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Pierluigi Mancarella

Bio: Pierluigi Mancarella is an academic researcher from University of Melbourne. The author has contributed to research in topics: Demand response & Distributed generation. The author has an hindex of 51, co-authored 303 publications receiving 10667 citations. Previous affiliations of Pierluigi Mancarella include University of Manchester & Polytechnic University of Turin.


Papers
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Journal ArticleDOI
01 Mar 2008-Energy
TL;DR: In this paper, a set of specific examples to show the effectiveness of the trigeneration CO2 emission reduction (TCO2ER) indicator proposed in the companion paper (Part I: Models and indicators) is provided.

151 citations

Journal ArticleDOI
TL;DR: A robust operational optimization framework for smart districts with multi-energy devices and integrated energy networks based on mixed integer linear programming (MILP) and linear approximations of the nonlinear network equations is proposed.
Abstract: Smart districts can provide flexibility from emerging distributed multi-energy technologies, thus bringing benefits to the district and the wider energy system. However, due to nonlinearity and modeling complexity, constraints associated with the internal energy network (e.g., electricity, heat, and gas) and operational uncertainties (for example, in energy demand) are often overlooked. For this purpose, a robust operational optimization framework for smart districts with multi-energy devices and integrated energy networks is proposed. The framework is based on two-stage iterative modeling that involves mixed integer linear programming (MILP) and linear approximations of the nonlinear network equations. In the MILP optimization stage, the time-ahead set points of all controllable devices (e.g., electrical and thermal storage) are optimized considering uncertainty and a linear approximation of the integrated electricity, heat, and gas networks. The accuracy of the linear model is then improved at a second stage by using a detailed nonlinear integrated network model, and through iterations between the models in the two stages. To efficiently model uncertainty and improve computational efficiency, multi-dimensional linked lists are also used. The proposed approach is illustrated with a real U.K. district; the results demonstrate the model’s ability to capture network limits and uncertainty, which is critical to assess flexibility under stressed conditions.

143 citations

Journal ArticleDOI
TL;DR: It becomes clear that grids dominated by photovoltaic energy call for more EES, while large shares of wind rely more on transmission capacity, and the EES energy requirements can be at least halved.

143 citations

Journal ArticleDOI
15 Jul 2014-Energy
TL;DR: In this article, the authors introduce a comprehensive analysis framework and a relevant unified and synthetic Mixed-Integer Linear Programming optimization model suitable for evaluating the technoeconomic and environmental characteristics of different Distributed Multi-Generation (DMG) options.

132 citations

Proceedings ArticleDOI
01 Sep 2015
TL;DR: The CIGRE C6.22 Working Group, Microgrid Evolution Roadmap as discussed by the authors has recently finalized its first Technical Brochure, which describes the main elements required to justify, develop, and implement viable microgrids, which the Group defined as follows: Microgrids are electricity distribution systems containing loads and distributed energy resources.
Abstract: This paper reports on the work of the CIGRE C6.22 Working Group, Microgrid Evolution Roadmap, which has recently finalized its first Technical Brochure. The Working Group was asked to identify the main elements required to justify, develop, and implement viable microgrids, which the Group defined as follows: Microgrids are electricity distribution systems containing loads and distributed energy resources, (such as distributed generators, storage devices, or controllable loads) that can be operated in a controlled, coordinated way either while connected to the main power network or while islanded. The main types of microgrids are described, and a benefits estimation approach developed and demonstrated. Also, an extensive review is made of microgrid functionality and technology, and a data base of microgrid pilot projects has been built.

129 citations


Cited by
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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal Article
TL;DR: This research examines the interaction between demand and socioeconomic attributes through Mixed Logit models and the state of art in the field of automatic transport systems in the CityMobil project.
Abstract: 2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

4,784 citations