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profit-based unit commitment models with price-responsive decision-dependent uncertainty

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第3期314卷 1052-1064页

作者： Lejeune, Miguel A. Dehghanian, Payman Ma, Wenbo George Washington Univ Washington DC 20052 USA

Highlighting the increasing importance of demand elasticity in electricity markets and its impact on the revenues of power generating companies, this paper proposes new profit-based unit commitment models that effectively capture the uncertainty in the willingness-to-pay the price set for the elastic demand. To develop a new revenue scheme for power generating companies, we use a coupling function to model the willingness-to-pay response of the elastic demand as a decision-dependent source of uncertainty. The coupling function reflects how power generating companies' pricing decisions may influence the market appeal (i.e., the buyer's willingness-to-pay) and how it affects their revenues. The optimization models are stochastic mixed-integer nonlinear problems with nonconvex continuous relaxations and are not amenable to a numerical solution in their original forms. We devise a convexification reformulation method and derive valid inequalities to strengthen the formulation. We propose a learning framework to parameterize the willingnessto-pay functions and the concept of the value of the decision-dependent solution to quantify the value of the uncertainty modeling approach. Numerical tests on power systems of various sizes, demand portfolios, and price elasticity levels show (i) how the valid inequalities speed up the solution process, (ii) the benefits of properly modeling decision-dependent uncertainty and demand elasticity, and (iii) how the incorporation of decision-dependent uncertainty in demand elasticity can change the power generating companies' decisions and revenue estimation.

关键词： Stochastic programming Price responsiveness profit-based unit commitment Willingness-to-pay Decision-dependent uncertainty

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A novel heuristic optimisation algorithm for solving profit-based unit commitment for thermal power generation with emission limitations

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INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY 2022年第6期41卷 675-698页

作者： Nazari, M. E. Fard, Z. Motamedi Golpayegan Univ Technol Elect Engn Golpayegan Iran

The profit-based unit commitment is a maximisation problem, which consists of the revenue minus costs subject to related constraints. However, with increasing concerns for the global warming, environmental limitations must also be observed. The objective of this study is to develop a novel heuristic optimisation algorithm for solving profit-based unit commitment, considering selling reserve, satisfying demand, and environmental emissions. Without emission limitations, the results show profits between 0.02% and 17.60% for profit-based unit commitment, as compared with other algorithms reported in the literature. As far as emission limitations are considered, the profits of 1.65-118.71% and emission cost reduction of 2.16-7.79% are achieved, as compared with those found in literature.

关键词： Deregulation electricity market emission optimisation profit-based unit commitment

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A mutual approach for profit-based unit commitment in deregulated power system integrated with renewable energy sources

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2021年第5期43卷 1102-1116页

作者： Anbazhagi, T. Asokan, K. AshokKumar, R. Annamalai Univ Dept Elect Engn Annamalainagar 608002 Tamil Nadu India Govt Coll Engn Dept Elect Engn Coimbatore Tamil Nadu India

This paper proposes a mutual technique for solving the profit-based unit commitment (PBUC) problem in deregulated power system integrated with wind power. The proposed mutual approach is the joined execution of different solution techniques and known by the non-dominated sorting of moth fly optimization (MFO) with levy flight search (NSMFLF) technique. In the proposed approach, the levy flight search and the traditional moth flame optimization looking conduct is prepared in parallel as for the objective function and update the conceivable combination of generation units. The objective function maximizes the profit of the generating companies as for the revenue and total fuel cost in light of the gauge estimations of power demand, price and reserve power. Here, the uncertainty events of the wind power are predicted by utilizing the artificial intelligence techniques. Thus, the system is ensured with the high utilization of wind power. Finally, the non-dominated sorting is performed to choose the optimal solution from the conceivable generated combinations. The optimal combination used to maximize the profit of the generating companies and solve the PBUC problem in light of the objective function. The proposed method is implemented in the matrix laboratory working stage and the outcomes are analyzed with the current strategies.

