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.

Combination of Elementary Processes to Form a General Energy System Configuration

2017 ◽  
Author(s):  
A. Toffolo ◽  
S. Rech ◽  
A. Lazzaretto
Keyword(s):  
Heat Transfer ◽  
Design Optimization ◽  
Ad Hoc ◽  
Optimization Procedure ◽  
Thermodynamic Cycle ◽  
Energy System ◽  
Design Parameters ◽  
Engineering Practice ◽  
System Configuration ◽  
Synthesis Design

The fundamental challenge in the synthesis/design optimization of energy conversion systems is the definition of the system configuration and design parameters. The traditional way to operate in system engineering practice is to follow the previous experience, starting from design solutions that already exist. 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 really feasible. To solve the general problem of the synthesis/design of complex energy systems a new bottom-up methodology is proposed, based on the original idea that the fundamental nucleus in the construction of any energy system configuration is the elementary thermodynamic cycle (compression, heat transfer with the hot source, expansion, heat transfer with the cold source). 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 a deep analysis of the major features of the methodology is presented to show, through different examples of applications, how an artificial intelligence is able to generate system configurations of various complexity using preset logical rules without any “ad hoc” expertise.

scholarly journals Optimum Choice of Energy System Configuration and Storages for a Proper Match between Energy Conversion and Demands

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3957
Author(s):  
Andrea Lazzaretto ◽  
Andrea Toffolo
Keyword(s):  
Energy Conversion ◽  
Energy System ◽  
Distribution Networks ◽  
Design Parameters ◽  
System Configuration ◽  
Or Groups ◽  
Energy Conversion And Storage ◽  
Proper Design ◽  
And Storage ◽  
Distribution Grids

This Special Issue addresses the general problem of a proper match between the demands of energy users and the units for energy conversion and storage, by means of proper design and operation of the overall energy system configuration. The focus is either on systems including single plants or groups of plants, connected or not to one or more energy distribution networks. In both cases, the optimum design and operation involve decisions about thermodynamic processes, about the type, number, design parameters of components/plants, and storage capacities, and about mutual interconnections and the interconnections with the distribution grids. The problem is very wide, can be tackled with different methodologies and may have several, more or less valuable and complicated solutions. The twelve accepted papers certainly represent a good contribution to perceive its difficulty.

scholarly journals Development of Complex Energy Systems with Absorption Technology by Combining Elementary Processes

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 495 ◽  
Author(s):  
Kosuke Seki ◽  
Keisuke Takeshita ◽  
Yoshiharu Amano
Keyword(s):  
Alternative Energy ◽  
Energy Systems ◽  
Energy System ◽  
Operating Conditions ◽  
Optimal System ◽  
System Configuration ◽  
Bottom Up ◽  
Elementary Processes ◽  
Minimum Number ◽  
Synthesis Methodology

Optimal design of energy systems ultimately aims to develop a methodology to realize an energy system that utilizes available resources to generate maximum product with minimum components. For this aim, several researches attempt to decide the optimal system configuration as a problem of decomposing each energy system into primitive process elements. Then, they search the optimal combination sequentially from the minimum number of constituent elements. This paper proposes a bottom-up procedure to define and explore configurations by combining elementary processes for energy systems with absorption technology, which is widely applied as a heat driven technology and important for improving system’s energy efficiency and utilizing alternative energy resources. Two examples of application are presented to show the capability of the proposed methodology to find basic configurations that can generate the maximum product. The demonstration shows that the existing absorption systems, which would be calculated based on the experience of designers, could be derived by performing optimization with the synthesis methodology automatically under the simplified/idealized operating conditions. The proposed bottom-up methodology is significant for realizing an optimized absorption system. With this methodology, engineers will be able to predict all possible configurations and identify a simple yet feasible optimal system configuration.

scholarly journals Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

2014 ◽  
Vol 2 (2) ◽  
pp. 26-40 ◽  
Author(s):  
Miltiadis Alamaniotis ◽  
Vivek Agarwal
Keyword(s):  
Support Vector Regression ◽  
Intelligent Systems ◽  
Fuzzy Inference ◽  
Energy Systems ◽  
Energy System ◽  
Support Vector ◽  
Complex Energy ◽  
Anticipatory Control ◽  
Certainty Factor ◽  
Inference System

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. The proposed methodology implements an anticipatory system aiming at controlling energy systems in a robust way. Initially, a set of support vector regressors is adopted for making predictions over critical system parameters. The predicted values are used as input to a two-stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real-world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.

