Andrea Lanna

Optimal Planning and Routing in Medium Voltage PowerLine Communications Networks

This paper deals with the problem of deploying a PowerLine Communication (PLC) network over a medium voltage (MV) power grid. The PLC network is used to connect the end nodes (ENs) of the MV grid to the service provider by means of PLC network nodes enabled as access points. In particular, a network planning problem is faced wherein we require to define the PLC network topology by deciding which MV network nodes are to be enabled as access points. An optimization problem is then formulated, which minimizes the cost of enabling the access points and maximizes the reliability of PLC network paths in a multi-objective optimization fashion. This work also considers resiliency (i.e., it guarantees the PLC network connectivity even in case of link faults) and capacity constraints (i.e., it checks that there are enough resources to transmit the estimated amount of traffic over the PLC network paths). As a byproduct, the optimization algorithm also returns the optimal routing. Simulations based on realistic MV network topologies validate the proposed approach.

Resilient planning of PowerLine Communications networks over Medium Voltage distribution grids

In this paper a network planning problem aiming to enable underground Medium Voltage (MV) power grids to resilient PowerLine Communications (PLCs) is faced. The PLC network is used to connect PLC End Nodes (ENs) located into the secondary substations to the energy management system of the utility by means of PLC network nodes enabled as Access Points. An optimization problem is formulated, aiming to optimally allocate the Access Points to the substations and the repeaters to the MV feeders. A multi-objective optimization approach is used, in order to keep in balance the needs of minimizing the cost of equipment allocation and maximizing the reliability of PLC network paths. Resiliency and capacity constraints are properly modeled, in order to guarantee the communications even under faulted link conditions. As a byproduct, the optimization algorithm also returns the optimal routing. Simulations performed on a realistic underground MV distribution grid validate the proposed approach.

Electric Vehicles charging control based on future internet generic enablers

In this paper a rationale for the deployment of Future Internet based applications in the field of Electric Vehicles (EVs) smart charging is presented. The focus is on the Connected Device Interface (CDI) Generic Enabler (GE) and the Network Information and Controller (NetIC) GE, which are recognized to have a potential impact on the charging control problem and the configuration of communications networks within reconfigurable clusters of charging points. The CDI GE can be used for capturing the driver feedback in terms of Quality of Experience (QoE) in those situations where the charging power is abruptly limited as a consequence of short term grid needs, like the shedding action asked by the Transmission System Operator to the Distribution System Operator aimed at clearing networks contingencies due to the loss of a transmission line or large wind power fluctuations. The NetIC GE can be used when a master Electric Vehicle Supply Equipment (EVSE) hosts the Load Area Controller, responsible for managing simultaneous charging sessions within a given Load Area (LA); the reconfiguration of distribution grid topology results in shift of EVSEs among LAs, then reallocation of slave EVSEs is needed. Involved actors, equipment, communications and processes are identified through the standardized framework provided by the Smart Grid Architecture Model (SGAM).

Model Predictive Control of Energy Storage Systems for Power Tracking and Shaving in Distribution Grids

In this paper, a model predictive control (MPC) strategy is proposed to control the energy flows in a distribution network node (e.g., a distribution substation) equipped with an electric storage system (ESS) and serving a portion of the grid with high penetration of renewable energy sources (RES). The aim is to make the power flow at node level more controllable in spite of the presence of fluctuating distributed energy resources. In particular, the proposed control strategy is such that the controlled power flow at node level tracks the profile established on a day-ahead basis for efficient operation of the grid. That is achieved by letting the MPC controller decide the current storage power setpoint based on the forecasts of the demand and of the RES output. Theoretical results are reported on the stability of the proposed control scheme in a simplified setting foreseeing zero forecasting error. The performance of the system in the general case is then evaluated on a simulation basis. Simulations show the effectiveness in managing RES fluctuations in realistic settings.

Validation of the Italian version of interpersonal sensitivity measure (IPSM) in adolescents and young adults

BACKGROUND Interpersonal sensitivity is a personality trait that describes as excessive awareness of both the behaviour and feelings of others. High interpersonal sensitivity has been associated with the development and maintenance of mental health problems. This study aimed to examine whether the Italian version of the interpersonal sensitivity measure (IPSM) has good internal consistence and convergent validity. METHODS Validity was established on a sample of 153 Italian adolescents and young adult help seekers for several psychological problems. These subjects were divided in two groups - depressive spectrum disorder group (n=42) and other diagnosis group (n=111) - according to Structured Clinical Interview (SCID-I) for DSM-IV and Kiddie-Sads-Present and Lifetime Version (K-SADS-PL). For convergent validity, we studied the correlation between total and each subscale IPSM scores and the General Symptoms (included depressive and dysphoric symptoms) of Prodromal Questionnaire. RESULTS The internal consistency were adequate and comparable to the original Boyce and Parker study. The validity was good, as indicated by both the convergent validity analysis and the depressive spectrum disorder group and other diagnosis group comparison. LIMITATIONS The absence of another scale measuring interpersonal sensitivity to assess the construct validity of IPSM; the clinical heterogeneity of the sample; the absence of test re-test reliability of the instrument. CONCLUSIONS Analysis of the results of internal consistency and convergent validity of the IPSM indicates that this version translated into Italian is valid and reliable.

