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An effective hybrid decomposition approach to solve the network-constrained stochastic unit commitment problem in large-scale power systems

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EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION 2024年 12卷

作者： Lima, Ricardo M. Constante-Flores, GonzaloE. Conejo, Antonio J. Knio, Omar M. King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn Div Thuwal 239556900 Saudi Arabia Ohio State Univ Dept Elect & Comp Engn Southfield MI USA Ohio State Univ Dept Integrated Syst Engn Columbus OH USA Ohio State Univ Dept Elect & Comp Engn Columbus OH USA

We propose a novel hybrid method to solve the network-constrained stochastic unit commitment problem. We target realistic large-scale instances including hundreds of thermal generation units, thousands of transmission lines and nodes, and a large number of stochastic renewable generation units. This scheduling problem is formulated as a two-stage stochastic programming problem with continuous and binary variables in the first stage and only continuous variables in the second stage. We develop a hybrid solution method that decomposes the original problem into a master problem including unit commitment and dispatch decisions, and decomposed subproblems representing dispatch with transmission constraints per scenario. The proposed decomposition embeds a column-and-constraint generation step within the traditional Benders decomposition framework. The performance of the proposed decomposition technique is contrasted with the solution of the extensive form via branch-and-cut and Benders decomposition available in commercial solvers, and with conventional Benders decomposition variants. Our computational experiments show that the proposed method generates bounds of superior quality and finds solutions for instances where other approaches fail.

关键词： unit commitment Stochastic unit commitment network-constrained unit commitment Benders decomposition Constraint-and-column generation

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network-constrained unit commitment with RE uncertainty and PHES by using a binary artificial sheep algorithm

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ENERGY 2019年 189卷

作者： Li, Chaoshun Wang, Wenxiao Wang, Jinwen Chen, Deshu Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Peoples R China

With increasing share of renewable energy (RE) in power system, the unit commitment of hybrid power system have become more complicated due to network security demand and integration of pumped hydro energy storage (PHES). In this paper, a network-constrained unit commitment (NCUC) problem considering RE uncertainty and modulation of PHES has been raised. The NCUC model, with AC network security constraints and environmental constraints as well as traditional terms of constraints, is complicated to be solved. A novel Binary Artificial Sheep Algorithm (BASA) is used to solve the NCUC model. In the frame of BASA, the NCUC problem is decomposed as a master UC problem to determine start/stop status and economic load dispatch and a sub problem to check the AC network constraints. Based on the NCUC model and the solving method, the joint impacts of RE uncertainty and PHES have been studied. Test systems with different size have been adopted to verify the feasibility and effectiveness of the BASA. It is seen that the BASA has achieve an overall competitive performance on terms of operation cost and convergence speed by comparing it with existing methods. A modified IEEE 30-bus system with wind and photovoltaic power stations has been designed to reveal the impacts of RE and PHES. The results demonstrate that uncertainty of RE affects operation cost and security of the hybrid power system, and the adverse impact would aggravate as the RE forecasting error increase. The results also confirm the significant effect of PHES in restraining the negative influence of RE uncertainty. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： network-constrained unit commitment Renewable energy Binary artificial sheep algorithm Scenario analysis Pumped hydro energy system

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network-constrained unit commitment under significant wind penetration: A multistage robust approach with non-fixed recourse

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APPLIED ENERGY 2018年 232卷 489-503页

作者： Cobos, Noemi G. Arroyo, Jose M. Alguacil, Natalia Street, Alexandre Univ Castilla La Mancha Dept Ingn Elect Elect Automat & Comunicac ETSI Ind E-13071 Ciudad Real Spain Pontifical Catholic Univ Rio de Janeiro Dept Elect Engn Rio De Janeiro RJ Brazil

Generation scheduling in future smart grids will face significant uncertainty due to their considerable reliance on intermittent renewable-based generation such as wind power. Adaptive robust optimization provides a suitable framework to handle wind-related uncertainty in generation scheduling. However, available robust models feature relevant practical limitations including 1) the potential lack of physical implementability stemming from disregarding the nonanticipativity of the dispatch process, 2) the potential suboptimality or even infeasibility due to the use of fixed-recourse schemes, and 3) the intractable computational burden associated with a scenario-based counterpart. This paper presents a new multistage robust unit commitment approach with non-fixed recourse relying on the formulation of an alternative two-stage robust model. As a result, the least-cost generation schedule ensuring dispatch nonanticipativity is attained by solving a trilevel program of similar complexity as compared with available formulations neglecting this aspect. Moreover, an enhanced column-and-constraint generation algorithm is devised whereby lexicographic optimization is applied to accelerate the finite convergence to optimality. Numerical simulations including a practical out-of-sample validation procedure reveal that the proposed approach is 1) computationally effective even for a benchmark that is well beyond the capability of a recently published method, and 2) superior in terms of solution quality over existing two-stage robust models disregarding dispatch nonanticipativity.

