Aggregating and Disaggregating Flexibility Objects

Abstract

Flexibility objects, objects with flexibilities in time and amount dimensions (e.g., energy or product amount), occur in many scientific and commercial domains. Managing such objects with existing DBMSs is infeasible due to the complexity, data volume, and complex functionality needed, so a new kind of flexibility database is needed. This paper is the first to consider flexibility databases. It formally defines the concept of flexibility objects (flex-objects), and provide a novel and efficient solution for aggregating and disaggregating flex-objects. This is important for a range of applications, including smart grid energy management. The paper considers the grouping of flex-objects, alternatives for computing aggregates, the disaggregation process, their associated requirements, as well as efficient incremental computation. Extensive experiments based on data from a real-world energy domain project show that the proposed solution provides good performance while still satisfying the strict requirements.

Aggregating and Disaggregating Flexibility Objects

“…Finally, we discuss the results of our extensive set of experiments with both regular and balance aggregation and show that our solution scales well and handles aggregation and disaggregation efficiently and effectively. This paper significantly extends our previous work [2] by providing (1) a more concise problem formulation, also including balance aggregation, (2) detailed aggregation/disaggregation algorithms with pseudo-code, (3) five concrete balance aggregation algorithms, (4) computational complexity analyses, and (5) a set of comprehensive balance aggregation experiments.…”

“…An example of an entity (e) is an electric vehicle (EV) that is connected to a charging station (D) and consuming specific amounts of electrical s (2) s (4) Fig. 2: A generic flex-object energy (r) at different hours to fully charge its battery.…”

“…Such flexibilities can be captured by flexibility objects (in short, flex-objects), specifying (1) how much energy is needed, (2) when it is needed, and (3) what the tolerated flexibilities are regarding time (e.g., between 9 PM and 5 AM) and energy amount at consecutive time intervals (e.g., between 2 and 4 kWh in the first hour and 3 and 5 kWh in the second hour). By interconnecting thousands of European Electricity Market participantsconsumers, producers, aggregators, and Balance Responsible Parties (BRPs) -using a large-scale Energy Data Management System [1], these flexobjects undergo the cycle of aggregation, instantiation, and disaggregation, depicted in Figure 1.…”

Evaluating the Value of Flexibility in Energy Regulation Markets

“…Various techniques to aggregate micro flex-offers to macro flex-offers has been described in [13]. We will apply a simpler view on aggregation in this paper in order not to take the focus away from the investigation of the simple flexibility scenarios, as described below.…”

Towards the automated extraction of flexibilities from electricity time series

“…The figure also shows the flexibilities in the energy profile, specifically, at each (15 min) time interval it states the minimum and maximum required energy (solid and dotted area respectively). The MIRABEL project prototypes the data management infrastructure which enables near real-time flex-offer collection [3], aggregation [4], and scheduling [5], in addition to the reliable and near real-time forecasting of energy production and consumption [6]. To sum up, the flex-offer concept is the basis of the project.…”