Collaborative Modeling and Decision-Making for Complex Energy Systems

10.1142/8025 ◽  
2011 ◽  
Author(s):  
Ali Mostashari
Keyword(s):  
Decision Making ◽  
Energy Systems ◽  
Complex Energy ◽  
Collaborative Modeling

Generation of Complex Energy Systems by Combination of Elementary Processes

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
A. Toffolo ◽  
S. Rech ◽  
A. Lazzaretto
Keyword(s):  
Design Optimization ◽  
Ad Hoc ◽  
Energy Systems ◽  
Optimization Procedure ◽  
Thermodynamic Cycle ◽  
Energy System ◽  
Design Parameters ◽  
System Configuration ◽  
Complex Energy ◽  
Synthesis Design

The fundamental challenge in the synthesis/design optimization of energy systems is the definition of system configuration and design parameters. The traditional way to operate is to follow the previous experience, starting from the existing design solutions. A more advanced strategy consists in the preliminary identification of a superstructure that should include all the possible solutions to the synthesis/design optimization problem and in the selection of the system configuration starting from this superstructure through a design parameter optimization. This top–down approach cannot guarantee that all possible configurations could be predicted in advance and that all the configurations derived from the superstructure are feasible. To solve the general problem of the synthesis/design of complex energy systems, a new bottom–up methodology has been recently proposed by the authors, based on the original idea that the fundamental nucleus in the construction of any energy system configuration is the elementary thermodynamic cycle, composed only by the compression, heat transfer with hot and cold sources and expansion processes. So, any configuration can be built by generating, according to a rigorous set of rules, all the combinations of the elementary thermodynamic cycles operated by different working fluids that can be identified within the system, and selecting the best resulting configuration through an optimization procedure. In this paper, the main concepts and features of the methodology are deeply investigated to show, through different applications, how an artificial intelligence can generate system configurations of various complexity using preset logical rules without any “ad hoc” expertise.

Complex Energy Networks Optimization: Part II — Software Application to a Case Study

2020 ◽  
Author(s):  
M. A. Ancona ◽  
M. Bianchi ◽  
L. Branchini ◽  
A. De Pascale ◽  
F. Melino ◽  
...  
Keyword(s):  
Energy Production ◽  
Internal Combustion Engines ◽  
Energy Systems ◽  
Distribution Networks ◽  
Optimal Scheduling ◽  
Small Scale ◽  
Complex Energy ◽  
Energy Networks ◽  
Energy Network

Abstract In order to increase the exploitation of the renewable energy sources, the diffusion of the distributed generation systems is grown, leading to an increase in the complexity of the electrical, thermal, cooling and fuel energy distribution networks. With the main purpose of improving the overall energy conversion efficiency and reducing the greenhouse gas emissions associated to fossil fuel based production systems, the design and the management of these complex energy grids play a key role. In this context, an in-house developed software, called COMBO, presented and validated in the Part I of this study, has been applied to a case study in order to define the optimal scheduling of each generation system connected to a complex energy network. The software is based on a non-heuristic technique which considers all the possible combination of solutions, elaborating the optimal scheduling for each energy system by minimizing an objective function based on the evaluation of the total energy production cost and energy systems environmental impact. In particular, the software COMBO is applied to a case study represented by an existing small-scale complex energy network, with the main objective of optimizing the energy production mix and the complex energy networks yearly operation depending on the energy demand of the users. The electrical, thermal and cooling needs of the users are satisfied with a centralized energy production, by means of internal combustion engines, natural gas boilers, heat pumps, compression and absorption chillers. The optimal energy systems operation evaluated by the software COMBO will be compared to a Reference Case, representative of the current energy systems set-up, in order to highlight the environmental and economic benefits achievable with the proposed strategy.

Comprehensive Energy Systems Analysis Support Tools for Decision Making

2010 ◽  
pp. 272-295
Author(s):  
C. Cosmi ◽  
S. Di Leo ◽  
S. Loperte ◽  
F. Pietrapertosa ◽  
M. Salvia ◽  
...  
Keyword(s):  
Decision Making ◽  
Environmental Planning ◽  
Spatial Scales ◽  
Energy Systems ◽  
Cost Effective ◽  
Sustainable Resource Management ◽  
International Projects ◽  
Planning Methods ◽  
Decision Making Processes ◽  
Environment Agency

Sustainability of energy systems is a common priority that involves key issues such as security of energy supply, mitigation of environmental impacts - the energy sector is currently responsible for 80% of all EU greenhouse gas emissions (European Environment Agency, 2007), contributing heavily to the overall emissions of local air pollutants - and energy affordability. In this framework, energy planning and decision making processes can be supported at different stages and spatial scales (regional, national, pan-European, etc.) by the use of comprehensive models in order to manage the large complexity of energy systems and to define multi-objective strategies on the medium-long term. This Chapter is aimed to outline the value of model-based decision support systems in addressing current challenges aimed to carry out sustainable energy systems and to diffuse the use of strategic energy-environmental planning methods based on the use of partial equilibrium models. The proposed methodology, aimed to derive cost-effective strategies for a sustainable resource management, is based on the experiences gathered in the framework of the IEA-ETSAP program and under several national and international projects.

