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Reliability constraint stochastic UC by considering the correlation of random variables with Copula theory

IET RENEWABLE POWER GENERATION 2019年第14期13卷 2587-2593页

作者： Yu, Dongmin Ghadimi, Noradin Northeast Elect Power Univ Dept Elect Engn Jilin 132012 Jilin Peoples R China Islamic Azad Univ Ardabil Branch Young Researchers & Elite Club Ardebil Iran

This essay performs a reliability constraint stochastic model for unit commitment problem by considering generation and transmission constraints with high wind penetration and volatility of load demands. This query is expressed as a MILP that is based on the linear direct current model. The proposed approach models uncertainty of wind generators output power, load demand fluctuations and stochastic elements outage of the system like generators and transmission lines. In this paper, stochastic interdependence between random variables like wind speed and load demand is recognized. To establish the probability distribution of these correlated random variables, Copula theory is applied. Correlation structure between wind speed of different locations and a group of loads existing in the same area is investigated and studied based on historical data. For representing these uncertainties in the stochastic unit commitment problem, possible scenarios are generated with Monte Carlo simulation method. The reliability constraints are utilized in each scenario to evaluate the feasibility of solutions from a reliability point. The introduced stochastic UC is executed on the RTS 96-bus test system. Numerical results demonstrate the advantages of implementing stochastic programming on the UC problem by taking into account the intermittent behavior of wind energy and load inconstancy.

关键词： power generation economics Monte Carlo methods stochastic programming linear programming power markets stochastic processes wind power plants power generation dispatch probability integer programming power system reliability power generation scheduling stochastic elements outage transmission lines stochastic interdependence wind speed correlated random variables Copula theory correlation structure stochastic UC problem reliability constraints reliability point introduced stochastic UC RTS-96-bus test system stochastic programming wind energy load inconstancy reliability constraint stochastic UC reliability constraint stochastic model unit commitment problem transmission constraints high wind penetration volatility mixed-integer linear programme linear direct current model approach models uncertainty wind generators output power load demand fluctuations

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Flexible power system operation accommodating uncertain wind power generation using transmission topology control: an improved linearised AC SCUC model

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第1期11卷 142-153页

作者： Nikoobakht, Ahmad Mardaneh, Mohammad Aghaei, Jamshid Guerrero-Mestre, Victoria Contreras, Javier Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Univ Castilla La Mancha ETS Ingenieros Ind E-13071 Ciudad Real Spain

Stochastic security constrained unit commitment (SSCUC) based on a DC model could be problematic in AC networks because the DC model is potentially inaccurate. However, solving SSCUC problems using an AC model is still very challenging. Accordingly, an improved linearised AC optimal power flow (ILACOPF) model is provided in order to optimise the SSCUC problem. The proposed SSCUC model includes a linear representation of network losses and reactive power and bus voltage magnitudes. Moreover, in this study, transmission switching (TS), a powerful tool for grid side flexibility, is introduced and utilised to facilitate the mitigation of the uncertainty of wind power generation. Nevertheless, solving the SSCUC problem with TS in a full AC network is still one of the challenges in practical implementation, which is facilitated by the proposed ILACOPF model. Additionally, the aim of this study is to develop a more accurate power flow model to obtain a more realistic SSCUC solution using TS. The proposed ILAC-SSCUC model using TS is formulated as a mixed-integer linear programme, being solved by the proposed effective solution approach based on Benders' decomposition. Numerical simulations on a 6-bus and IEEE 118-bus systems have been performed to evaluate the effectiveness of the method.

关键词： wind power plants power transmission control load flow control optimal control flexible power system operation uncertain wind power generation transmission topology control linearised AC SCUC model stochastic security constrained unit commitment SSCUC AC networks AC model improved linearised AC optimal power flow ILACOPF network losses reactive power bus voltage magnitudes transmission switching TS grid side flexibility ILACOPF model mixed-integer linear programme Benders decomposition

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Two-stage stochastic operation framework for optimal management of the water-energy-hub

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第22期13卷 5218-5228页

作者： Kavousi-Fard, Abdollah Su, Wencong Jin, Tao Papari, Behnaz Fuzhou Univ Dept Elect Engn Fuzhou 350116 Fujian Peoples R China Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Univ Michigan Dept Elect & Comp Engn Dearborn MI 48128 USA Florida State Univ Dept Elect & Comp Engn Tallahassee FL 32306 USA

This study proposes a bi-level stochastic framework to address optimal scheduling of energy hub (EH) in a pool-based short-term market considering electrical-thermal-water demands. EH acts as an independent price-maker producer in a day-ahead electricity market aiming to maximise its profit. The market settlement mechanism is constructed as the pay-at-market-clearing price (MCP), where each producer/consumer is paid at the MCP. The problem model is formulated as a bi-level optimisation approach in a stochastic environment, in which the upper level defines the profit maximisation of the proposed strategic producer, whereas the lower-level expresses the dispatch cost of the considered power grid. This results in a problem formulation with mathematical equilibrium constraints which is transformed into a new mixed-integer linear programme based on Karush-Kuhn-Tucker conditions. A stochastic framework based on unscented transform is developed to model the high uncertainties of EH water demand, EH thermal demand, EH electric demand, generators and loads submitted price to the market. The simulation results on the IEEE test system advocate the effectiveness and appropriate performance of the proposed strategic EH producer in the electricity market and its effect on the locational marginal prices of buses in a transmission-constrained market.

关键词： stochastic programming power grids optimisation power markets linear programming integer programming pricing MCP problem model bi-level optimisation approach stochastic environment profit maximisation strategic producer lower-level considered power grid problem formulation mathematical equilibrium constraints mixed-integer linear programme Karush-Kuhn-Tucker conditions EH water demand EH electric demand strategic EH producer transmission-constrained market stage stochastic operation framework optimal management water-EH bi-level stochastic framework optimal scheduling energy hub pool-based short-term market electrical-thermal-water demands independent price-maker producer day-ahead electricity market market settlement mechanism pay-at-market-clearing price

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Scheduling parallel serial-batch processing machines with incompatible job families, sequence-dependent setup times and arbitrary sizes

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2022年第17期60卷 5131-5154页

作者： Gahm, Christian Wahl, Stefan Tuma, Axel Univ Augsburg Chair Business Adm Prod & Supply Chain Management Augsburg Germany

The scheduling of (parallel) serial-batch processing machines is a task arising in many industrial sectors. In the metal-processing industry for instance, cutting operations are necessary to fabricate varying metal pieces out of large base slides. Here, the (cutting) jobs have individual, arbitrary base slide capacity requirements (sizes), individual processing times and due dates, and specific material requirements (i.e. each job belongs to one specific job family, whereby jobs of different families cannot be processed within the same batch and thus are incompatible). In addition, switching of base metal slides and material dependent adjustments of machine parameters cause sequence-dependent setup times. All these conditions need to be considered while minimising total weighted tardiness. For solving the scheduling problem, a mixed-integer program and several tailor-made construction heuristics (enhanced by local search mechanisms) are presented. The experimental results show that problem instances with up to five machines and 60 jobs can be tackled using the optimisation model. The experiments on small and large problem instances (with up to 400 jobs) show that a purposefully used batch capacity limitation improves the solution quality remarkably. Applying the best heuristic to the data of two real-world application cases shows its huge potential to increase delivery reliability.

关键词： Serial batching incompatible job families sequence-dependent setup times arbitrary sizes total weighted tardiness mixed-integer linear programme

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