Stochastic Modeling and Uncertainty Analysis With Multi-Objective Optimization Strategies for the Synthesis/Design and Operation/Control of a PEMFC Fuel Processing Subsystem

2008 ◽  
Author(s):  
Kihyung Kim ◽  
Meng Wang ◽  
Michael R. von Spakovsky ◽  
Douglas J. Nelson
Keyword(s):  
Uncertainty Analysis ◽  
Large Scale ◽  
Operating Cost ◽  
Energy System ◽  
Cost Models ◽  
Multi Objective Optimization ◽  
Fuel Processing ◽  
Synthesis Design ◽  
Operation Control ◽  
Processing Subsystem

A stochastic modeling and uncertainty analysis methodology for energy system synthesis/design is proposed in this paper and applied to the development of the fuel processing subsystem (FPS) of a proton exchange membrane fuel cell (PEMFC) system. The FPS consists of a steam methane reformer, both high and low temperature water-gas shift reactors, a CO preferential oxidation reactor, a steam generator, a combustor, and several heat exchangers. For each component of the system, detailed thermodynamic, geometric, chemical kinetic, and cost models are developed and integrated into an overall model for the subsystem. Conventionally, in energy system synthesis/design, such models are treated deterministically, using a specific set of non-probabilistic input variable values that produce a specific set of non-probabilistic output variable values. Even though these input values, which include the specific load profile (i.e. electrical, thermal, and/or aerodynamic) for which the system or subsystem is synthesized/designed, can have significant uncertainties that inevitably propagate through the system to the outputs, such deterministic approaches are unable to quantify these uncertainties and their effect on the final synthesis/design and operation/control. This deficiency can, of course, be overcome by treating the inputs and outputs probabilistically. The difficulty with doing this, particularly when large-scale dynamic optimization with a large number of degrees of freedom is being used to determine the optimal synthesis/design and operation/control of the system, is that the traditional probabilistic approaches (e.g., Monte Carlo Method) are so computationally intensive that combined with large-scale optimization it renders the problem computationally intractable. This difficulty can be overcome by the use of approximate approaches such as the response sensitivity analysis (RSA) method based on Taylor series expansion. In this study, RSA is employed and developed by the authors for use with dynamic energy system optimization. Load profile and cost models are treated as probabilistic input values and uncertainties in output results investigated. The results for the uncertainty analysis applied to the optimization of the FPS synthesis/design and operation/control are compared with those found using a Monte Carlo approach with good results. In this paper, the FPS synthesis/design and operation optimization is treated as a multi-objective optimization problem to minimize the capital cost and operating cost simultaneously, and uncertainty effects on the optimization are assessed by taking uncertainties into account in the objectives and constraints. Optimization results show that there is little effect on the objective (the operating cost and capital cost), while the constraints (e.g., that on the CO concentration) can be significantly affected during the synthesis/design and operation/control optimization.

Dynamic Synthesis/Design and Operation/Control Optimization Under Uncertainty of a PEMFC System

2008 ◽  
Author(s):  
Kihyung Kim ◽  
Meng Wang ◽  
Michael R. von Spakovsky ◽  
Douglas J. Nelson
Keyword(s):  
Dynamic System ◽  
Alternative Energy ◽  
Large Scale ◽  
Proton Exchange ◽  
Optimization Under Uncertainty ◽  
Cost Models ◽  
System Synthesis ◽  
Control Optimization ◽  
Synthesis Design ◽  
Operation Control

Proton exchange membrane fuel cells (PEMFCs) are one of the leading candidates in alternative energy conversion devices for transportation, stationary, and portable power generation applications. Such systems with their own fuel conversion unit typically consist of several subsystems: a fuel processing subsystem, a fuel cell stack subsystem, a work recovery-air supply subsystem, and a power electronics subsystem. Since these subsystems have different physical characteristics, their integration into a single system/subsystem level unit make the problems of optimal dynamic system synthesis/design and operation/control highly complex. Thus, dynamic system/subsystem/component modeling and highly effective optimization strategies are required. Furthermore, uncertainties in the results of system synthesis/design and operation/control optimization can be affected by any number of sources of uncertainty such as the load profiles and cost models. These uncertainties can be taken into account by treating the problem probabilistically. The difficulty with doing this, particularly when large-scale dynamic optimization with a large number of degrees of freedom is being used to determine the optimal synthesis/design and operation/control of the system, is that the traditional probabilistic approaches (e.g., Monte Carlo Method) are so computationally intensive that combined with large-scale optimization it renders the problem computationally intractable. This difficulty can be overcome by the use of approximate approaches such as the response sensitivity analysis (RSA) method based on Taylor series expansion. Thus, in this paper, a stochastic modeling and uncertainty analysis methodology for energy system synthesis/design and operation/control which uses the RSA method is proposed and employed for calculating the uncertainties on the system outputs. Their effects on the synthesis/design and operation/control optimization of a 5kWe PEMFC system are assessed by taking the uncertainties into account in the objectives and constraints. It is shown that these uncertainties significantly affect the reliability of being able to meet certain constraints (e.g., that on the CO concentration) during the synthesis/design and operation/control optimization process. These and other results are presented.