Electric vehicle trip planning integrating range constraints and charging facilities

This paper presents a strategy for multi-modal trip planning integrating the management of fully electric vehicle range and charging services along the trip. The network graph is modelled as the superposition of layers representing different transportation means and charging infrastructure, putting in evidence the interaction between the transportation and electricity distribution grids. The presence of energy constraints on the network nodes implies to formalize the trip planning problem as a resource constrained shortest path problem, and solve it through an ad-hoc decomposition strategy. The proposed approach is validated through the simulation of realistic test cases, showing its effectiveness and potential in satisfying complex user preferences, mitigating drivers perception about limited vehicle range and availability of charging infrastructure, smoothing the impact of massive fully electric vehicle charging on distribution grids.

Electric energy storage systems integration in distribution grids

This paper presents a real time control strategy for dynamically balancing electric demand and supply at local level, in a scenario characterized by a HV/MV substation with the presence of renewable energy sources in the form of photovoltaic generators and an electric energy storage system. The substation is connected to the grid and is powered by an equivalent traditional power plant playing the role of the bulk power system. A Model Predictive Control based approach is proposed, by which the active power setpoints for the traditional power plant and the storage are continually updated over the time, depending on generation costs, storages state of charge, foreseen demand and production from renewables. The proposed approach is validated on a simulation basis, showing its effectiveness in managing fluctuations of network demand and photovoltaic generation in test and real conditions.

Real time optimal power flow integrating large scale storage devices and wind generation

This paper presents a real time strategy for optimal power flow in presence of storage devices and wind turbine driven by Doubly Fed Induction Generators. These elements work in cooperation defining a dynamic bus where the generated power is subject to temporal constraints, which establish a coupling between traditional power flow problems related to consecutive time periods; further the uncertainty in wind power generation forecasts requires a continuous update of the planned power profiles, in order to guarantee a dynamic equilibrium among demand and supply. Model predictive control is used for this purpose, considering the dynamic equations of the storage and the wind turbine rotor as prediction models. A proper target function is introduced in order to find a trade-off between the need of minimizing generation costs and the excursions of the storage state of charge and the wind turbine angular speed from reference states. In the case study under consideration storage, wind turbines and a traditional synchronous generator are operated by the Transmission System Operator in the form of a Virtual Power Plant working as slack bus to cover network losses. The proposed approach is validated on simulation basis.

An any-sink energy-efficient routing protocol in multi-hop wireless sensor networks for planetary exploration

Summary Wireless sensor networks (WSNs) are made of spatially distributed autonomous sensors, which cooperate to monitor physical or environmental parameters and to deliver such data to one or more data sinks. A promising field of application of WSNs is planetary exploration, characterized by a continuous monitoring of the surface to have clear notion of planet conditions and prepare for future manned missions. The potentially large size of the region to be monitored and the line-of-sight limitations (as, for instance, on the Moon, which is the case study discussed in the paper) hamper the possibility of having 1-hop sensor-sink communications. Therefore, to allow sensed data to reach the sink(s), the sensors must be able to create and maintain a multi-hop ad hoc network. This paper proposes an ad hoc routing algorithm applicable to WSNs for planetary exploration, aiming at (i) assuring any-cast communications with multiple data sinks, (ii) minimizing the control overhead for routing maintenance, (iii) being light in terms of memory/computational requirements, to be installed into low-power and low-memory/processing devices, (iv) being rapid to reconfigure in the presence of node failures and (v) optimizing the choice of the paths, to achieve energy balancing and saving. Extensive simulations show the efficiency of the proposed approach. Copyright

A QoE-aware dynamic bandwidth allocation algorithm based on game theory

Quality of Experience (QoE) is a wide concept including user perception, behavior and expectations as well as application and network performances. The Internet of the future should be able to increase the QoE offered to the users, also in relationship with their commercial profiles. This paper presents an innovative approach, based on game theory, which, according to the feedback of QoE, is able to dynamically assign the available bandwidth of a shared technology (e.g. a WLAN, a cell) to the running flows, in order to maximize the QoE of the users and to guarantee fairness. Moreover, flows could be prioritized, according to commercial profiles (e.g., flows for which users pay more must be served with higher quality). The proposed approach is independent of the way the feedback of QoE is computed (it could be given by a direct user quality expression, estimated from the QoS measurements, from the users behavior, etc.): the only assumption is that the QoE is a non-decreasing continuous function of the bandwidth allocated to the application. Simulations, considering audio flows with different codecs for which the IQX hypothesis (i.e., exponential interdependency of QoE and QoS) holds, show high performances and fairness/prioritization properties.