Evaluation of Performance Robustness of a Gas Turbine Cogeneration Plant Based on a Mixed-Integer Linear Model

2016 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Ryo Nakamura ◽  
Tetsuya Wakui ◽  
Yuji Shinano
Keyword(s):  
Linear Model ◽  
Energy Supply ◽  
Mixed Integer ◽  
Design Stage ◽  
Cogeneration Plant ◽  
Energy Demands ◽  
Integer Linear Model ◽  
Supply Systems ◽  
Energy Supply Systems ◽  
Performance Robustness

In designing energy supply systems, designers are requested to rationally determine equipment types, capacities, and numbers in consideration of equipment operational strategies corresponding to seasonal and hourly variations in energy demands. However, energy demands have some uncertainty at the design stage, and the energy demands which become certain at the operation stage may differ from those estimated at the design stage. Therefore, designers should consider that energy demands have some uncertainty, evaluate the performance robustness against the uncertainty, and design the systems to heighten the robustness. Especially, this issue is important for cogeneration plants, because their performances depend significantly on both heat and power demands. Although robust optimal design methods of energy supply systems under uncertain energy demands were developed, all of them are based on linear models for energy supply systems. However, it is still a hard challenge to develop a robust optimal design method even based on a mixed-integer linear model. At the first step for this challenge, in this paper, a method of evaluating the performance robustness of energy supply systems under uncertain energy demands is proposed based on a mixed-integer linear model. This problem is formulated as a bilevel mixed-integer linear programming one, and a sequential solution method is applied to solve it approximately by discretizing uncertain energy demands within their intervals. In addition, a hierarchical optimization method in consideration of the hierarchical relationship between design and operation variables is applied to solve large scale problems efficiently. Through a case study on a gas turbine cogeneration plant for district energy supply, the validity and effectiveness of the proposed method and features of the performance robustness of the plant are clarified.

Optimal Design of a Gas Turbine Cogeneration Plant by a Hierarchical Optimization Method With Parallel Computing

2018 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Yuji Shinano ◽  
Yuki Wakayama ◽  
Tetsuya Wakui
Keyword(s):  
Optimal Design ◽  
Energy Supply ◽  
Optimization Method ◽  
Optimal Operation ◽  
Hierarchical Optimization ◽  
Cogeneration Plant ◽  
Design Problems ◽  
Computation Efficiency ◽  
Supply Systems ◽  
Energy Supply Systems

To attain the highest performance of energy supply systems, it is necessary to rationally determine types, capacities, and numbers of equipment in consideration of their operational strategies corresponding to seasonal and hourly variations in energy demands. Mixed-integer linear programming (MILP) approaches have been applied widely to such optimal design problems. The authors have proposed a MILP method utilizing the hierarchical relationship between design and operation variables to solve the optimal design problems of energy supply systems efficiently. In addition, some strategies to enhance the computation efficiency have been adopted: bounding procedures at both the levels and ordering of the optimal operation problems at the lower level. In this paper, as an additional strategy to enhance the computation efficiency, parallel computing is adopted to solve multiple optimal operation problems in parallel at the lower level. In addition, the effectiveness of each and combinations of the strategies adopted previously and newly is investigated. This hierarchical optimization method is applied to an optimal design of a gas turbine cogeneration plant, and its validity and effectiveness are clarified through some case studies.

Robust Optimal Design of a Gas Turbine Cogeneration Plant Under Uncertain Energy Demands and Costs

2015 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Masashi Ohkura ◽  
Tetsuya Wakui
Keyword(s):  
Optimal Design ◽  
Gas Turbine ◽  
Energy Supply ◽  
Design Method ◽  
Performance Comparison ◽  
Energy Demands ◽  
Robust Optimal Design ◽  
Optimal Design Method ◽  
Supply Systems ◽  
Energy Supply Systems

In designing energy supply systems, designers should consider that energy demands and costs as parameters have some uncertainties, evaluate the robustness in system performances against the uncertainties, and design the systems rationally to heighten the robustness. A robust optimal design method of energy supply systems under only uncertain energy demands was revised so that it can be applied to systems with complex configurations and large numbers of periods for variations in energy demands. In addition, a method of comparing performances of two energy supply systems under only uncertain energy demands was proposed by utilizing a part of the revised robust optimal design method. In this paper, the revised robust optimal design method as well as the proposed performance comparison method are extended so that they can be applied to the robust optimal design and the performance comparison of energy supply systems under not only uncertain energy demands but also uncertain energy costs. Through a case study on a gas turbine cogeneration system for district energy supply, the validity and effectiveness of the extended optimal design method and features of the robust optimal design are clarified. In addition, the gas turbine cogeneration system is compared with a conventional energy supply system using the extended performance comparison method.

