Michela Robba

Optimizing forest biomass exploitation for energy supply at a regional level.

A decision support system for forest biomass exploitation for energy production purposes is presented. In the proposed approach, geographic information system based techniques are integrated with mathematical programming methods to yield a comprehensive system that allows the formalisation of the problem, decision taking, and evaluation of effects. The aim of this work is to assess the possibility of biomass exploitation for both thermal and electric energy production in a given area, while relating this use to an efficient and sustainable management of the forests within the same territory. The decision support system allows for the locating of plants and the computing of their optimal sizing (defining which kind of energy is convenient to produce for the specific area), taking into account several aspects (economic, technical, regulatory, and social) and deciding how to plan biomass collection and harvesting. A case study applied to a small Italian mountain area is presented.

An environmentally sustainable decision model for urban solid waste management

The aim of this work is to present the structure and the application of a decision support system (DSS) designed to help decision makers of a municipality in the development of incineration, disposal, treatment and recycling integrated programs. Specifically, within a MSW management system, several treatment plants and facilities can generally be found: separators, plants for production of refuse derived fuel (RDF), incinerators with energy recovery, plants for treatment of organic material, and sanitary landfills. The main goal of the DSS is to plan the MSW management, defining the refuse flows that have to be sent to recycling or to different treatment or disposal plants, and suggesting the optimal number, the kinds, and the localization of the plants that have to be active. The DSS is based on a decision model that requires the solution of a constrained non-linear optimization problem, where some decision variables are binary and other ones are continuous. The objective function takes into account all possible economic costs, whereas constraints arise from technical, normative, and environmental issues. Specifically, pollution and impacts, induced by the overall solid waste management system, are considered through the formalization of constraints on incineration emissions and on negative effects produced by disposal or other particular treatments.

Solid waste management in urban areas: Development and application of a decision support system

A decision support system (DSS) developed to assist the planner in decisions concerning the overall management of solid waste at a municipal scale is described. The DSS allows to plan the optimal number of landfills and treatment plants, and to determine the optimal quantities and the characteristics of the refuse that has to be sent to treatment plants, to landfills and to recycling. The application of the DSS is based on the solution of a constrained non-linear optimization problem. Various classes of constraints have been introduced in the problem formulation, taking into account the regulations about the minimum requirements for recycling, incineration process requirements, sanitary landfill conservation, and mass balance. The cost function to be minimized includes recycling, transportation and maintenance costs. The DSS has been tested on the municipality of Genova, Italy, and the results obtained are presented.

A Dynamic Decision Model for the Real-Time Control of Hybrid Renewable Energy Production Systems

The use of renewable energy sources can reduce the greenhouse gas emissions and the dependence on fossil fuels. The main problem of the installations based on renewable energy is that electricity generation cannot be fully forecasted and may not follow the trend of the actual energy demand. Hybrid systems (including different subsystems such as renewable energy plants, energy storage systems based on hydrogen or dam water reservoirs) can help in improving the economic and environmental sustainability of renewable energy plants. In addition, hybrid systems may be used to satisfy other user demands (such as water supply or hydrogen for automotive use). However, their use should be optimized in order to fulfill the user demand in terms of energy or other needs. In this paper, a model representing an integrated hybrid system based on a mix of renewable energy generation/conversion technologies (e.g., electrolyzer, hydroelectric plant, pumping stations, wind turbines, fuel cell) is presented. The model includes an optimization problem for the control of the different ways to store energy. The goal is to satisfy the hourly variable electric, hydrogen, and water demands. A specific application area in Morocco is considered and the results obtained are discussed in detail.

A dynamic optimization model for solid waste recycling

Recycling is an important part of waste management (that includes different kinds of issues: environmental, technological, economic, legislative, social, etc.). Differently from many works in literature, this paper is focused on recycling management and on the dynamic optimization of materials collection. The developed dynamic decision model is characterized by state variables, corresponding to the quantity of waste in each bin per each day, and control variables determining the quantity of material that is collected in the area each day and the routes for collecting vehicles. The objective function minimizes the sum of costs minus benefits. The developed decision model is integrated in a GIS-based Decision Support System (DSS). A case study related to the Cogoleto municipality is presented to show the effectiveness of the proposed model. From optimal results, it has been found that the net benefits of the optimized collection are about 2.5 times greater than the estimated current policy.

A Multilevel Approach for the Optimal Control of Distributed Energy Resources and Storage

An approach is proposed to deal with distributed energy resources, renewables and storage devices connected to microgrids. Specifically, a multilevel architecture is introduced and evaluated for the following main purposes: to reduce the computational complexity, to deal with different decentralized microgrids, different decision makers, and multiple objectives. A two-level decision architecture based on a Model Predictive Control (MPC) scheme is presented, in which the upper decision level has the function of fixing the values of a certain set of parameters (reference values), by assuming a certain structure of the control strategies to be applied at the lower decision level. On the basis of such parameters, each decision maker at the lower level solves its own optimization problem by tracking the reference values provided by the upper level. The effectiveness of the proposed approach is demonstrated. The application of the proposed control architecture to a specific case study (Savona, Italy) is presented and discussed.

A system of systems model for the control of the university of Genoa Smart Polygeneration Microgrid

Experimental tests and demonstration projects are very useful to derive new methods and tools for the optimal control of smart grids. In this work, the University of Genoa Smart Polygeneration Microgrid (SPM) is firstly presented, in connection with the different sub-systems that compose the overall system. Then, a simplified mathematical dynamic model, that can be used for optimal control purposes, is described. Finally, a dynamic optimization problem is formalized and solved.

Planning and management of sustainable microgrids: The test-bed facilities at the University of Genoa

The aim of this paper is to describe the system composed by the SPM (Smart Polygeneration Microgrid) feeding the SEB (Sustainable Energy Building) at the University of Genoa (Savona Campus), and to assess the Campus operating costs, CO2 emissions, and primary energy annual savings determined by the combined SPM-SEB system. This work highlights the main difference between two scenarios (AS-IS and TO-BE) with specific reference to operation and management of various power units. As demonstrated by the work, besides research and testing of new devices, the SPM-SEB can be used also for demonstration and teaching activities, and contributes to increase the overall energy efficiency of the Campus, lowering its primary energy consumption.

An optimization algorithm for the operation planning of the University of Genoa smart polygeneration microgrid

The aim of this paper is to describe the Smart Polygeneration Microgrid (SPM), which is being constructed at the Savona Campus of the Genoa University, also thanks to funding from the Italian Ministry of Education, University and Research (amount 2.4 Million Euros). Specifically, a detailed model of the grid is presented and an optimization problem is defined, in order to achieve suitable goals, like the minimization of the production costs or the maximization of power quality or environmental indices.

A Bilevel Approach for the Optimal Control of Flows Through a Network

The operational management of traffic flows, controlled by different decision makers (that do not exchange information) through a network, gives rise to a common modeling framework that may find application within different research areas: road traffic control, hazardous materials transportation, telecommunication networks, energy systems. In this paper, a general decision architecture is considered and an application is provided to the case of the management of fleets of vehicles that transport hazardous materials (hazmat). The considered architecture takes into account the presence of different decision makers. The problem is also characterized by the presence of several (possibly conflicting) objectives. In the case of hazmat transportation, such objectives may be the reduction of economic costs and the containment of the risk (for vehicles and infrastructures). The considered model includes an upper-level decision maker that can take decisions affecting the utility functions of the lower-level decision makers (LDMs), for example, changing the tolls for the LDMs, but leaving to such LDMs some decision capability. A specific case study is considered, relevant to the management of vehicles carrying hazmat through a critical infrastructure.