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Sub-Symmetry-Breaking Inequalities for ILP with Structured Symmetry 1

20th International Conference on Integer Programming and Combinatorial Optimization (IPCO)

作者： Bendotti, Pascale Fouilhoux, Pierre Rottner, Cecile Sorbonne Univ CNRS 7606 LIP6 Paris France EDF R&D Palaiseau France

ISBN: (数字)9783030179533

ISBN: (纸本)9783030179533;9783030179526

We consider integer linear programs whose solutions are binary matrices and whose (sub-)symmetry groups are symmetric groups acting on (sub-)columns. We propose a framework to build (sub-)symmetry-breaking inequalities for such programs, by introducing one additional variable per sub-symmetry group considered. The proposed framework is applied to derive inequalities breaking both symmetries and sub-symmetries in the graph coloring problem and in the ramp constrained min-up/min-down unit commitment problem.

关键词： Integer linear programming (Sub)-symmetry breaking inequalities Graph Coloring problem unit commitment problem

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unit commitment by Genetic Evolving Ant Colony Optimization

Unit Commitment by Genetic Evolving Ant Colony Optimization

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World Congress on Nature and Biologically Inspired Computing

作者： Vaisakh, K. Srinivas, L. R. Andhra Univ AU Coll Engn Dept Elect Engn Visakhapatnam 530003 Andhra Pradesh India SRKR Engn Coll Dept Elect & Elect Engn Bhimavaram 534204 Andhra Pradesh India

ISBN: (纸本)9781424450534

Ant Colony Optimization (ACO) is more suitable for combinatorial optimization problems. This paper proposes Genetic Evolving Ant Colony Optimization (EACO) method for solving unit commitment (UC) problem. The EACO employs Genetic Algorithm (GA) for finding optimal set of ACO parameters, while ACO solves the UC problem. problem formulation takes into consideration the minimum up and down time constraints, start up cost, shut-down cost, spinning reserve, ramp rate constraints and generation limit constraints. The feasibility of the proposed approach is demonstrated for 4 and 10-unit systems. The test results are encouraging and are compared with those obtained by other methods.

关键词： Evolving ant colony optimization unit commitment problem pheromone matrix genetic algorithm

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Operation Planning for High unit Utilization in Distributed Energy Management System with Storage Devices

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ELECTRICAL ENGINEERING IN JAPAN 2017年第2期199卷 33-46页

作者： Shibata, Kodai Miyamoto, Toshiyuki Kitamura, Shoichi Mori, Kazuyuki Izui, Yoshio Osaka Univ Grad Sch Engn Suita Osaka Japan Osaka Univ Grad Sch Engn Elect Engn Suita Osaka Japan Mitsubishi Electr Corp Adv Technol R&D Ctr Tokyo Japan

Suppose a special district (group) that is composed of multiple companies (agents) imposed energy demand. We have proposed a distributed energy management system (DEMS) that optimizes energy consumption of a group through energy trading in the group. In this paper, we propose an efficient operation planning method for DEMS with storage device. At first, we formulate the optimization problem for agents. Second, we propose a method to search a unit commitment state that depends on group composition. We confirmed that the proposed method enables efficient use of generators in groups. (C) 2017 Wiley Periodicals, Inc.

关键词： distributed energy management system Walras auction storage battery unit commitment problem

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Uncertainty in unit commitment in Power Systems: A Review of Models, Methods, and Applications

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ENERGIES 2021年第20期14卷

作者： Hong, Ying-Yi Apolinario, Gerard Francesco DG. Chung Yuan Christian Univ Dept Elect Engn Taoyuan 32023 Taiwan Technol Inst Philippines Elect Engn Dept Manila 1001 Philippines

The unit commitment problem (UCP) is one of the key and fundamental concerns in the operation, monitoring, and control of power systems. Uncertainty management in a UCP has been of great interest to both operators and researchers. The uncertainties that are considered in a UCP can be classified as technical (outages, forecast errors, and plugin electric vehicle (PEV) penetration), economic (electricity prices), and "epidemics, pandemics, and disasters " (techno-socio-economic). Various methods have been developed to model the uncertainties of these parameters, such as stochastic programming, probabilistic methods, chance-constrained programming (CCP), robust optimization, risk-based optimization, the hierarchical scheduling strategy, and information gap decision theory. This paper reviews methods of uncertainty management, parameter modeling, simulation tools, and test systems.

