Power Laws: Optimizing Demand-side Strategies Hosted By DrivenData

competition
complete
€23,000

Woohoo! This competition has come to a close!

Many thanks to the participants for all of their hard work and commitment to using data for good!

alt-text

This is one of three challenges in the “Power Laws” series being run simultaneoulsy by Schneider Electric. Each challenge explores a different aspect of energy efficiency and smart energy management. The winning algorithms from these competitions will be released under an open source license in order to spread understanding about how energy modeling works and what approaches are most effective.

Power Laws: Optimizing Demand-side Strategies

Flexibility can be defined as "the ability of a resource, whether any component or collection of components of the power system, to respond to the known and unknown changes of power system conditions at various operational timescales".1 The exploitation of flexibility is essential to avoid costly reinforcements of the power system and maintain security of supply while increasing the penetration of renewable (and intermittent) sources of energy.

Flexibility can be produced in different manners. It might come from generation options, from energy storage or from energy demand. In some cases, generation can also be proposed through alternative dispatchable assets such as Combined Heat and Power (CHP). Storage is valid for both electricity and heat. Energy storage is an easy way to increase building flexibility, provided there is a business case for such an investment. The present challenge is focused on making a good usage of an installed storage system.

Viewed from the demand side, in the case of smart buildings, time of use tariffs incite to use energy when it is the most available. Given such a tariff, the goal is to buy more energy when its price is the lowest, and buy less (or possibly sell) energy when its price is the highest.

Your goal in this competition is to build an algorithm that controls a battery charging system and spends the least amount of money over a simulation period.


Competition End Date:

March 31, 2018, 11:59 p.m. UTC

Place Prize Amount
1st €12,000
2nd €7,000
3rd €4,000

Prizes delivered by DrivenData in USD, based on the exchange rate on February 6, 2018.

1. E. Ela, M. Milligan, A. Bloom, A. Botterud, A. Townsend, and T. Levin. Evolution of Wholesale Electricity Market Design with Increasing Levels of Renewable Generation. Technical Report NREL/TP-5D00-61765, September 2014.