1,720,966 research outputs found
A multi-objective optimization method for Smart Multi-Energy Systems: the case of a food industrial district in Italy
No full textTo maximize the environmental performance of the energy systems, a paradigm change towards the concept of Smart Multi Energy Systems (SMES) is needed. Optimal design and operation of SMES, which efficiently integrate different energy sources, vectors and needs, is intrinsically a multi-objective problem in terms of sustainability. In this study, we develop a decision support methodology based on performance indicators and Pareto multi-objective optimization, considering economic, environmental and energetic objective functions. In Part I of this research, the so-called conventional approach has been applied to an Italian food industrial district case study. SMES design combines RES and CCHP serving a cluster of firms through district energy distribution networks. Results show that SMES concept can really represent a major opportunity to industrial districts either from the sustainability and the competitiveness perspective. Research also suggests that some financial incentives should be studied so that the solution providing the largest energy saving and GHG emission reduction should become economically attractiv
Improving sustainability of energy intensive sectors through multi-objective models
Full text linkGlobal energy consumption and the related carbon dioxide emissions, which represent a large share of the overall anthropogenic greenhouse gas production, are continuously increasing since most of the energy needs are still provided by fossil fuels, thus constituting one of the main issues to be addressed in the climate change mitigation agenda. To achieve the Paris Agreement’s ambitious objectives, an energy transition towards sustainable energy systems based on the new smart energy system (SES) paradigm is needed, thus integrating the various energy sources, vectors and needs within the sectors (electricity, heating, cooling, transport, etc.).
However, optimal planning, design and management of complex integrated systems such as SES require to make use of proper decision support models based on multi-objective optimization techniques, since a sustainability analysis intrinsically involves environmental, economic and social aspects. Furthermore, a SES project involves several stakeholders, each driven by different and often conflicting objectives, which should be considered within such models, to remove some relevant barriers to the energy transition.
Focusing on the improvement of the sustainability of the energy-intensive sectors, the main objective of this thesis is thus the development of a decision support framework based on multi-objective optimization with the aim to support the decision makers in the planning, design and management of integrated smart energy systems, while considering the different involved stakeholders. The proposed model, composed by three main phases (namely investigative, design and decision-making), has been developed by steps via its application on case studies belonging to two main topics concerning the improvement of the sustainability performance of energy-intensive sectors through the implementation of the smart energy system concept. The first main topic is representative of the context of industrial districts and concerns their sustainable energy supply based on technical solutions specifically designed for cluster of firms, allowed by geographical proximity. The other one concerns the synergic integration between industrial and urban areas, through the recovery of waste energy from industrial processes to feed municipal district heating with a carbon-free source. The case studies have been selected, within the opportunities available in the local territorial context, not only because fit for the implementation of the smart energy system concept, but also due to their suitability for the implementation of different phases of the proposed decision support system (DSS)
Proposal for methodology to analyse operability of wine production plant in terms of power demand
No full textHow optimally selecting among internal and external opportunities for waste heat valorization: a case study from the steel industry
No full textConcerning waste heat recovery projects, especially in the energy-intensive industrial sectors, facility managers face indeed the challenge of making the optimal strategic choice within the different waste heat recovery options. In this context only the two energy recovery options based on a smart energy system approach, namely, power generation through an Organic Rankine Cycle (ORC) unit (both for self-consumption and grid selling) and the exploitation of the generated heat transfer fluid to feed an urban DH network. The economic objective represents the main driver, although environmental objectives are becoming increasingly important, also thanks to the rising value of green marketing. Indeed, when both the potential demand from external users and the opportunity to produce electricity represent attractive options, in order to allow the facility manager to select the most suitable waste heat recovery option and to decide which project to endorse, a deeper insight on the sustainability performances of each potential waste heat recovery solution is required. The developed DSS framework has then been applied adopting a facility manager’s perspective, with the aim to investigate the economic, energetic and environmental performances of different options for waste heat recovery exploitation, thus allowing a strategic decision making for the endorsement of the related investments. The model application provided useful suggestions on the optimal configuration of the energy recovery system, i.e. the selection of the most suitable option for the exploitation of the recovered energy, also taking into account the possible combination of different technologies, their optimal sizing and the definition of the operational strategy
Integrating industrial waste heat recovery into future sustainable Smart Energy Systems
No full textIn order to achieve the ambitious objectives set by the European Union for the climate and energy goals, a transition towards a future sustainable energy supply is needed. The integration of the huge potential for industrial waste heat recovery into Smart Energy System (SES) represents a main opportunity to accomplish these goals.
To successfully implement this strategy, the adoption of a system approach is required, since all the several stakeholders’ conflicting objectives should be considered. To address this challenge, in this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of a SES involving an industrial facility as the waste heat source and the neighborhood with different characteristics and activities (residential, commercial, and institutional) as potential users by a district heating network, in the typical European city brown field context.
The model has been applied to an Italian case study, analysing heat recovery from a steel casting facility to satisfy the heating needs of the southern part of Udine Municipality through the realization of a district heating (DH) network. Different DH layout scenarios have been analysed, to consider the connection of the main current and future city areas and different clients.
Energy system modelling has been implemented in MATLAB®, while the genetic multi-objective optimization has been performed by modeFRONTIER®, which allows to mark the Pareto front of solutions and the Multi Criteria Decision Making (MCDM) post processing analysis.
Results show that the developed model allows to properly select the DH network set of users and system layout to fully exploit the available waste energy, in particular how involving a large and heterogeneous basin of clients leads to remarkable economic and environmental performances. Design configurations such as the best compromise for thermal energy storage capacity are also provided. Moreover, the multi-objective model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenshi
Fostering sustainable micro district heating: A tool for biomass boiler design
Full text linkBiomass micro district heating networks can represent an opportunity for small communities to comply with European directives and achieve a sustainable energy supply. To foster their adoption, a facility management provider should rely on methods and tools to properly size the biomass energy conversion system, so that it can better suit the local community characteristics and requirements. To this end, the concepts of partial and complementary degrees-hour are introduced in order to partition energy flows along the whole heating season between the biomass boiler and the fossil fuel peak load one for each possible biomass boiler size. Basing on such division, the operational profile of the plant and related costs as well as carbon dioxide equivalent emissions can be evaluated. The methodology is embedded in a decision support tool, which provides the minimum cost solutions as well as the more environment-friendly ones. Results from the application of the tool to a real case of a mountain village are discussed
Supporting the current energy performance indicator for wineries to better monitor the overall production efficiency
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Planning and design of sustainable smart multi energy systems. The case of a food industrial district in Italy
No full textTo maximize the environmental performance of the energy systems, a paradigm change towards the concept of smart multi energy systems is needed. Optimal planning, design and operation of such energy systems, which efficiently integrate different energy sources, vectors and needs, is intrinsically a multi-objective problem in terms of sustainability. In this study, a decision support system based on perfor-mance indicators and Pareto multi-objective optimization is developed. System design combines renewable energy sources and combined cooling heat and power serving a cluster of firms through district energy distribution networks. Results show that the model enables the analysis of the trade-off between the different objective functions, allowing to identify the optimal energy systems layout through the selection of the proper size of the generation units. It also provides design directions such as the thermal energy storage capacity. The case study evidences that the smart energy systems concept can really represent a main opportunity to industrial districts both from the sustainability and the competitiveness perspective. Research also suggests that some financial incentives should be studied so that the solution providing the largest energy saving and carbon dioxide emission reduction could improve its economic attractiveness
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