关键词： Lexicographic optimization Multistage robust optimization network-constrained unit commitment Nonanticipativity Ramping capability Wind uncertainty

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network-constrained unit commitment Based on Reserve Models Fully Considering the Stochastic Characteristics of Wind Power

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ENERGIES 2018年第2期11卷

作者： Wang, Gang You, Dahai Zhang, Zhe Dai, Li Zou, Qi Liu, Hengwei Huazhong Univ Sci & Technol State Key Lab Adv Electromagnet Engn & Technol 1037 Luoyu Rd Wuhan 430074 Hubei Peoples R China

The existing optimization approaches regarding network-constrained unit commitment with large wind power integration face great difficulties in reconciling the two crucial but contradictory objectives: computational efficiency and the economy of the solutions. This paper proposes a new network-constrained unit commitment approach, which aims to better achieve these two objectives, by introducing newly proposed reserve models and simplified network constraints. This approach constructs the reserve models based on a sufficiently large number of stochastic wind power scenarios to fully and accurately capture the stochastic characteristics of wind power. These reserve models are directly incorporated into the traditional unit commitment formulation to simultaneously optimize the on/off decision variables and system reserve levels, therefore, this approach can comprehensively evaluate the costs and benefits of the scheduled reserves and thus produce very economical schedule. Meanwhile, these reserve models bring in very little computational burden because they simply consist of a small number of continuous variables and linear constraints. Besides, this approach can evaluate the impact of network congestion on the schedule by just introducing a small number of network constraints that are closely related to network congestion, i.e., the simplified network constraints, and thus concurrently ensures its high computational efficiency. Numerical results show that the proposed approach can produce more economical schedule than stochastic approach and deterministic approach but has similar computational efficiency as the deterministic approach.

关键词： network-constrained unit commitment wind power stochastic characteristics reserve models network congestion

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network-constrained unit commitment Incorporating Dynamic Thermal Rating and Transmission Line Switching 2

Network-Constrained Unit Commitment Incorporating Dynamic Th...

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2nd IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Li, Yanlin Xie, Kaigui Xiao, Ruosong Hu, Bo Chao, Huawei Kong, Dezhuang Chongqing Univ Sch Elect Engn Chongqing Peoples R China State Grid Corp China Chengdu Gaoxin Power Supply Co Chengdu Sichuan Peoples R China

ISBN: (纸本)9781538685495

The increasing penetration levels and stochastic characteristics of renewable energies and aging of transmission equipment bring potential negative impact on the economic and reliable operation of power grid. Therefore, the realistic and cost-effective choice for the utilities is to tap the potential of existing transmission infrastructures. Some smart grid technologies can leverage the potential transmission capacity and offer a flexible way for the power system operation. The dynamic thermal rating can evaluate the maximum transmission capacity of lines dynamically based on the environmental data. The optimal transmission switching can change the transmission topology and remove the transmission congestions. These technologies should be considered in the network-constrained unit commitment problem systematically to study their impact on the power system scheduling. However, the dynamic thermal rating incorporated network-constrained unit commitment studies are all based on the fixed transmission topology. So the overall influence of dynamic thermal rating and transmission line switching on network-constrained unit commitment has not been studied as yet. In this paper, the line switching technology and dynamic line rating according to multi-regional environmental information are incorporated in the network-constrained unit commitment framework. Case studies are implemented on a modified RTS-79 system. The simulation results verify the effectiveness of the coordination of two technologies in the reduction of generation cost and wind curtailment.