关键词： chance-constrained programming hierarchical scheduling strategy information gap decision theory probabilistic methods risk-based optimization robust optimization stochastic programming unit commitment problem uncertainty

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Assessment of the required running capacity in weakly interconnected insular power systems

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ELECTRIC POWER SYSTEMS RESEARCH 2023年 221卷

作者： Paspatis, A. G. Fiorentzis, K. Katsigiannis, I. Tsikalakis, A. Karapidakis, E. S. Thalassinakis, E. J. Gigantidou, A. Hellen Mediterranean Univ Dept Elect & Comp Engn Iraklion Greece HEDNO SA Isl Network Operat Dept Iraklion Greece

In this paper a methodology is proposed for assessing the required running capacity in weakly interconnected insular power systems. This information is of crucial importance for system operators, when deciding the operation policy of the interconnected power system. In the proposed methodology, a probabilistic analysis is initially employed to identify probable extreme stress conditions of the local oil-fired units of the insular power system and the interconnector. Then, based on the unit commitment guidelines and the technical limitations of the interconnector, a power flow analysis is proposed to be followed. Hence, useful insights can be obtained for the system operators, regarding the required running capacity and the interconnection operation. To validate the proposed methodology's efficacy, the case of the interconnection of Crete with the Hellenic Transmission System is considered. The presented case study follows the recently proposed guidelines for unit commitment in the power system of Crete following to the interconnection, while considering the extreme scenarios derived from the probabilistic analysis. The existing oil-fired units that will be required to remain available for dispatching after the operation of the AC interconnector are identified, while the interconnection operation is characterized.

关键词： Insular power systems Transmission planning Renewable energy sources Interconnection Power flow analysis Power reserves unit commitment problem Power system reliability

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A Thermal unit commitment Approach Using an Improved Quantum Evolutionary Algorithm

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2009年第7期37卷 770-786页

作者： Jeong, Yun-Won Park, Jong-Bae Shin, Joong-Rin Lee, Kwang Y. Konkuk Univ Dept Elect Engn Seoul 143701 South Korea Baylor Univ Dept Elect & Comp Engn Waco TX 76798 USA

This article presents a new approach for solving unit commitment problems using a quantum-inspired evolutionary algorithm. The unit commitment problem is a complicated non-linear and mixed-integer combinatorial optimization problem with heavy constraints. This article proposes an improved quantum evolutionary algorithm to effectively solve unit commitment problems. The quantum-inspired evolutionary algorithm is considered a novel evolutionary algorithm inspired by quantum computing, which is based on the concept and principles of quantum computing such as the quantum bit and the superposition of states. The proposed improved quantum evolutionary algorithm adopts both the simplified rotation gate and the decreasing rotation angle approach in order to improve the convergence performance of the conventional quantum-inspired evolutionary algorithm. The suggested simplified rotation gate can determine the rotation angle without a lookup table, while the conventional rotation gate requires a predefined lookup table to determine the rotation angle. In addition, the proposed decreasing rotation angle approach provides the linearly decreasing magnitude of rotation angle along the iteration. Furthermore, this article includes heuristic-based constraint treatment techniques to deal with the minimum up/down time and spinning reserve constraints in unit commitment problems. Since the excessive spinning reserve can incur high operation costs, the unit de-commitment strategy is also introduced to improve the solution quality. To demons trate the performance of the proposed improved quantum evolutionary algorithm, it is applied to the large-scale power systems of upto 100-unit with 24-hr demand horizon.

