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An Efficient Approach to Schedule Generating Units of Combined Heat and Power (CHP) Generating System

IETE JOURNAL OF RESEARCH 2023年第2期69卷 975-986页

作者： Anand, Himanshu Thapar Inst Engn & Technol Dept Elect & Instrumentat Engn Patiala 147004 Punjab India

The unit commitment (UC) of thermal, heat and combined heat and power (CHP) is one of the critical issues of power systems which have an essential role in the economic performance of power systems. The mutual dependency of heat and power in the CHP unit has increased the complexity of the UC problem. In this research work, two modes of CHP units, extraction and back-pressure, have been undertaken, which offers flexibility as compared to each other. The added value of operating modes of CHP units in the UC problem is in the infancy stage. Afterwards, the optimization technique has been applied to solve the CHP UC problem. The binary particle swarm optimization is used to to update unit status, and to search optimal generation schedule priority list method has been employed. This method has been applied to solve economic and profit models of CHP-UC problem. One test system that has been undertaken consists of ten conventional thermal units, one CHP, and one heat only unit. The obtained results of economic and profit models reveal the importance of the CHP unit under different modes.

关键词： Global optimization priority list method profit-based unit commitment scheduling unit commitment

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Unit commitment based on modified firefly algorithm

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MEASUREMENT & CONTROL 2020年第3-4期53卷 320-327页

作者： Hussein, Balasim M. Jaber, Aqeel S. Univ Diyala Coll Engn Dept Power & Elect Machines Baqubah Iraq Mamoun Univ Coll Dept Elect Power Engn Tech Baghdad Iraq

Optimization technologies have drawn considerable interest in power system research. The success of an optimization process depends on the efficient selection of method and its parameters based on the problem to be solved. Firefly algorithm is a suitable method for power system operation scheduling. This paper presents a modified firefly algorithm to address unit commitment issues. Generally, two steps are involved in solving unit commitment problems. The first step determines the generating units to be operated, and the second step calculates the amount of demand-sharing among the units (obtained from the first step) to minimize the cost that corresponds to the load demand and constraints. In this work, the priority list method was used in the first step and the second step adopted the modified firefly algorithm. Ten generators were selected to test the proposed method, while the values of the cost function were regarded as criteria to gauge and compare the modified firefly algorithm with the classical firefly algorithm and particle swarm optimization algorithms. Results show that the proposed approach is more efficient than the other methods in terms of generator and error selections between load and generation.

关键词： Unit commitment modified firefly priority list method particle swarm optimization

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A Modified priority list-Based MILP method for Solving Large-Scale Unit Commitment Problems

A Modified Priority List-Based MILP Method for Solving Large...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Ke, Xinda Lu, Ning Wu, Di Kintner-Meyer, Michael N Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA Pacific NW Natl Lab Energy & Environm Directorate Richland WA 99352 USA

ISBN: (纸本)9781467380409

This paper presents a two-step modified priority list (MPL) based mixed integer linear programming (MILP) method for improving the computational speed of unit commitment (UC) programs while preserving optimality. In the first step, the heuristics of UC results for a given generation fleet are investigated to develop the MPL. A subset of the generators are determined to be online (committed) or offline (uncommitted) within a planning period (e.g., a week), based on the demand curve and generator priority list. Then, for generators whose on/off status is predetermined, the corresponding binary variables are removed from the MILP solving process. After this simplification, the remaining problem can be solved much faster using an off-the-shelf MILP solver, based on the branch-and-bound algorithm. Scale factors are used to adjust the tradeoff between solution speed and level of optimality. Simulation results show that the proposed method can significantly speed up the large-scale UC problem with negligible compromise in optimality by selecting appropriate scale factors.

关键词： Mixed integer linear programming power system scheduling priority list method unit commitment

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A Modified priority list-Based MILP method for Solving Large-Scale Unit Commitment Problems

A Modified Priority List-Based MILP Method for Solving Large...

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IEEE Power and Energy Society General Meeting

作者： Xinda Ke Ning Lu Di Wu Michael Kintner-Meyer Department of Electrical and Computer Engineering North Carolina State University Raleigh USA

ISBN: (纸本)9781467380416

关键词： Mixed integer linear programming power system scheduling priority list method unit commitment

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A Solution to Unit Commitment Problem Using Hybrid Ant System/priority list method

A Solution to Unit Commitment Problem Using Hybrid Ant Syste...

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2nd International Power and Energy Conference (PECon 2008)

作者： Chusanapiputt, Songsak Nualhong, Dulyatat Jantarang, Sujate Phoomvuthisarn, Sukumvit Mahanakom Univ Technol Fac Engn Dept Elect Power Engn Bangkok Thailand Elect Generating AuthorThailand Elect & Control Syst Engn Div Elect Engn Dept Bangkok Thailand Mahanakorn Univ Technol Fac Engn Dept Comp Engn & Satellite Res Ctr Bangkok Thailand Chulalongkorn Univ Ctr Excellence Elect Power Technol Bangkok Thailand

ISBN: (纸本)9781424424047

This paper presents a new method to solve unit commitment problem with operating constraints using a hybrid ant system/priority list method (HASP). The proposed methodology employs ant system in cooperating with the priority list method to find unit commitment solution as means of mutually combining the advantages of them in that a flexibility of the priority list method is reinforced, while AS algorithm can gain the benefit of using bias information for improving its performance during search process. The simulation results show that the proposed HASP is capable of obtaining satisfactory solution within reasonable computational time.

关键词： Unit commitment Ant system priority list method Evolutionary computation

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Fuzzy Logic Algorithm for Unit Commitment Problem

Fuzzy Logic Algorithm for Unit Commitment Problem

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International Conference on Control, Automation, Communication and Energy Conservation

作者： Kadam, D. P. Sonwane, P. M. Dhote, V. P. Kushare, B. E. Pune Univ KK Wagh Inst Engn Educ & Res Nasik Maharastra India KK Wagh Inst Engn Educ & Res Dept Elect Engn Nasik Maharastra India

ISBN: (纸本)9788184244397

The Unit Commitment Problem is to determine a minimal cost turn-on and turn-off schedule of a set of electrical power generating units to meet a load demand while satisfying a set of operational constraints. The production cost includes fuel, startup, shutdown, and no-load costs. Some of the operational constraints that must be taken into account include,[2] 1. The total power generated must meet the load demand plus system losses. 2. There must be enough spinning reserve to cover any shortfalls in generation. 3. The loading of each unit must be within its minimum and maximum allowable rating. 4. The minimum up and down times of each unit must be observed. The unit commitment is aimed at devising a proper generator commitment schedule for a power system over a period of one day to one week. The main objective of unit commitment is to minimize the total production cost over the study period & to satisfy the constraints imposed on the system such as power generation-load balance, spinning reserve, operating constraints, minimum up time & minimum down time, etc. Several conventional methods are available to solve the unit commitment problem. But all these methods need the exact mathematical model of the system & there may be a chance of getting stuck at the local optimum. This paper describes the application of fuzzy logic algorithm for determining short term commitment of thermal units in electrical power generation. The results obtained from fuzzy logic based approach are compared with the priority list method solution to unit commitment problem. The comparison fuzzy logic based approach are powerful tools for solving such highly non-linear, multi constrained optimization problems in electrical power systems.

关键词： Unit Commitment problem (UCP) Fuzzy Logic Algorithm priority list method

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