213 Optimal Operation of Energy Supply Systems Based on Prediction of Energy Demands

2004 ◽  
Vol 2004.79 (0) ◽  
pp. _2-27_-_2-28_
Author(s):  
Daisuke KUMASHIRO ◽  
Ryohei YOKOYAMA ◽  
Koichi ITO ◽  
Kazuyuki KAMIMURA ◽  
Tadahiko MATSUBA
Keyword(s):  
Energy Supply ◽  
Optimal Operation ◽  
Energy Demands ◽  
Supply Systems ◽  
Energy Supply Systems

Robust Optimal Operation of a Gas Turbine Cogeneration Plant Under Uncertain Energy Demands

2014 ◽  
Vol 137 (2) ◽  
Author(s):  
Ryohei Yokoyama ◽  
Masashi Ohkura ◽  
Tetsuya Wakui
Keyword(s):  
Gas Turbine ◽  
Energy Supply ◽  
Numerical Study ◽  
Optimization Method ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Cogeneration Plant ◽  
Co2 Emission Reduction ◽  
Operational Strategy ◽  
Energy Demands

Some optimal operation methods based on the mixed-integer linear programming (MILP) have been proposed to operate energy supply plants properly from the viewpoints of economics, energy saving, and CO2 emission reduction. However, most of the methods are effective only under certain energy demands. In operating an energy supply plant actually, it is necessary to determine the operational strategy properly based on predicted energy demands. In this case, realized energy demands may differ from the predicted ones. Therefore, it is necessary to determine the operational strategy so that it is robust against the uncertainty in energy demands. In this paper, an optimization method based on the MILP is proposed to conduct the robust optimal operation of energy supply plants under uncertain energy demands. The uncertainty in energy demands is expressed by their intervals. The operational strategy is determined to minimize the maximum regret in the operational cost under the uncertainty. In addition, a hierarchical relationship among operation modes and on/off states of equipment, energy demands, and energy flow rates of equipment is taken into account. First, a general formulation of a robust optimal operation problem is presented, which is followed by a general solution procedure. Then, in a numerical study, the proposed method is applied to a gas turbine cogeneration plant for district energy supply. Through the study, some features of the robust optimal operation are clarified, and the validity and effectiveness of the proposed method are ascertained.

A Multi-Stage Optimization Approach for Energy Supply Systems With Discrete Design Decisions

2019 ◽  
Author(s):  
S. Bruche ◽  
G. Tsatsaronis
Keyword(s):  
Energy Supply ◽  
Original Problem ◽  
Superior Performance ◽  
Mixed Integer ◽  
Optimization Models ◽  
Optimization Approach ◽  
Energy Supply System ◽  
Multi Stage ◽  
Supply Systems ◽  
Energy Supply Systems

Abstract Mixed integer linear programming is frequently applied to identify promising design solutions of energy supply systems. However, application-relevant optimization models are often associated with complicating model features, e.g. numerous discrete design candidates or a large time horizon of the optimization. So, even state-of-the-art solvers may be confronted with major challenges to find satisfying solutions within reasonable time. In this paper a systematic multi-stage optimization approach is proposed that is intended to support the available algorithms in solving these complex problems. The basic idea of the approach is the distribution of the original problem into two major levels. On the first level, promising design candidates are generated using simplified optimization models. These simplifications are achieved through time series aggregation and the relaxation of operational binary variables. In the second stage, the objective values of the design candidates for the original problem are determined. The division of the problem into two stages leads to a significant reduction in required optimization time but simultaneously leads to an uncertainty regarding the quality of the found solution. Therefore, in a subsequent step, it is checked whether the objective value is within an acceptable distance from the theoretically best solution. If this is not the case, the first two steps are iteratively repeated. The proposed multi-stage approach is applied to the optimization of an energy supply system located in Germany. The results show a superior performance regarding required optimization time over conventional methods.

scholarly journals Optimization of operation of energy supply systems with co-generation and absorption refrigeration

2012 ◽  
Vol 16 (suppl. 2) ◽  
pp. 409-422 ◽  
Author(s):  
Mirko Stojiljkovic ◽  
Bratislav Blagojevic ◽  
Goran Vuckovic ◽  
Marko Ignjatovic ◽  
Dejan Mitrovic
Keyword(s):  
Energy Supply ◽  
Electric Utility ◽  
Heat Pumps ◽  
Point Of View ◽  
Mixed Integer ◽  
System Control ◽  
Absorption Refrigeration ◽  
Simulation And Optimization ◽  
Supply Systems ◽  
Energy Supply Systems

Co-generation systems, together with absorption refrigeration and thermal storage, can result in substantial benefits from the economic, energy and environmental point of view. Optimization of operation of such systems is important as a component of the entire optimization process in pre-construction phases, but also for short-term energy production planning and system control. This paper proposes an approach for operational optimization of energy supply systems with small or medium scale co-generation, additional boilers and heat pumps, absorption and compression refrigeration, thermal energy storage and interconnection to the electric utility grid. In this case, the objective is to minimize annual costs related to the plant operation. The optimization problem is defined as mixed integer nonlinear and solved combining modern stochastic techniques: genetic algorithms and simulated annealing with linear programming using the object oriented ?ESO-MS? software solution for simulation and optimization of energy supply systems, developed as a part of this research. This approach is applied to optimize a hypothetical plant that might be used to supply a real residential settlement in Nis, Serbia. Results are compared to the ones obtained after transforming the problem to mixed 0-1 linear and applying the branch and bound method.

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