关键词： combinatorial optimization unit commitment problem improved quantum evolutionary algorithm constraint treatment technique

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Comparative Analysis of Economic Viability with Distributed Energy Resources on unit commitment

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2016年第14期44卷 1588-1607页

作者： Govardhan, Manisha Roy, Ranjit Sardar Vallabhbhai Natl Inst Technol Dept Elect Engn Surat 395007 Gujarat India

Classic unit commitment is the important and challenging task of allocating generating units subject to basic constraints over a scheduled time horizon to obtain the least generation cost. Penetration of distributed energy resources in modern power systems makes generation planning more complex. This article presents the individual and combined effect of three distributed energy resources, namely wind power generator as a renewable energy source, plug-in electric vehicles, and emergency demand response program on unit commitment. The inconsistent nature of wind speed and wind power is characterized by the Weibull probability distribution function considering overestimation and underestimation costs of stochastic wind power. The comprehensive comparative analysis of the economic viability on unit commitment is carried out to minimize the total cost of the entire system. To obtain the optimum solution, a modified teaching-learning-based optimization algorithm is used. The IEEE standard ten-unit test system is used for this study. To validate the efficacy of the modified teaching-learning-based optimization algorithm, a 26-unit reliability test system is also considered. It is found that the collective effect of wind power generator, plug-in electric vehicles, and emergency demand response program on unit commitment provides significant reduction in the total cost.

关键词： distributed energy resources emergency demand response program modified teaching-learning-based optimization algorithm plug-in electric vehicles teaching-learning based optimization algorithm unit commitment problem Weibull probability distribution function

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Differential evolution algorithm for solving unit commitment with ramp constraints

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2008年第8期36卷 771-787页

作者： Patra, S. Goswami, S. K. Goswami, B. Assam Engn Coll Dept Elect Engn Gauhati 781013 Assam India Jadavpur Univ Kolkata W Bengal India

This article proposes a differential evolution algorithm to solve the unit commitment problem with ramp constraints. Two implementations of the proposed algorithm-the first one using the binary code, and the second one using the integer code-have been developed. Both of these implementations have been found to converge to the same optimum solution requiring a different number of generations and a different CPU time. The proposed algorithm shows competitive performance with the best of the similar methods proposed earlier.

关键词： binary differential evolution unit commitment problem binary and integer coded implementations

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Economic Dispatch Cost Reduction in Box-based Robust unit commitment ⁎

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IFAC-PapersOnLine 2020年第2期53卷 13248-13253页

作者： Youngchae Cho Takayuki Ishizaki Nacim Ramdani Jun-ichi Imura Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan Univ. Oreans INSA-CVL PRISME EA 4229 F45072 Orleans France

This paper proposes a box expanding method to reduce the economic dispatch (ED) cost in the box-based robust unit commitment model (BUC). As a non-anticipative robust unit commitment model for a power system under demand uncertainty, BUC co-optimizes the commitment schedule and the feasible set of the ED problem to minimize the total operating cost for the worst-case realization in a set of possible demand scenarios; the feasible set of the ED problem is modeled as a box to enable the non-anticipative real-time dispatch. Meanwhile, as BUC considers the worst-case total operating cost, the actual total operating cost may be unnecessarily high. In this paper, the box feasible set of the ED problem in BUC is expanded to a larger one via multi-objective optimization with a no-preference method. The expanded box forms a new feasible set of the ED problem, which increases the chance of reducing the actual ED cost and thus the actual total operating cost. Simulation results using 5-, 14-, and 30-bus test systems demonstrate the effectiveness and generality of the proposed method.

关键词： optimization problems power systems stochastic programming uncertainty unit commitment problem

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unit commitment for a Power System with Pumped Storage units

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IFAC Proceedings Volumes 1997年第17期30卷 545-550页

作者： Michael P. Walsh Mark J. O'Malley Department of Electrical and Electronic Engineering University College Dublin Belfield Dublin 4 Ireland

The spinning reserve constraint presents a significant challenge in smaller power *** is common to have the reserve required specified at multiple times following a contingency. In this paper some operating modes of a pumped storage unit designed to provide reserve are described. A novel neural network technique for the unit commitment problem is also presented. This technique is ideally suited to consider all the operating modes of a pumped storage unit. Results illustrate the circumstances in which the various pumped storage modes may be useful.

关键词： Hydrothermal power systems unit commitment problem Neural networks

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