关键词： network-constrained unit commitment dynamic thermal rating transmission line switching

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A decomposition method for network-constrained unit commitment with AC power flow constraints

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ENERGY 2015年 88卷 595-603页

作者： Bai, Yang Zhong, Haiwang Xia, Qing Kang, Chongqing Xie, Le Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77840 USA

To meet the increasingly high requirement of smart grid operations, considering AC power flow constraints in the NCUC (network-constrained unit commitment) is of great significance in terms of both security and economy. This paper proposes a decomposition method to solve NCUC with AC power flow constraints. With conic approximations of the AC power flow equations, the master problem is formulated as a MISOCP (mixed integer second-order cone programming) model. The key advantage of this model is that the active power and reactive power are co-optimised, and the transmission losses are considered. With the AC optimal power flow model, the AC feasibility of the UC result of the master problem is checked in subproblems. If infeasibility is detected, feedback constraints are generated based on the sensitivity of bus voltages to a change in the unit reactive power generation. They are then introduced into the master problem in the next iteration until all AC violations are eliminated. A 6-bus system, a modified IEEE 30-bus system and the IEEE 118-bus system are used to validate the performance of the proposed method, which provides a satisfactory solution with approximately 44-fold greater computational efficiency. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： network-constrained unit commitment AC power flow constraints Decomposition Power flow sensitivity

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Hydrogen energy storage train scheduling with renewable generation and demand response

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JOURNAL OF ENERGY STORAGE 2025年 115卷

作者： Gupta, Pranda Prasanta Kalkhambkar, Vaiju Sharma, Kailash Chand Bhui, Pratyasa GLA Univ Dept Elect Engn Mathura Uttar Pradesh India Rajarambapu Inst Technol Dept Elect Engn Sangli Maharashtra India Dr B R Ambedkar Natl Inst Technol Dept Elect & Commun Engn Jalandhar India Indian Inst Technol Dharwad Dept Elect Engn Dharwad India

Large-scale penetration of renewable and hydrogen energy sources represents promising trends toward carbon emission reductions in the power sector. The storage systems such as the hydrogen energy storage (HES) Train will be crucial in responding to extreme grid events due to their agility and flexibility. This manuscript proposes a stochastic network constrained unit commitment (NCUC) considering HES Train with solar PV generation and demand response program (DRP). The DRP is introduced as a flexible option for dealing with energy market prices, providing sustainable options, and modifying the load profile for peak load shaving. The proposed model is applied to manage an HES Train that provides hydrogen energy services with low electricity prices. Moreover, the vector autoregressive moving average (VARMA) model is used in the stochastic optimization strategy to handle uncertain solar PV power. The model is formulated as a mixed integer linear programming (MILP) problem along with a generalized bender decomposition technique (GBD) to obtain the global optimal solution. A sensitivity analysis is presented to analyze solar power's ability to handle the high demand of the system operation. The proposed NCUC problem is simulated using GAMS software on an IEEE 24-bus system. HES Train scheduling with DRP and uncertain solar PV reduces the overall cost by 8.71 % as compared to the thermal-HES Train system.

关键词： Demand response program Hydrogen energy service providers Hydrogen energy storage train network-constrained unit commitment Solar power generation Mixed integer linear programming

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A holistic risk-aware coordinated framework for coupled hydrogen transport, LOHC storage, and rich renewable grid optimization

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APPLIED ENERGY 2025年 392卷

作者： Elsir, Mohamed Al-Sumaiti, Ameena Saad Khalifa Univ Coll Engn & Phys Sci Adv Power & Energy Ctr APEC Dept Elect EngnSmart OR Lab Abu Dhabi U Arab Emirates

The transition to sustainable energy systems is essential for achieving net-zero emissions and addressing climate change. While renewable energy sources (RES) are critical for this transition, their high penetration often leads to significant curtailment and grid stability challenges. Hydrogen energy systems (HES) offer a promising solution by providing grid flexibility and efficiently utilizing excess renewable energy. Although prior studies have explored HES components such as electrolyzers, hydrogen storage, and fuel cells, they often lack the level of detail and computational efficiency required for integration into large-scale optimization models. This paper addresses these gaps by proposing a novel, holistic framework that integrates highly detailed yet computationally efficient models of key HES components, such as proton exchange membrane fuel cells (PEMFCs), alkaline water electrolysis (AWE), and hydrogen transportation systems (HTS) leveraging liquid organic hydrogen carriers (LOHC), with advanced optimization techniques and risk-based demand response (DR) strategies. Advanced linearization techniques are developed for the AWE and PEMFC models to ensure computational efficiency without sacrificing accuracy, enabling scalable optimization of large-scale systems. The framework incorporates a two-stage stochastic programming model enhanced by a hidden Markov process (HMP) to address uncertainties in RES generation and electricity demand. By integrating HTS into the framework, this study highlights the logistical constraints of hydrogen delivery, ensuring a comprehensive approach to system optimization. Validated on the IEEE 24-bus reliability test system (RTS), the proposed framework demonstrates significant improvements in grid performance. Under deterministic conditions, it reduces RES curtailment by 99 %, lowers system costs by 11.2 %, and decreases emissions by 26.44 %. In stochastic settings, the risk-based DR strategy mitigates the impact of uncertainti

