Sébastien Mathieu

An efficient algorithm for the provision of a day-ahead modulation service by a load aggregator

This article studies a decision making problem faced by an aggregator willing to offer a load modulation service to a Transmission System Operator. This service is contracted one day ahead and consists in a load modulation option, which can be called once per day. The option specifies the range of a potential modification on the demand of the loads within a certain time interval. The specific case where the loads can be modeled by a generic tank model is considered. Under this assumption, the problem of maximizing the range of the load modulation service can be formulated as a mixed integer linear programming problem. A novel heuristic-method is proposed to solve this problem in a computationally efficient manner. This method is tested on a set of problems. The results show that this approach can be orders of magnitude faster than CPLEX without significantly degrading the solution accuracy.

A quantitative analysis of the effect of flexible loads on reserve markets

We propose and analyze a day-ahead reserve market model that handles bids from flexible loads. This pool market model takes into account the fact that a load modulation in one. Direction must usually be compensated later by a modulation of the same magnitude in the opposite direction. Our analysis takes into account the gaming possibilities of producers and retailers, controlling load flexibility, in the day-ahead energy and reserve I markets, and in imbalance settlement. This analysis is carried out by an agent-based approach where, for every round, each actor uses linear programs to maximize its profit according to forecasts of the prices. The procurement of a reserve is assumed to be determined, for each period, as a fixed percentage of the total consumption cleared in the energy market for the same period. The results show that the provision of reserves by flexible loads has a negligible impact on the energy market prices but, markedly decreases the cost of reserve procurement. However, as the rate of flexible loads increases, the system operator has to rely more and more on non-contracted reserves, which may cancel out the benefits made in the procurement of reserves.

Direct control service from residential heat pump aggregation with specified payback

This paper addresses the problem of an aggregator controlling residential heat pumps to offer a direct control flexibility service. The service is defined by a 15 minute power modulation, upward or downward, followed by a payback of one hour and 15 minutes. The service modulation is relative to an optimized baseline that minimizes the energy costs. The potential amount of modulable power and the payback effect are computed by solving mixed integer linear problems. Within these problems, the building thermal behavior is modeled by an equivalent thermal network made of resistances and lumped capacitances whose parameters are identified from validated models. Simulations are performed on 100 freestanding houses. For an average 4.3 kW heat pump, results show a potential of 1.2 kW upward modulation with a payback of 600 Wh and 150 Wh of overconsumption. A downward modulation of 500 W per house can be achieved with a payback of 420 Wh and 120 Wh of overconsumption.

Agent-based analysis of dynamic access ranges to the distribution network

There is a need to clearly state an interaction model that formalizes interactions between actors of the distribution system exchanging flexibility. In previous works we quantitatively evaluated the performance of five interaction models devised with industrial partners using the agent-based testbed DSIMA. Simulation results showed that these interaction models relying on active network management suffer from a lack of coordination between the distribution and the transmission system operator, activating flexibility simultaneously in opposite directions. This paper introduces a new interaction model fixing this issue based on dynamic access bounds to the network changing throughout the day and preventing the activation of flexibility leading to congestions. This new interaction model is implemented in DSIMA and compared to a model restricting the grid users to a very restrictive but safe access range. Results show that this new model allows to safely increase by 55 % the amount of distributed generation in the network.

A combinatorial branch-and-bound algorithm for box search

Considering a set of points in a multi-dimensional space with an associated real value for each point, we want to find the box with the maximum sum of the values of the included points. This problem has applications in data mining and can be formulated as a mixed-integer linear program. We propose a branch-and-bound algorithm where the bounding is obtained by combinatorial arguments instead of the traditional linear relaxation. Computational experiments show that this approach competes with current state of the art mixed-integer solvers. The algorithm proposed in this paper may be seen as a simple and dependence-free method to solve the box search problem.

Box search for the data mining of the key parameters of an industrial process

To increase their competitiveness, many industrial companies monitor their production process, collecting large amount of measurements. This paper describes a technique using this data to improve the performance of a monitored process. In particular we wish to find a set of rules, i.e. intervals on a reduced number of parameters, for which an output value is maximized. The model-free optimization problem to solve is to find a box, restricted on a limited amount of dimensions, with the maximum mean value of the included points. This article compares a machine learning-based heuristic to the solution computed by a mixed-integer linear program on real-life databases from steel and glass manufacturing. Computational results show that the heuristic obtains comparable solutions to the mixed integer linear approach. However, the exact approach is computationally too expensive to tackle real life databases. Results show that the restriction of five process parameters, on these databases, may improve the quality of the process by 50%.