Advanced demand response solutions based on fine-grained load control

Abstract

International audience—We consider demand response solutions having the capability to monitor different variables at users' premises, like presence and temperature, and to control individual appliances. We focus on the optimal control of the appliances during time periods where the available capacity is not enough to satisfy the demand generated by houses operating freely. We propose an approach to define the utility of appliances as a function of monitored variables, as well as control schemes to optimize this utility. Global optimums can be reached when a centralized entity (i.e., an aggregator) can gather information from each user and control each individual appliance. This may not be always possible, for example for privacy and/or scalability reasons. We therefore consider, in addition, a system where decisions are taken partially at a centralized site (global power allocation per home) and partially at customer premises (sharing of the allocated power among local appliances). Performances of proposed control mech-anisms are evaluated and compared. We show the potential value of introducing demand response mechanisms at fine granularity

Advanced demand response solutions for capacity markets

“…It also has obvious privacy issues. As stated in the introduction, the present work builds on conclusion of the analysis in [3]. Most closely related work to our proposal is the scheme presented in [11] which is very similar to [5] if prices are interpreted as control signals.…”

“…They propose a greedy algorithm (maximizes utility slot by slot) based on the utility that each appliance declare for each slot. It's shown in [3] that such an allocation has low performance since decisions are taken with no view on the global time period. It also has obvious privacy issues.…”

“…Following [3], a specific utility function is modeled for each class of appliances based on usage patterns and criticality, users' preferences and exogenous variables (e.g. external temperature).…”

“…In [3] the authors propose and analyze several IoT-based DR mechanisms. They show that fine-grained visibility and control on a set of households at an aggregation point enables to maximize users perceived utility.…”

“…Proposed solution enforce fairness by considering two levels of utility for each appliance (i.e., vital and comfort). We compare the performance of the proposed scheme with the two cases studied in [3] (fully centralized solution and two level system with no feedback). Results are analyzed for homogeneous (all households have the same characteristics) and heterogeneous scenarios.…”