Design Optimization of a Rocker-Joint Silent Chain and Sprocket Drive Based on the Mesh Performance Indices

2012 ◽  
Vol 197 ◽  
pp. 104-109 ◽  
Author(s):  
Wen Yi Su ◽  
Yu Ren Wu
Keyword(s):  
Design Optimization ◽  
Design Procedure ◽  
Optimization Procedure ◽  
Design Parameters ◽  
Chain Drive ◽  
Performance Indices ◽  
Tooth Contact Analysis ◽  
Noise Vibration ◽  
Chain Drives ◽  
Novel Design

Improvement on noise, vibration and wear in silent chain drives is always an important research subject. However, design methods revealed in public are few because the silent chain shapes are variable and complex. A feasible design procedure is extremely required for improving transmission performance of chain drives. Therefore, a novel design optimization procedure for the rocker-joint silent (RJS) chain and sprocket drive is proposed in this paper. The mathematical models of geometry generation, tooth contact analysis and impact velocities at different mesh stages and chain raise amount in the RJS chain drive have been established. Besides, impact velocities and raise amount which may produce ill effects in the chine drive are incorporated as a multi-objective function to carry out the global minimization trying to find out the optimal design parameters for RJS chain drives. The single-objective optimization trends have also been verified with the previous references.

Optimal Synthesis/Design of a Pem Fuel Cell Cogeneration System for Multi-Unit Residential Applications–Application of a Decomposition Strategy

2004 ◽  
Vol 126 (1) ◽  
pp. 30-39 ◽  
Author(s):  
Borja Oyarza´bal ◽  
Michael R. von Spakovsky ◽  
Michael W. Ellis
Keyword(s):  
Fuel Cell ◽  
Design Optimization ◽  
Large Scale ◽  
Unit Cost ◽  
Pem Fuel Cell ◽  
Energy System ◽  
Cell System ◽  
Proton Exchange ◽  
Fuel Cell System ◽  
Synthesis Design

The application of a decomposition methodology to the synthesis/design optimization of a stationary cogeneration proton exchange membrane (PEM) fuel cell system for residential applications is the focus of this paper. Detailed thermodynamic, economic, and geometric models were developed to describe the operation and cost of the fuel processing sub-system and the fuel cell stack sub-system. Details of these models are given in an accompanying paper by the authors. In the present paper, the case is made for the usefulness and need of decomposition in large-scale optimization. The types of decomposition strategies considered are conceptual, time, and physical decomposition. Specific solution approaches to the latter, namely Local-Global Optimization (LGO) are outlined in the paper. Conceptual/time decomposition and physical decomposition using the LGO approach are applied to the fuel cell system. These techniques prove to be useful tools for simplifying the overall synthesis/design optimization problem of the fuel cell system. The results of the decomposed synthesis/design optimization indicate that this system is more economical for a relatively large cluster of residences (i.e. 50). Results also show that a unit cost of power production of less than 10 cents/kWh on an exergy basis requires the manufacture of more than 1500 fuel cell sub-system units per year. Finally, based on the off-design optimization results, the fuel cell system is unable by itself to satisfy the winter heat demands. Thus, the case is made for integrating the fuel cell system with another system, namely, a heat pump, to form what is called a total energy system.

Long-Term Degradation-Based Modeling and Optimization Framework

2018 ◽  
pp. 192-220
Author(s):  
Tarannom Parhizkar
Keyword(s):  
Energy Systems ◽  
Optimization Procedure ◽  
Energy System ◽  
Operating Conditions ◽  
Energy Prices ◽  
Ambient Conditions ◽  
Term Operation ◽  
Optimization Framework ◽  
Degradation Models

Energy systems degrade during long-term operation. Thus, performance profile of the system deteriorates over time. To optimize energy system parameters more reliably and accurately, it is necessary to consider degradation models of the system in the optimization procedure. In this chapter, a novel degradation-based optimization framework is proposed. This framework optimizes design and operation parameters of energy systems while accounting for the degradation effects on system performance. Therefore, this framework is beneficial for long-term analysis and optimization of energy systems. Validity and usefulness of the proposed methodology are demonstrated by optimizing the operating conditions and maintenance intervals of a gas turbine power plant, under different seasonal ambient conditions and energy prices. The case study results effectively meet all the positive expectations that are placed on the proposed degradation-based optimization framework.

