arXiv subjects

Matteo Saviozzi

Publications and source records attributed to Matteo Saviozzi.

5 recordsLinked to original sources

arXiv2023

Performance Investigation of an Optimal Control Strategy for Zero-Emission Operations of Shipboard Microgrids

This work introduces an efficient power management approach for shipboard microgrids that integrates diesel generators, a fuel cell, and battery energy storage system. This strategy addresses both unit commitment and power dispatch, considering the zero-emission capability of the ship, as well as optimizing the ship's speed. The optimization is done through mixed integer linear programming with the objective of minimizing the operational cost of all the power resources. Evaluations are conducted on a notional all-electric ship, with electrical load simulated using a Markov chain based on actual measurement data. The findings underscore the effectiveness of the proposed strategy in optimizing fuel consumption while ensuring protection against blackout occurrences.

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arXiv2023

A Security-Constrained Optimal Power Management Algorithm for Shipboard Microgrids with Battery Energy Storage System

This work proposes an optimal power management strategy for shipboard microgrids equipped with diesel generators and a battery energy storage system. The optimization provides both the unit commitment and the optimal power dispatch of all the resources, in order to ensure reliable power supply at minimum cost and with minimum environmental impact. The optimization is performed solving a mixed integer linear programming problem, where the constraints are defined according to the operational limits of the resources when a contingency occurs. The algorithm is tested on a notional all-electric ship where the ship's electrical load is generated through a Markov chain, modeled on real measurement data. The results show that the proposed power management strategy successfully maximizes fuel saving while ensuring blackout prevention capability.

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arXiv2022

Methods and Tools for the Management of Renewable Energy Communities: the ComER project

Renewable Energy Communities (RECs) have been officially introduced into the European legislation through the Clean Energy for all Europeans package. A REC is defined as an association of citizens, commercial activities, enterprises, and local authorities that own small-scale power plants based on Renewable Energy Sources (RESs). The community has the objective of maximizing the share of renewable energy, i.e. the self-consumption of the energy generated by the community RES power plants and to generally optimize the use of electrical energy. This paper describes the ComER project, developed by the University of Cassino and the Campus Bio-Medico University of Rome. The project focuses on the main technical problems to face for the realization of a REC. The principal objective is to develop methods and tools necessary for the management and control of RECs. In particular, this paper describes the rules established for RECs in the Italian legislations, the organization of the ComER project, the adopted solutions and the first obtained results.

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arXiv2022

Optimal Management of Renewable Generation and Uncertain Demand with Reverse Fuel Cells by Stochastic Model Predictive Control

This paper proposes a control strategy for a Reverse Fuel Cell used to manage a Renewable Energy Community. A two-stage scenario-based Model Predictive Control algorithm is designed to define the best economic strategy to be followed during operation. Renewable energy generation and users' demand are forecasted by a suitably defined Discrete Markov Chain based method. The control algorithm is able to take into account the uncertainties of forecasts and the nonlinear behaviour of the Reversible Fuel Cell. The performance of proposed approach is tested on a Renewable Energy Community composed by an aggregation of industrial buildings equipped with PV.

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arXiv2020

An Optimization Problem for Day-Ahead Planning of Electrical Energy Aggregators

The widespread diffusion of distributed energy resources, especially those based on renewable energy, and energy storage devices has deeply modified power systems. As a consequence, demand response, the ability of customers to respond to regulating signals, has moved from large high-voltage and medium-voltage end-users to small, low-voltage, customers. In order to be effective, the participation to demand response of such small players must be gathered by aggregators. The role and the business models of these new entities have been studied in literature from a variety of viewpoints. Demand response can be clearly applied by sending a dedicated price signal to customers, but this methodology cannot obtain a diverse, punctual, predictable, and reliable response. These characteristics can be achieved by directly controlling the loads units. This approach involves communication problems and technological readiness. This paper proposes a fully decentralized mixed integer linear programming approach for demand response. In this framework, each load unit performs an optimization, subject to technical and user-based constraints, and gives to the aggregator a desired profile along with a reserve, which is guaranteed to comply with the constraints. In this way, the aggregator can trade the reserve coming from several load units, being the only interface to the market. Upon request, then, the aggregator communicates to the load units the modifications to their desired profiles without either knowing or caring how this modification would be accomplished. The effectiveness is simulated on 200 realistic load units.

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