关键词： Wind power profit-based unit commitment deregulated power system moth fly optimization levy flight search

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profit-based unit commitment for a GENCO Equipped with Compressed Air Energy Storage and Concentrating Solar Power units

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ENERGIES 2021年第3期14卷 576-576页

作者： Gilvaei, Mostafa Nasouri Imani, Mahmood Hosseini Ghadi, Mojtaba Jabbari Li, Li Golrang, Anahita Univ Guilan Dept Elect Engn Rasht *** Iran Politecn Torino Dept Energy I-10129 Turin Italy Univ Technol Sydney Sch Elect & Data Engn Sydney NSW 2007 Australia NTNU Norwegian Univ Sci & Technol Dept Informat Secur & Commun Technol N-2815 Gjovik Norway

With the advent of restructuring in the power industry, the conventional unit commitment problem in power systems, involving the minimization of operation costs in a traditional vertically integrated system structure, has been transformed to the profit-based unit commitment (PBUC) approach, whereby generation companies (GENCOs) perform scheduling of the available production units with the aim of profit maximization. Generally, a GENCO solves the PBUC problem for participation in the day-ahead market (DAM) through determining the commitment and scheduling of fossil-fuel-based units to maximize their own profit according to a set of forecasted price and load data. This study presents a methodology to achieve optimal offering curves for a price-taker GENCO owning compressed air energy storage (CAES) and concentrating solar power (CSP) units, in addition to conventional thermal power plants. Various technical and physical constraints regarding the generation units are considered in the provided model. The proposed framework is mathematically described as a mixed-integer linear programming (MILP) problem, which is solved by using commercial software packages. Meanwhile, several cases are analyzed to evaluate the impacts of CAES and CSP units on the optimal solution of the PBUC problem. The achieved results demonstrate that incorporating the CAES and CSP units into the self-scheduling problem faced by the GENCO would increase its profitability in the DAM to a great extent.

关键词： compressed air energy storage concentrating solar power plant electricity markets generation companies profit-based unit commitment

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Modified Genetic Algorithm for the profit-based unit commitment Problem in Competitive Electricity Market

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ENERGIES 2023年第23期16卷 7751-7751页

作者： Nepomuceno, Lucas Santiago de Oliveira, Layon Mescolin da Silva Junior, Ivo Chaves de Oliveira, Edimar Jose de Paula, Arthur Neves Univ Fed Juiz de Fora Dept Elect Energy BR-36036900 Juiz De Fora Brazil

This article proposes a solution to the profit-based unit commitment (PBUC) problem to maximize the profit of a power generation company that owns thermal units and compressed air energy storage (CAES) systems, considering the Day-Ahead market. The proposed methodology is more realistic as it considers a mixed-integer nonlinear formulation of the PBUC. The problem is solved through two stages, with Stage 1 dedicated to obtaining the operational state of the generating units (On or Off) and the operation mode of the storage system (energy exchange: charging, discharging, idle). Stage 2 determines the dispatch of power from the thermoelectric units and the energy exchange in the storage system. The analysis of the system consisting of 20 thermoelectric units and three storage systems shows the efficiency of the proposed method in making decisions for the power generation company and is therefore promising for real-world applications.

关键词： profit-based unit commitment compressed air energy storage day-ahead energy market hybrid optimization genetic algorithm

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Binary whale optimization algorithm: a new metaheuristic approach for profit-based unit commitment problems in competitive electricity markets

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ENGINEERING OPTIMIZATION 2019年第3期51卷 369-389页

作者： Reddy, Srikanth K. Panwar, Lokesh Panigrahi, B. K. Kumar, Rajesh IIT Dept Elect Engn Delhi India IIT Ctr Energy Studies Delhi India MNIT Dept Elect Engn Jaipur Rajasthan India

This article presents a metaheuristic approach, the binary whale optimization algorithm (BWOA), to solve complex, constrained, non-convex, binary-nature profit-based unit commitment (PBUC) optimization problems of a price-taking generation company (GenCo) in the electricity market. To simulate the binary-nature PBUC problem, the continuous, real-value whale position/location is mapped into binary search space through various transfer functions. This article introduces three variants of BWOA using tangential hyperbolic, inverse tangent (arctan) and sigmoidal transfer functions. The effectiveness of the BWOA approaches is examined in test systems with different market mechanisms, i.e. an energy-only market, and energy and reserve market participation with different reserve payment methods. The simulation results are presented, discussed and compared with other existing approaches. The convergence characteristics, solution quality and consistency of the results across different BWOA variants are discussed. The superiority and statistical significance of the proposed approaches with respect to existing approaches is also presented.

