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Two-stage robust power cost minimization in a natural gas compressor station

Petroleum Science 2022年第1期19卷 409-428页

作者： Yize Meng Ruoran chen Keren Zhang Tianhu Deng Department of Industrial Engineering Tsinghua UniversityBeijing100084China

Optimal operation of a compressor station is important since it accounts for 25%to 50%of a company’s total operating *** short-term management of a compressor station,handling demand uncertainty is important yet *** studies either require precise information about the distribution of uncertain parameters or greatly simplify the compressor *** build a two-stage robust optimization framework of power cost minimization in a natural gas compressor station with nonidentical *** the first stage,decision variables are the ON/OFF state of each compressor and discharge *** worst-case cost of the second stage is incorporated in the first *** decision variables feasibility is discussed and proper feasibility cuts are also proposed for the first *** employ a piece-wise approximation and propose accelerate *** numerical results highlight two advantages of robust approach when managing uncertainty in practical settings:(1)the feasibility of first-stage decision can be increased by up to 45%,and(2)the worst-case cost can be reduced by up to 25%compared with stochastic programming ***,our numerical experiments show that the designed accelerate algorithm has time improvements of 1518.9%on average(3785.9%at maximum).

关键词： Natural gas Single station power minimization Nonconvex robust optimization c&cg algorithm

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Distributionally Robust Optimal Dispatch of Offshore Wind Farm cluster connected by VSc-MTDc considering Wind Speed correlation

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cSEE Journal of Power and Energy Systems 2023年第3期9卷 1021-1035页

作者： Xiangyong Feng Shunjiang Lin Wanbin Liu Weikun Liang Mingbo Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China Guangdong Key Laboratory of Clean Energy Technology South China University of TechnologyGuangzhou 511458China

Multi-terminal voltage source converter-based highvoltage direct current(VSc-MTDc)transmission technology has become an important mode for connecting adjacent offshore wind farms(OWFs)to power *** dispatch of an OWF cluster connected by the VSc-MTDc can improve economic operation under the uncertainty of wind speeds.A two-stage distributionally robust optimal dispatch(DROD)model for the OWF cluster connected by VSc-MTDc is *** first stage in this model optimizes the unit commitment of wind turbines to minimize mechanical loss cost of units under the worst joint probability distribution(JPD)of wind speeds,while the second stage searches for the worst JPD of wind speeds in the ambiguity set(AS)and optimizes active power output of wind turbines to minimize the penalty cost of the generation deviation and active power loss cost of the *** on the Kullback–Leibler(KL)divergence distance,a data-driven AS is constructed to describe the uncertainty of wind speed,considering the correlation between wind speeds of adjacent OWFs in the cluster by their joint *** original solution of the two-stage DROD model is transformed into the alternating iterative solution of the master problem and the sub-problem by the column-and-constraint generation(c&cg)algorithm,and the master problem is decomposed into a mixedinteger linear programming and a continuous second-order cone programming by the generalized Benders decomposition method to improve calculation ***,case studies on an actual OWF cluster with three OWFs demonstrate the correctness and efficiency of the proposed model and algorithm.

关键词： c&cg algorithm distributionally robust optimization generalized Benders decomposition offshore wind farm wind speed correlation

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A robust optimization method for new distribution systems based on adaptive data-driven polyhedral sets

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FRONTIERS IN ENERGY RESEARcH 2024年 12卷

作者： Ye, Yuming Wang, Jungang Pan, Dingcai Zhang, Jingsong Li, Fan Yin, Xueli Elect Power Res Inst Guizhou Power Grid Co Ltd Guiyang Guizhou Peoples R China China Southern Power Grid Energy Dev Res Inst Guangzhou Guangdong Peoples R China China Southern Power Grid Digital Power Grid Grp C Guangzhou Guangdong Peoples R China

In order to better describe the uncertainty of renewable energy output, this paper proposed a novel robust optimization method for new distribution systems based on adaptive data-driven polyhedral sets. First, an ellipsoidal uncertainty set was established using historical data on renewable energy output, and a data-driven convex hull polyhedral set was established by connecting high-dimensional ellipsoidal vertices;on this basis, an adaptive data-driven polyhedral set model was established to address the problem of high conservatism in the scaling process of convex hull polyhedral sets. Furthermore, a novel adaptive data-driven robust scheduling model for new distribution systems was established, and a column-and-constraint generation (c&cg) algorithm was used to solve the robust scheduling model. Finally, the improved IEEE-33 bus system simulation verification shows that the robust scheduling model for new distribution systems based on adaptive data-driven polyhedral sets can reduce conservatism and improve the robustness of optimization results.