Design of a Passively Morphing Ornithopter Wing Using a Novel Compliant Spine

2010 ◽  
Author(s):  
Yashwanth Tummala ◽  
Aimy Wissa ◽  
Mary Frecker ◽  
James E. Hubbard
Keyword(s):  
Drag Reduction ◽  
Design Optimization ◽  
Design Methodology ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Complete Analysis ◽  
Design Parameters ◽  
Flight Performance ◽  
Level Flight ◽  
Steady Level

A new scheme to design morphing ornithopter wings using a passive compliant spine is presented in this paper. The objective of this work is to optimize steady level flight performance of an ornithopter by passively implementing the Continuous Vortex Gait (CVG) which requires bending, twist and sweep coupling during the upstroke. An optimization problem is formulated to design a compliant spine for pre-specified bending, sweep, and twist deflections. As a first step to achieving these 3 DOF kinematics, a 1 DOF compliant spine is considered to produce a specified bending deflection during the upstroke for drag reduction while remaining stiff during the downstroke for increased lift. The effect of the relevant geometric design parameters, namely contact gap, angle, and hinge geometry, are considered and optimized to achieve the aforementioned kinematics for both single and multiple joints, which make up a compliant spine. Results presented include the spine design optimization procedure, as well as a complete analysis for a 1DOF compliant spine to illustrate the efficacy of the methodology. This compliant spine design methodology and optimization procedure will be used, in the future, to design the 3-DOF compliant spine for the passively morphing ornithopter.

scholarly journals Application of a Decomposition Strategy to the Optimal Synthesis/Design of a Fuel Cell Sub-System

2002 ◽  
Author(s):  
Borja Oyarza´bal ◽  
Michael R. von Spokovsky ◽  
Michael W. Ellis ◽  
J. Ricardo Mun˜oz ◽  
Nikolaos G. Georgopoulos
Keyword(s):  
Fuel Cell ◽  
Design Optimization ◽  
Large Scale ◽  
Unit Cost ◽  
Energy System ◽  
Economic Modeling ◽  
Synthesis Design ◽  
Decomposition Strategies ◽  
Commercial Applications ◽  
Scale Optimization

The application of a decomposition methodology to the synthesis/design optimization of a stationary cogeneration fuel cell sub-system for residential/commercial applications is the focus of this paper. To accomplish this, a number of different configurations for the fuel cell sub-system were considered. The most promising candidate configuration, which combines features of different configurations found in the literature, is chosen for detailed thermodynamic, geometric, and economic modeling both at design and off-design. The case is then made for the usefulness and need of decomposition in large-scale optimization. The types of decomposition strategies considered are conceptual/time and physical decomposition. Specific solution approaches to the latter, namely Local-Global Optimization (LGO) are outlined in the paper. Conceptual/time decomposition and physical decomposition using the LGO approach are applied to the fuel cell sub-system. These techniques prove to be useful tools for simplifying the overall synthesis/design optimization problem of the fuel cell sub-system. Finally, the results of the decomposed synthesis/design optimization of the fuel cell sub-system indicate that this sub-system is more economical for a relatively large cluster of residences (i.e. 50). To achieve a unit cost of power production of less than 10 cents/kWh on an exergy basis requires the manufacture of more than 1500 fuel cell sub-system units per year. In addition, based on the off-design optimization results, the fuel cell sub-system is unable by itself to satisfy the winter heat demands. Thus, the case is made for integrating the fuel cell sub-system with another sub-system, namely, a heat pump, to form what is called a total energy system.

scholarly journals Optimized Design of a Novel Hydraulic Propeller Turbine for Low Heads

Designs ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 20
Author(s):  
Dario Barsi ◽  
Marina Ubaldi ◽  
Pietro Zunino ◽  
Robert Fink
Keyword(s):  
Design Optimization ◽  
High Efficiency ◽  
Single Point ◽  
Design Procedure ◽  
Optimization Procedure ◽  
Design Parameters ◽  
Geometrical Parameters ◽  
Practical Case ◽  
Optimized Design ◽  
Starting Point

In the present paper, an optimized design procedure capable of providing the geometry of a high efficiency compact hydraulic propeller turbine for low head is proposed and developed. The turbine preliminary design is based on fundamental turbomachinery mean-line equations and on the employment of statistical correlations, which relate the main geometrical parameters to the fundamental design parameters. The first obtained geometry represents the starting point of an automated aerodynamic single point optimization procedure based on a genetic algorithm generating and updating a wide database of turbine geometries. The approach employs a three-dimensional (3D) Reynolds averaged Navier–Stokes (RANS) solver for the construction of the corresponding database of performance. A meta-model, such as an artificial neural network (ANN), is used to speed up the design optimization process. The procedure has been applied on the practical case of a novel simplified hydraulic propeller turbine prototype for very low heads. The adopted design optimization procedure is able to modify the turbine blade and vane geometries in order to achieve automatically the targeted net head and the maximum for the total to total internal efficiency once diameter, mass flow rate, and rotational speed are assigned.

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