Off-Line and On-Line Optimization Under Uncertainty: A Case Study on Energy Management

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10848)


Optimization problems under uncertainty arise in many application areas and their solution is very challenging. We propose here methods that merge off-line and on-line decision stages: we start with a two stage off-line approach coupled with an on-line heuristic. We improve this baseline in two directions: (1) by replacing the on-line heuristics with a simple anticipatory method; (2) by making the off-line component aware of the on-line heuristic. Our approach is grounded on a virtual power plant management system, where the load shifts can be planned off-line and the energy balance should be maintained on-line. The overall goal is to find the minimum cost energy flows at each point in time considering (partially shiftable) electric loads, renewable and non-renewable energy generators, and electric storages. We compare our models with an oracle operating under perfect information and we show that both our improved models achieve a high solution quality, while striking different trade-offs in terms of computation time and complexity of the off-line and on-line optimization techniques.


Optimization Uncertainty Energy management 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.DISIUniversity of BolognaBolognaItaly

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