15h30 - 15h55
Demand response planner with scheduling for building districts
We present a demand response planner for a district with heterogeneous buildings and scheduling decisions. We use a multi-objective optimization model to trade off the total cost of energy consumption and the user’s dissatisfaction generated by load shifting. Computational experiments and simulations validate the performance of the proposed approach.
15h55 - 16h20
A bi-level approach for increase in power consumption predictability in smart grids
The decentralization of energy generation has motivated the development of Demand Response programs. We investigate one of these as a bi-level problem for the utility. In this framework, the utility sets pricing parameters for users to book consumption capacity. They optimize both their financial involvement and guaranteed information on users' consumption.
16h20 - 16h45
An optimization model for real-world electricity scheduling usage in smart homes
Smart homes have the potential to achieve optimal energy consumption so that households can profit from appropriately scheduling electricity consumption. Fully 35% of all households in North America and 20% in Europe are expected to become smart homes by 2020. However, integrated optimization models still have limitations in the number of specific models appliances considered and/or in their reliability. Our work presents a new appliance-oriented integrated linear optimization model to find an optimal trade-off between cost and comfort associated with the use of energy in residential equipment, appliances, and electric vehicles considering renewable local generation, batteries and demand response. We make use of selected models from the literature and analyze them in detail. The proposed model can be used in an energy management system to find an optimal consumption pattern and the corresponding trade-off between cost and comfort. Computational results validate the proposed model and demonstrate how it addresses the limitations of previous models in the literature.
16h45 - 17h10
A decomposition-based approach for the coordination of distributed energy resources
We present a decentralized framework for coordinating numerous and heterogeneous Distributed Energy Resources. This approach allows to integrate any type of resource whose operation can be formulated within a mixed-integer linear program. The practical efficiency of the algorithm is demonstrated through extensive computational experiments, using data from Ontario energy markets.