关键词： two-stage robust optimization convex hull polyhedral set hyperplane polyhedral set economic dispatch c&cg algorithm

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A robust active distribution network defensive strategy against cyber-attack considering multi-uncertainties

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第8期16卷 1476-1488页

作者： Yang, Jie Guo, Yihao Guo, chuangxin chen, Zhe Wang, Shenghan Jiang, Boyou Zhejiang Univ Coll Elect Engn 38 Zheda Rd Hangzhou 310027 Zhejiang Peoples R China Elect Power Res Inst State Grid Zhejiang Elect Po 1 Huadian Lane Hangzhou 310000 Zhejiang Peoples R China

A robust defensive strategy for active distribution networks considering multi-uncertainties and island restoration is studied. Firstly, the authors take triple uncertainties into consideration, that is, the attack strategy, the amount of wind power generation and solar irradiation. Next, a trilevel defender-attacker-defender (DAD) two-stage robust mathematical model is established to make full use of the energy storage support capacity and reduce the load shedding. The first stage is to pre-allocate defensive resources, and the second stage is to dispatch emergent defensive resources in the worst scenario to minimize the load shedding. Using column and constraint generation (c&cg) algorithm to solve the model, the original problem is converted into the min main problem and max-min sub-problem. The non-convexity of the sub-problem is relaxed by using the second order cone programming (SOcP) model, and converted to the max problem according to the strong duality theory. Solving the model with returned cuttings iteratively. The simulation results show that the proposed method is effective and the defensive strategy can adapt to multi-uncertainties.

关键词： computer crime duality (mathematics) wind power plants strong duality theory resource allocation solar power stations trilevel defender-attacker-defender two-stage robust mathematical model iterative methods max-min sub-problem energy storage support capacity wind power generation cyber-attack minimax techniques min main problem trilevel DAD two-stage robust mathematical model distributed power generation SOcP model distribution networks robust active distribution network defensive strategy c&cg algorithm solar irradiation second order cone programming model robust defensive strategy power system security load shedding island restoration column and constraint generation algorithm concave programming active distribution networks power engineering computing

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Research on data-driven, multi-component distribution network attack planning methods

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FRONTIERS IN ENERGY RESEARcH 2024年 12卷

作者： Wang, Xueyan Zhang, Bingye Li, Dengdiao Sun, Jinzhou Wang, Yu Wang, Xinyu Liang, Qu Tang, Fei State Grid Zhejiang Elect Power Co Ltd Taizhou Power Supply Co Hangzhou Jiangsu Peoples R China Wuhan Univ Sch Elect & Automat Wuhan Peoples R China Hubei Engn & Technol Res Ctr AC DC Intelligent Distribut Network Wuhan Peoples R China

As the physical power information system undergoes continual advancement, mobile energy storage has become a pivotal component in the planning and orchestration of multi-component distribution networks. Furthermore, the evolution and enhancement of big data technologies have significantly contributed to enhancing the rationality and efficacy of various distribution network planning and layout approaches. At the same time, multi-distribution networks have also confronted numerous network attacks with increasing probability and severity. In this study, a Petri net is initially employed as a modeling technique to delineate the network attack flow within the distribution network. Subsequently, the data from prior network attacks are consolidated and scrutinized to evaluate the vulnerability of the cyber-physical system (cPS), thereby identifying the most critical network attack pattern for a multi-component distribution network. Following this, the defender-attacker-defender planning methodology is applied for scale modeling, incorporating rapidly evolving mobile energy storage into the pre-layout, aiming to mitigate the detrimental impact of network attacks on the power grid. Ultimately, the column and constraint generation (c&cg) algorithm is utilized to simulate and validate the proposed planning strategy in a 33-node system with multiple control groups established to demonstrate the viability and merits of the proposed strategy.

关键词： multi-component distribution network cyber attack DAD planning model mobile energy storage c&cg algorithm data-driven

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Adaptive robust unit commitment model based on the polyhedral uncertainty set 5

Adaptive robust unit commitment model based on the polyhedra...

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5th Asia conference on Power and Electrical Engineering (AcPEE)

作者： Dong, Yunhui Wang, chengfu Zhang, Yumin Li, Xijuan Sheng, Hongzhang Li, Bowen Shandong Univ Sch Elect Engn Jinan Peoples R China Shandong Univ Sci & Technol Sch Elect Engn Qingdao Peoples R China State Grid Shaoxin Power Supply Co Shaoxing Peoples R China

ISBN: (纸本)9781728152813

To address the increase of wind power uncertain along with wind power capacity, a bi-level robust unit commitment (RUc) model is built to obtain the optimal unit commitment scheme in the worst-case scenario. The objective function considers the start-up/off cost and operation cost of all units. considering the temporal correlation characteristics of wind power forecast errors, a polyhedral uncertainty set is designed. conditional Value-at Risk (cVaR) is adopted to describe the risk loss when the real wind power output is beyond the predefined uncertainty set and also determine the interval of acceptable wind power output. In view of the inner and outer layers of model interact with each other, the primal problem is decomposed into day-ahead Uc master problem and the subproblem which considers economic dispatch. In the solving process, the strong duality theorem and the Big-M method are employed to transform the sub-problem with max-min structure into a MILP problem, then the problem is solved by the column and constraint generation (c&cg) algorithm. Finally, the results show the effectiveness of the proposed model.

关键词： Robust unit commitment Wind power cVaR Temporal correlation c&cg algorithm

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Study of two-stage Robust Multi-storage Peaking Strategy Based on 3

Study of two-stage Robust Multi-storage Peaking Strategy Bas...

