Find an incentive plan to improve the behaviour of a set of energy units

From Linked Building Data Community Group
  • Title: Find an incentive plan to improve the behaviour of a set of energy units
  • Description: employs combinatorial optimization technology to provide a policy maker with suggestions about which incentive schemes (and amounts) are more likely to achieve specific energy related goals (e.g. a reduction of the energy consumption).

The user must specify a target district, described as a set of energy units whose consumption/production profiles are susceptible to incentives. The system outputs an incentive plan, specified as an allocation of resources (e.g. money) to a set of incentive schemes (e.g. one-time incentives or tax reductions for buying and installing PV plants). The incentives will affect the behaviour of the target energy unit. In particular, possible changes include: 1) Modification of the consumption/production profile of the energy unit 2) The impact of the consumption/production profile on one or more global metrics (e.g. CO2 emissions). The resource allocation will be done so as to optimize a cost metric of choice (e.g. diffusion of renewable energy sources, the amount of the required budget) and will take into account the citizen responsiveness to the considered incentive schemes. The user will have the ability to specify a number of constraints: budget limits will be very common, but other types of constraints will be also supported (e.g. required reduction of CO2, required improvements in the renewable energy production, budget limits).

  • Domain(s): Energy, Building Data, Geolocation Data
  • Objectives: Support the definition of incentive plans: this service is specific for policy makers and it is meant to complement the manual “generate-and-test” approach that is usually employed to identify incentive plans. In particular, the ability to specify constraints will let the user decide exactly which part of the incentive plan should be automatically generated.
  • Stakeholders: Policy maker
  • Requirements:
  • LD Benefits:
  1. data integration;
  • Challenges
  1. integrating data on-demand;