Optimal collaborative demand-response planner for smart residential buildings

Abstract

This work presents a collaborative scheme for the end-users in a smart building with multiple housing units. This approach determines a day-ahead operational plan that provides demand-response services by taking into account the amount of energy consumed per household, the use of shared storage and solar panels, and the amount of shifted load. We use a biobjective optimization model to trade off total user satisfaction versus total cost of energy consumption. The optimization works in combination with a price structure based on time and level of use that encourages load shifting and benefits the participants. Computational experiments and an extensive sensitivity analysis validate the performance of the proposed approach and help to clarify its strengths, its limits, and the requirements for ensuring the desired outcome.

Smart grid lab research in Europe and beyond

“…The research initiative Optimization for Smart Grids (OSG) was founded by a consortium of research institutes and the Polytechnique Montreal and is focused on the application of mathematical optimization techniques to the planning and operation of modern power systems. In particular, the areas in which the initiative is conducting research are system load management and DR, modeling, management and operation of smart buildings, maintenance scheduling in hydropower systems, location and pricing of EV charging stations, and the optimal provision of reactive power in a large‐scale grid …”

A Bilevel Approach to Optimal Price-Setting of Time-and-Level-of-Use Tariffs

“…In this model, neither of the user or supplier decisions influence the load distribution. The contributions of this article are the development of a variant of the Time-and-Level-of-Use (TLOU) tariff introduced in [2] and developed in [3], the formulation of the price-setting problem under this scheme from a supplier perspective as a bilevel bi-objective problem, the study of the structure of the game and feasible solutions for both players and the design of two efficient algorithms based on inverse optimization and the optimal value mapping and to solve the problem by finding the complete set of Pareto-efficient points.…”

Optimal setting of time-and-level-of-use prices for an electricity supplier

“…Recently, the authors in [8] and [9] presented a new price scheme called Time-and-Level-of-Use. TLOU offers a similar time-windows-structure to that of the traditional TOU, including power capacity limits that enable multi-ple energy prices in each time window depending on the consumption level.…”