关键词： Binary optimization profit-based unit commitment meta-heuristic optimization electricity market binary whale optimization

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profit based unit commitment using memetic binary differential evolution algorithm

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APPLIED SOFT COMPUTING 2019年 81卷 105502-000页

作者： Dhaliwal, Jatinder Singh Dhillon, J. S. St Longowal Inst Engn & Technol Elect & Instrumentat Engn Dept Longowal Punjab India

profit-based unit-commitment problem (PBUCP) is a notable combinatorial optimizing problem faced in the deregulated power industry. The PBUCP finds the best profitable solution by committing and scheduling the thermal generating units efficiently. To solve the PBUCP, a new memetic binary differential evolution algorithm is proposed which considers binary differential evolution (BDE) algorithm as global search operator to improve the exploration aspect and binary hill-climbing (BHC) algorithm as local search operator to improve the exploitation aspect. A binary differential evolution algorithm is introduced whereby a new mutation strategy is implemented. A novel BHC algorithm makes priority-based perturbations on unit's status to improve the global best solution searched by the BDE algorithm alone. A new excessive unit de-commitment strategy based on priority and total profit is also proposed. The power to committed units is allocated based on priority of units. The efficacy of algorithms has been researched on the PBUCP test systems comprising of 10-, 40- and 100-units over a time horizon. The outcomes of the proposed algorithms are compared with previously known best solutions. Simulated outcomes achieved by the proposed algorithms compete with the already reported algorithms to solve the PBUCP. Wilcoxon signed-rank test proves the predominance of the proposed algorithms statistically. (C) 2019 Elsevier B.V. All rights reserved.

关键词： profit-based unit commitment Memetic binary differential evolution Binary differential evolution Binary hill-climbing Memetic algorithm Priority methods

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A binary differential evolution based memetic algorithm to solve profit based unit commitment problem 8

A binary differential evolution based memetic algorithm to s...

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8th IEEE Power India International Conference (PIICON)

作者： Dhaliwal, Jatinder Singh Dhillon, Jaspreet Singh St Longowal Inst Engn & Technol Dept Elect & Instrumentat Engn Longowal Punjab India

ISBN: (纸本)9781538673393

unit commitment problem (UCP) and profit based unit commitment problem (PBUCP) are two combinatorial optimization problems with several constraints in the power system optimization research. In nowadays, the PBUCP becomes more dominant over the UCP due to restructuring in power industry. In recent years, many researchers have used various evolutionary algorithms to solve the multi-constrained PBUCP but differential evolution (DE) algorithm has received less consideration. A binary differential evolution (BDE) algorithm is introduced in the present research for solving the PBUCP. Further, to enhance the performance of the proposed BDE algorithm, a synergy of the BDE algorithm and a hill climbing local search optimizer (HCLSO) is used to solve the PBUCP. In the proposed synergy, BDE algorithm explores global aspect and a HCLSO method exploits local aspect. A HCLSO is proposed in this paper which makes perturbations in unit status based on a priority of units. A new de-commitment procedure is adopted to de-commit the needlessly committed units. The competency of the proposed BDE algorithm and BDE-HCLSO algorithm has been investigated on 10-units power system for 24 hours scheduling period. Results are justified by performing a comparison with the earlier reported algorithms employed to solve the PBUCP. Further, the simulation results demonstrate that BDE-HCLSO algorithm gives superior results over BDE algorithm.

关键词： profit-based unit commitment Binary differential evolution Hill climbing method Memetic algorithm

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profit-based unit commitment with security constraints and fair allocation of cost saving in industrial microgrids

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2013年第6期7卷 315-325页

作者： Derakhshandeh, Sayed Yaser Golshan, Mohammad Esmail Hamedani Masoum, Mohammad A. S. Isfahan Univ Technol Dept Elect & Comp Engn Esfahan Iran Curtin Univ Technol Dept Elect & Comp Engn Perth WA 6845 Australia

unit commitment (UC) in industrial microgrids (IMGs) is an important issue which has not received much attention in the literature. IMGs consist of many factories with distributed energy resources (DERs) and electric loads that heavily rely on combined heat and power systems. This study illustrates that UC in an IMG is not solely a profit-based UC or a security constrained UC (SCUC) problem. Therefore a new profit-based SCUC (PB-SCUC) formulation is proposed for IMGs that includes both microgrid (MG) security and factories constraints while utilising the generators waste heat to fulfill thermal requirements. The MG controller will solve the PB-SCUC problem to minimise the final production cost through maximisation of the profit by selling electricity to the upstream network. As each DER and boiler may have an individual owner, an approach based on game theory is also implemented to fairly allocate cost saving among factories participating in the generation process. Detailed simulation results are presented for an IMG consisting of 12 factories and analysed to show the effectiveness of the proposed approaches.

关键词： distributed power generation game theory industrial power systems power system economics power system measurement power system simulation profitability profit-based unit commitment security constraints fair allocation cost saving industrial microgrids distributed energy resources electric loads security constrained UC problem game theory

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

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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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