关键词： Hydrogen storage Proton exchange membrane fuel cells Alkaline water electrolysis Hidden Markov process Hydrogen transportation system network-constrained unit commitment

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Towards energy transition: A novel day-ahead operation scheduling strategy for demand response and hybrid energy storage systems in smart grid

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ENERGY 2024年 293卷

作者： Elsir, Mohamed Al-Sumaiti, Ameena Saad Moursi, Mohamed Shawky El Khalifa Univ Adv Power & Energy Ctr Elect Engn & Comp Sci Dept Abu Dhabi U Arab Emirates

Fossil fuel power plants continue to contribute significantly to carbon emissions, necessitating a transition towards cleaner energy sources. Despite the growing presence of renewables within the power systems, the incorporation of carbon capture technologies into the traditional thermal power plants holds great potential in emissions reduction. In this paper, the integration of renewable energy sources (RES) and coal-fired power generation units outfitted with carbon capture schemes is addressed. Multiple demand response (DR) programs and hydropower plants are strategically utilized to increase the power system flexibility. To effectively plan the day-ahead (DA) operation of the power system, a presumed market-clearing framework is adopted and modelled as a risk-constrained two-objective stochastic mixed-integer linear programming problem. The proposed framework helps to tackle the uncertainties related to RES and demand variations by employing a hidden Markovian process (HMP) technique. To simultaneously minimize the system's operational costs and CO2 emissions, an enhanced version of the augmented..-constraint method is employed. To prove its value, the proposed framework is devoted to the 24-bus IEEE reliability test system (IEEE-RTS). The system features substantial penetration of RES (exceeding 87% of peak load) and standard DR options capacities (less than 25% of peak load). The results show a 24% reduction in load peaks, an over 63% decrease in emissions, and a 17% reduction in the overall operation costs.

关键词： Energy transition Demand response network-constrained unit commitment Hidden Markovian process Risk-constrained two-objective stochastic mixed-integer linear programming

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A computational comparison of PTDF-based and phase-angle-based formulations of network constraints in distributed unit commitment

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ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS 2023年第2期14卷 515-540页

作者： Zhang, Shaobo Hedman, Kory W. Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85281 USA

In centralized approaches for the network-constrained unit commitment problem, the dominant way to formulate the linearized power flow problem is based on sensitivity factors such as power transfer distribution factors (PTDF formulation), instead of using phase-angle variables (b-theta formulation). The PTDF formulation enables various exploits of the problem structure, and those exploits grow in importance with the problem size. While these exploits exist for centralized approaches, new challenges arise for distributed approaches that are based on regional decomposition. In distributed approaches, additional constraints for tie lines need to be added to the PTDF formulation. At the same time, the advantages of the PTDF formulation diminish, since a distributed approach often solves smaller-sized unit commitment (UC) problems for each region in an iterative manner until convergence is achieved. This paper explores the performance of distributed algorithms for network-constrained UC problems based on two ways of formulating the linearized power flow problem for the power grid: PTDF-based and phase-angle-based. The performance of the two mathematical models is analyzed at different degrees of decomposition. Numerical simulations are performed to solve 24-h unit commitment problems for a Polish 3012-bus system. The results show that when the number of buses in each subproblem is large and binary constraints are enforced, the PTDF formulation performs better. The results also show that partitioning into more regions may take more iterations to reach desired solution quality, although each iteration takes less time. This trade-off need to be considered in the application of distributed unit commitment algorithms.

关键词： Distributed algorithms network-constrained unit commitment Power transfer distribution factors PTDF

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