scholarly journals Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6223
Author(s):  
Bin Ye ◽  
Minhua Zhou ◽  
Dan Yan ◽  
Yin Li
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Energy Systems ◽  
Energy System ◽  
Energy Utilization ◽  
Target Area ◽  
Renewable Energy Systems ◽  
Multi Objective ◽  
Hybrid Renewable Energy Systems ◽  
Hybrid Renewable Energy

The application of renewable energy has become increasingly widespread worldwide because of its advantages of resource abundance and environmental friendliness. However, the deployment of hybrid renewable energy systems (HRESs) varies greatly from city to city due to large differences in economic endurance, social acceptance and renewable energy endowment. Urban policymakers thus face great challenges in promoting local clean renewable energy utilization. To address these issues, this paper proposes a combined multi-objective optimization method, and the specific process of this method is described as follows. The Hybrid Optimization Model for electric energy was first used to examine five different scenarios of renewable energy systems. Then, the Technique for Order Preference by Similarity to an Ideal Solution was applied using eleven comprehensive indicators to determine the best option for the target area using three different weights. To verify the feasibility of this method, Xiongan New District (XND) was selected as an example to illustrate the process of selecting the optimal HRES. The empirical results of simulation tools and multi-objective decision-making show that the Photovoltaic-Diesel-Battery off-grid energy system (option III) and PV-Diesel-Hydrogen-Battery off-grid energy system (option V) are two highly feasible schemes for an HRES in XND. The cost of energy for these two options is 0.203 and 0.209 $/kWh, respectively, and the carbon dioxide emissions are 14,473 t/yr and 345 t/yr, respectively. Our results provide a reference for policymakers in deploying an HRES in the XND area.

A new hybrid multi-criteria decision-making approach for developing integrated energy systems in industrial parks

2020 ◽  
Vol 270 ◽  
pp. 122119 ◽  
Author(s):  
Jiahang Yuan ◽  
Yun Li ◽  
Xinggang Luo ◽  
Zhongliang Zhang ◽  
Yuanpeng Ruan ◽  
...  
Keyword(s):  
Decision Making ◽  
Energy Systems ◽  
Multi Criteria Decision Making ◽  
Integrated Energy Systems ◽  
Industrial Parks

China's Energy and Resource Uses: Continuity and Change

1998 ◽  
Vol 156 ◽  
pp. 935-951 ◽  
Author(s):  
Vaclav Smil
Keyword(s):  
20Th Century ◽  
Energy Systems ◽  
Energy Resources ◽  
Complex Energy ◽  
Continuity And Change ◽  
Resource Endowment

Recent writings on China's achievements during the last quarter of the 20th century stress, almost without exception, the enormity of change. But, for both universal and particular reasons, this survey of the country's energy resources and uses will stress continuity as much as change. Taking the inertia of complex energy systems as the key universal given, the most important particular explanation lies in peculiarities of China's resource endowment.

Introduction: Energy Systems Modelling for Decision-Making

2015 ◽  
pp. 1-12 ◽  
Author(s):  
Alessandro Chiodi ◽  
George Giannakidis ◽  
Maryse Labriet ◽  
Brian Ó Gallachóir ◽  
GianCarlo Tosato
Keyword(s):  
Decision Making ◽  
Energy Systems ◽  
Systems Modelling

Thermoeconomic Diagnosis: Zooming Strategy Applied to Highly Complex Energy Systems: Part 1 — Detection and Localization of Anomalies

2002 ◽  
Author(s):  
Vittorio Verda ◽  
Luis Serra ◽  
Antonio Valero
Keyword(s):  
Inverse Problem ◽  
Complex Systems ◽  
Reference Conditions ◽  
Energy Systems ◽  
Combined Cycle ◽  
Operating Conditions ◽  
The Other ◽  
Complex Energy ◽  
Operational Diagnosis ◽  
Detection And Localization

This paper presents a summary of our most recent advances in Thermoeconomic Diagnosis, developed during the last three years [1–3], and how they can be integrated in a zooming strategy oriented towards the operational diagnosis of complex systems. In fact, this paper can be considered a continuation of the work presented at the International Conference ECOS’99 [4–6] in which the concepts of malfunction (intrinsic and induced) and dysfunction [7] were analyzed in detail. These concepts greatly facilitate and simplify the analysis, the understanding and the quantification of how the presence of an anomaly, or malfunction, affects the behavior of the other plant devices and of the whole system. However, what remains unresolved is the so-called inverse problem of diagnosing [3], i.e. given two states of the plant (actual and reference operating conditions), find the causes of deviation of the actual conditions with respect to the reference conditions. The present paper tackles this problem and describes significant advances in addressing how to locate the actual causes of malfunctions, based on the application of procedures for filtering induced effects that hide the real causes of degradation. In this paper a progressive zooming thermoeconomic diagnosis procedure, which allows one to concentrate the analysis in an ever more specific zone is described and applied to a combined cycle. In an accompanying paper (part 2 [8]) the accuracy of the diagnosis results is discussed, depending on choice of the thermoeconomic model.

Comparative study of posteriori decision-making methods when designing building integrated energy systems with multi-objectives

2019 ◽  
Vol 194 ◽  
pp. 123-139 ◽  
Author(s):  
Rui Jing ◽  
Meng Wang ◽  
Zhihui Zhang ◽  
Jian Liu ◽  
Hao Liang ◽  
...  
Keyword(s):  
Decision Making ◽  
Comparative Study ◽  
Energy Systems ◽  
Integrated Energy Systems
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