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.

Multi- Versus Single-Level Dynamic Synthesis/Design and Operation/Control Optimizations of a PEMFC System

2008 ◽  
Author(s):  
Meng Wang ◽  
Kihyung Kim ◽  
Michael R. von Spakovsky ◽  
Douglas J. Nelson
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Proton Exchange ◽  
Optimization Techniques ◽  
Optimization Strategy ◽  
Single Level ◽  
Control Optimization ◽  
Synthesis Design ◽  
Gradient Based ◽  
Operation Control

As primary tools for the development of energy systems, optimization techniques have been studied for decades. However, for large-scale synthesis/design and operation/control optimization problems, it may turn out that it is impractical to solve the entire problem as a single optimization problem. In this paper, a multi-level optimization strategy, dynamic iterative local-global optimization (DILGO), is utilized for the synthesis/design and operation/control optimization of a 5 kWe PEMFC (Proton Exchange Membrane Fuel Cell) system. The strategy decomposes the system into three subsystems: a stack subsystem (SS), a fuel processing subsystem (FPS), and a work and air recovery subsystem (WRAS) and, thus, into three optimization sub-problems. To validate the decomposition strategy, the results are compared with a single-level dynamic optimization, in which the whole system is optimized together. In addition, for the purpose of comparison between different optimization algorithms, gradient-based optimization results are compared with those for a hybrid heuristic/gradient-based optimization algorithm.

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.

Synthesis, design and operation optimization of a combined cycle integrated energy system including optimization of the seasonal speed of a VLCC

2020 ◽  
pp. 147509022095401
Author(s):  
George N Sakalis ◽  
George J Tzortzis ◽  
Christos A Frangopoulos
Keyword(s):  
Net Present Value ◽  
Operating Cost ◽  
Energy System ◽  
Combined Cycle ◽  
Electricity Production ◽  
Steam Turbines ◽  
Operation Optimization ◽  
Synthesis Design ◽  
Integrated Energy System ◽  
Propulsion Power

The study of an integrated energy system is presented in this article that will cover all types of energy loads (mechanical, electrical, thermal) on a Very Large Crude Carrier (VLCC) with the maximum technically possible and economically feasible exploitation of fuel energy, thus reducing the operating cost and environmental footprint of the ship. There may be a large variety of configurations, design specifications and operating states that can cover the loads, making it necessary to apply synthesis, design and operation optimization of the system. The net present value of the system is selected as the objective function. For this purpose, a superconfiguration of the system is considered, which includes a number of Diesel engines adapted for possible operation in a combined Diesel and Rankine cycle, heat recovery steam generators producing high and low pressure steam, steam turbines that can contribute to propulsion and/or to the electricity production, an exhaust gas boiler and auxiliary boilers, as well as Diesel-generator sets. The synthesis of the system, that is, the components that will finally exist in the system, and their interconnections, the design specification of the components and the operating properties at characteristic operating states of the ship are not predetermined, but they are the result of formal, mathematical optimization. In addition, the speed of the vessel in each state, an important operational variable that has a crucial effect on the propulsion power and thus on the fuel consumption, is also determined by the optimization. The hull characteristics, the loading condition and the weather state are taken into account for the calculation of the propulsion power. For the optimization, proper models of the various components have been developed and the optimization problem is solved by addressing the three levels (synthesis, design, and operation) at a single computational step. The benefits of optimization, as well as the conditions that make the combined cycle economically justified, are demonstrated through an application example. The numerical solution is obtained for various values of fuel price and freight rate, so that the effects of these two crucial parameters on the optimal solution are assessed.

scholarly journals Operational optimization of a building-level integrated energy system considering additional potential benefits of energy storage

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Sai Liu ◽  
Cheng Zhou ◽  
Haomin Guo ◽  
Qingxin Shi ◽  
Tiancheng E. Song ◽  
...  
Keyword(s):  
Energy Storage ◽  
Operating Cost ◽  
Economic Cost ◽  
Energy System ◽  
Peak Shaving ◽  
Operational Optimization ◽  
Integrated Energy System ◽  
Potential Benefits ◽  
The Times ◽  
Building Level

AbstractAs a key component of an integrated energy system (IES), energy storage can effectively alleviate the problem of the times between energy production and consumption. Exploiting the benefits of energy storage can improve the competitiveness of multi-energy systems. This paper proposes a method for day-ahead operation optimization of a building-level integrated energy system (BIES) considering additional potential benefits of energy storage. Based on the characteristics of peak-shaving and valley-filling of energy storage, and further consideration of the changes in the system’s load and real-time electricity price, a model of additional potential benefits of energy storage is developed. Aiming at the lowest total operating cost, a bi-level optimal operational model for day-ahead operation of BIES is developed. A case analysis of different dispatch strategies verifies that the addition of the proposed battery scheduling strategy improves economic operation. The results demonstrate that the model can exploit energy storage’s potential, further optimize the power output of BIES and reduce the economic cost.

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