Multi-commodity network flow models for dynamic energy management – Mathematical formulation

Abstract The evolution of energy infrastructures towards a more distributed, adaptive, predictive and marketbased paradigm implies an effort on combining communication protocols and energy transmission and distribution systems in a common architecture. This architecture should allow decentralized control in order to be able to manage efficiently distributed generation, storage and exchange of energy between sources and sinks. Dynamic energy management models are a part of this "systems thinking" vision that aims to create a new field of applications that is at the intersection of computing science and energy technology. The broader implications associated with them are related with the possibility of creating communities that integrate energy supply and demand within a given region, in order to limit their impact. In order to push intelligence to the energy networks' edges, up to individual sources and sinks, scalable and flexible distributed systems will have to be build. In this sense, data mining techniques and multicommodity network flow models can be combined for pattern detection, forecasting and optimization, which are essential features of dynamic energy management

Parametric performance analysis and energy model calibration workflow integration - A scalable approach for buildings

High efficiency paradigms and rigorous normative standards for new and existing buildings are fundamental components of sustainability and energy transitions strategies today. However, optimistic assumptions and simplifications are often considered in the design phase and, even when detailed simulation tools are used, the validation of simulation results remains an issue. Further, empirical evidences indicate that the gap between predicted and measured performance can be quite large owing to different types of errors made in the building life cycle phases. Consequently, the discrepancy between a priori performance assessment and a posteriori measured performance can hinder the development and diffusion of energy efficiency practices, especially considering the investment risk. The approach proposed in the research is rooted on the integration of parametric simulation techniques, adopted in the design phase, and inverse modelling techniques applied in Measurement and Verification (M&V) practice, i.e., model calibration, in the operation phase. The research focuses on the analysis of these technical aspects for a Passive House case study, showing an efficient and transparent way to link design and operation performance analysis, reducing effort in modelling and monitoring. The approach can be used to detect and highlight the impact of critical assumptions in the design phase as well as to guarantee the robustness of energy performance management in the operational phase, providing parametric performance boundaries to ease monitoring process and identification of insights in a simple, robust and scalable way

Optimization concepts in district energy design and management – A case study

AbstractThe integration of optimization techniques in building and district energy design constitute an essential tool for reducing the global impact of energy services. Appropriate dynamic energy management systems must be employed too in order to maintain a high level of performance in the operational phase and to obtain better system knowledge. Therefore, in the strategic energy planning of districts, it is necessary to embody the main concepts of Smart Grid and virtual power plants frameworks. In the research presented, the preliminary results from a case study are illustrated with a reflection on energy consumption subdivision and load profiles for the sizing and operational strategy definition of distributed generation systems

Open data and models for energy and environment

An increasing number of data sources and models to handle them call for transparency and openness in assessing their goodness and practical use for people. The simplest and most robust tools to collect, process, and analyse data to offer solid data-based evidence for future projections in building and district and regional system planning are of interest. For this purpose, and following the success of the first Special Issue “Open Data and Energy Analytics”, the Special Issue “Open Data and Models for Energy and Environment” has been launched, intended for energy engineers and planners. Among a very high number of submissions, 10 articles were selected for acceptance and published

Multi-commodity network flow models for dynamic energy management – Smart Grid applications

AbstractThe strong interconnection between human activities, energy use and pollution reduction strategies in contemporary society has determined the necessity of collecting scientific knowledge from different fields to provide useful methods and models to foster the transition towards more sustainable energy systems. This is a challenging task in particular for contemporary communities where an increasing demand for services is combined with rapidly changing lifestyles and habits. The Smart Grid concept is the result of a confluence of issues and a convergence of objectives, which include national energy security, climate change, pollution reduction, grid reliability, etc. While thinking about a paradigm shift in energy systems, drivers, characteristics, market segments, applications and other interconnected aspects must be taken into account simultaneously. In this context, the use of multi-commodity network flow models for dynamic energy management aims at finding a compromise between model usefulness, accuracy, flexibility, solvability and scalability in Smart Grid applications

Open data and energy analytics

This pioneering Special Issue aims at providing the state-of-the-art on open energy data analytics; its availability in the different contexts, i.e., country peculiarities; and at different scales, i.e., building, district, and regional for data-aware planning and policy-making. Ten high-quality papers were published after a demanding peer review process and are commented on in this Editorial

A Case Study of Solar Technologies Adoption: Criteria for BIPV Integration in Sensitive Built Environment

Abstract Solar Photovoltaics is one of the core technologies for a paradigm shift of our electric infrastructure towards distributed generation. In 2011 Italy became the first world market; however, Germany has even the primacy of accumulated power. The installed capacity amounted to 10.000 MW according to data of Italian Manager of Energy Services (GSE) against 1.000 MW in 2010 and 3.000 the beginning of 2011. The projections of GSE include the achievement of the 12.000 MW by the end of the year with more than 350.000 running plants. In a nearly mature market, cost related issues and technical difficulties are encountered in particular in the successful integration within a sensitive and consolidated built environment. The research presented aims to investigate the possible results of an effective use of Building Integrated Photovoltaics (BIPV), choosing existing buildings in the city of Bellinzona (Canton Ticino, CH) as case studies. Bellinzona presents similar characteristics to small Northern Italian cities in terms of built environment characteristic and climate conditions. The theoretical framework for the analysis is the one proposed initially for low energy and nearly net zero energy buildings (NZEB). Although this type of analysis has been developed, in particular, for building with high penetration of renewable energy sources generation (up to 100% of the energy consumed), it seems worth investigating the dynamic interaction of building energy demand, on-site generation and grid with similar tools, because of the necessity of achieving low energy demand also in retrofitted existing buildings in a near future

Building performance monitoring: From in-situ measurement to regression-based approaches

Simple and robust data analysis methodologies are crucial to learn insights from measured data and reduce the performance gap in building stock. For this reason, continuous performance monitoring should become a more diffuse practice in order to improve our design and operation strategies for the future. The research presented aims to highlight potential links between experimental approaches for test-facilities and methods and tools used for continuous performance monitoring, at the state of the art. In particular, we explore the relation between ISO 9869:2014 method for in-situ measurement of thermal transmittance (U) and regression-based monitoring approaches, such as co-heating test and energy signature, for heat load coefficient (HLC) and solar aperture (gA) estimation. In particular, we highlight the robustness and scalability of these monitoring techniques, considering relevant issues in current integrated engineer design perspective. These issues include, among others, the necessity of limiting the number of a sensors to be installed in buildings, the possibility of employing both experimental and real operation data and, finally, the possibility to automate and perform monitoring at multiple scales, from single components, to individual buildings, to building stock and cities

Net zero energy buildings: Expense or investment?

Abstract With the objective of reducing the heavy consumption of building sector, sustainable policies around the world promote, for the future, the construction of zero-energy or nearly zero-energy buildings. Higher investment in efficient technologies for energy saving and exploitation of renewables, however, can cause doubts about the real convenience of these "new generation" buildings. Based on the analysis of a case study under development, this paper demonstrates that a zero-energy building represents an affordable investment cost, especially if integrated with photovoltaics