Michele Roccotelli

A District Energy Management Based on Thermal Comfort Satisfaction and Real-Time Power Balancing

This paper presents a district energy management strategy devoted to monitor and control the district power consumption in a twofold human-centered perspective: the respect of users comfort preferences and the minimization of the power consumption and costs. The presented district energy management system forwards the power profile determined the day ahead to each building energy management system that, in turn, minimizes its real-time power consumption and costs (based on rewards and penalties), respecting the comfort preferences. Successively, the power is redistributed among the district buildings in order to minimize the penalties by applying two approaches: a centralized approach for public buildings and a distributed methodology for private buildings. Such optimization problems are formalized by defining some linear programming problems: two case studies are solved to show the applicability of the proposed management strategies.

A control strategy for district energy management

This paper deals with the District Energy Management problem by proposing the hierarchical control architecture and a suitable control strategy for the energy governance of a district of public office buildings. The District Energy Management System (DEMS) provides energy for the building network on the basis of the Day-Ahead Energy Market rules. Moreover, it monitors the district power consumption and interacts with the Building Energy Management Systems (BEMS) to optimize the power consumption the day-ahead, by respecting the users comfort preferences and minimizing the costs. Two optimization models are formulated for both building and district energy management. The first optimization is performed by the BEMS and pursues the objective of satisfying the thermal comfort by minimizing the power cost function. The second optimization is performed by the DEMS in order to minimize the district power cost by appropriately balancing the penalties and rewards.

An Integrated Framework for Binary Sensor Placement and Inhabitants Location Tracking

This correspondence paper deals with the sensor placement optimization problem in the context of indoor multiple inhabitants location tracking to solve ambient assisted living problems. Binary sensors, like passive infrared (PIR) sensors, are used to guaranty specific coverage requirements and allow privacy respecting. Moreover, within real home environments, different kinds of obstacles (like walls, high furniture, etc.) can affect the detection capacity of PIR sensors. This paper proposes an integrated framework devoted to optimize the placement of sensors and PIR sensors in smart homes by taking into account physical topologies and coverage precision constraints. An integer linear programming problem is formalized and a case study illustrates the applicability of the proposed approach and the scalability of the optimization method.

Optimal energy management integrating renewable energy, energy storage systems and electric vehicles

This paper addresses the problem of the energy management of cooperative district microgrids: the goal is maximizing the utilization of energy bought at the day-ahead energy market by avoiding the real-time purchase of additional energy. To this purpose the District Energy Management System (DEMS) controls the real-time energy consumption of the district and minimizes additional real-time energy requests. A Linear Programming problem is formulated and solved by the DEMS by optimally integrating renewable energy sources, storage systems and electric vehicles considered energy storages in the district microgrids. A case study enlightens and compares the benefits of the presented strategy.

Motion detector placement optimization in smart homes for inhabitant location tracking

The aim of the paper is to provide an optimal placement of sensors for inhabitant location tracking in smart homes, by using only motion detectors. In particular, motion detectors are binary sensors largely used in ambient assisted living applications because they are low cost, non-intrusive and privacy sensors. An approach to optimize the placement of motion detectors in a real home environment by adopting a two-dimensional grid is presented. In this context, the real coverage area of a sensor is computed by considering the obstacles and respecting the specified coverage performance requirements. The optimization problem is formalized and solved as an Integer Linear Programming problem and a case study is presented to show the efficacy of the proposed approach.

Actors interactions and needs in the European electromobility network

The standardization of services in the European electromobility network is becoming one of the main goal of researchers and practitioners. In this context, the objective of the paper is proposing a general view of the main needs and functions of the involved actors and stakeholders, and to state their interactions within the electromobility network. In particular, actors and stakeholders are grouped in so called macro-areas, and the interoperability and cooperation at both macro-areas and actors levels are provided by means of Unified Modeling Language (UML) diagrams.

A natural ventilation control in buildings based on co-simulation architecture and Particle Swarm Optimization

This paper presents a building automation strategy for natural ventilation control and reducing building energy consumption. An on-off control is proposed in order to manage the windows opening and realize a natural ventilation flow guaranteeing indoor thermal comfort. The control logic is based on activation thresholds that are optimized to reduce the discomfort for overheating and undercooling. In particular, the temperature comfort range dynamically varies according to the adaptive thermal comfort theory. To this aim, a co-simulation architecture is proposed: the thermal building behavior and ventilation dynamics are simulated by TRNFLOW within the TRNSYS software and a Particle Swarm Optimization algorithm is employed to optimize the thresholds of windows opening. A case study focusing on a residential building situated in the Mediterranean climatic context is presented: the thermal comfort analysis shows that the optimized control logic significantly reduces the overheating discomfort.