, and improve the investment and operational efficiency of the grid while further enhancing its reliability; (3) Working with Distribution Utilities for real-world models and operational advice, while facilitating the transfer of research findings to practice. The scope of the project includes (i) distribution network reconfiguration, (ii) distribution system upgrades and (iii) market mechanisms for supply-demand balancing. The research relies on methods from approximation algorithms and mechanism design, such as submodular optimization, stochastic combinatorial optimization, and price of anarchy analysis.

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University of Texas Austin
United States
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