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3rd International conference on New Energy and Power Engineering, IcNEPE 2023

作者： Xu, Kai Zhang, Ming Wang, Yaru Wang, Fayin Qingdao University School of Electrical Engineering Qingdao China Wuzheng Group Co. Ltd. Rizhao China

ISBN: (纸本)9798350393224

With the large-scale access of renewable energy sources, the stable operation of microgrids has been seriously affected, thus increasing the peaking burden of the system. To solve this problem, this paper proposes a two-stage robust peaking strategy for microgrids that takes into account the uncertainty of renewable energy sources. In the first stage, planning is based on forecast data with the objective of minimizing net load fluctuations. In the second stage, wind power uncertainty is considered to find the wind power output in the worst scenario and adjust the strategy in the first stage to ensure the stability of the microgrid. Secondly, for the problem of single interval two-stage robust conservatism, a multi-interval uncertainty set is employed and solved using the nested column and constraint generation (c&cg) algorithm. Finally, the rationality and effectiveness of the strategy in this paper are verified by an arithmetic example analysis. © 2023 IEEE.

关键词： c&cg algorithm microgrid two-stage robustness wind and photovoltaic uncertainty

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Power System Restoration Strategy considering the Wind Farm with Hydrogen Storage 3

Power System Restoration Strategy Considering the Wind Farm ...

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3rd Asia Power and Electrical Technology conference, APET 2024

作者： Wei, Youwang Fang, Weikang Sun, Lei School of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China

ISBN: (纸本)9798350367690

The increasing integration of wind energy poses significant challenges to the reliable operation of power systems in normal and extreme operation scenarios. Nevertheless, the hydrogen storage system (HSS), with its adaptable operational attributes, has the potential to effectively address the unpredictability and fluctuating nature of wind power. This study focuses on the post-disaster restoration phase, introducing a noval coordination mechanism between the wind farm and the HSS for the faster and reliable restoration. The whole process restoration considering the wind farm with hydrogen storage (WFHS) is modeled as a two-stage distributionally robust optimization problem. The first stage problem determines the sequence of unit start-up and network skeleton reconfiguration, while the second stage problem performs load restoration and scheduling of the WFHS considering the uncertainty of wind outputs. The column-and-constraint generation (c&cg) decomposition algorithm is employed to address the two-stage distributionally robust optimization problem. The proposed coordination mechanism is carried on the enhanced IEEE 39-bus system. Numerical results demonstrate that the coordination of the wind farm and hydrogen storage system can increase the total load served, enable full utilization of wind energy in the restoration process and minimize wind energy waste. © 2024 IEEE.

关键词： c&cg algorithm distributionally robust optimization hydrogen storage power system restoration wind uncertainty

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Two stage robust economic dispatching of microgrid considering uncertainty of wind, solar and electricity load along with carbon emission predicted by neural network model

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ENERGY 2024年 300卷

作者： Shen, Haotian Zhang, Hualiang Xu, Yujie chen, Haisheng Zhang, Zhilai Li, Wenkai Su, Xu Xu, Yalin Zhu, Yilin Chinese Acad Sci Nanjing Inst Future Energy Syst Inst Engn Thermophys Nanjing 211135 Peoples R China Chinese Acad Sci Inst Engn Thermophys Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

The fluctuation characteristics of wind, solar and electric load in microgrid are predicted by BP neural network. Based on forecast error, an economic robust optimization model is established considering uncertain variables, flexible load and carbon emission, solving by c &cg algorithm, which adjusted for individual uncertainty degree and overall conservatism of variables. The power of gas turbine is closely related to time -of -use price while the power of energy storage depends on the relationship of electrovalence and operation cost and flexible load is transferred to valley consumption time. As overall conservatism increases, the electricity purchase increases where microgrid refers to buy more electricity to resist risks, leading to 1897.4 yuan and 1007.2 kg of carbon emission added. Robust scheduling has lower costs compared to intra-day scheduling of 14.2 % decreasing when the intra-day electrovalence increases. considering carbon quota constraint dispatching is more inclined to utilize gas turbine and energy storage while the total cost would rise by 247.6 yuan. With changing the operating cost of gas turbine, a balance point could be obtained in the game between economy and carbon emission. And there would exist an optimal equipment operation strategy when carbon emission is sufficiently enough, which realizes a balance of energy -carbon -economy.

关键词： Fluctuation forecast Day-ahead dispatching Robust optimization carbon quotas c&cg algorithm Energy-carbon-economy balance

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A trilevel model against false gas-supply information attacks in electricity systems

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ELEcTRIc POWER SYSTEMS RESEARcH 2020年 189卷 106541-106541页

作者： Zhao, Bining Lamadrid, Alberto J. Blum, Rick S. Kishore, Shalinee Lehigh Univ Dept ECE Bethlehem PA 18015 USA Lehigh Univ Dept Econ Bethlehem PA 18015 USA Lehigh Univ Dept ISE Bethlehem PA 18015 USA

The interdependence between natural gas and electricity systems is increasing rapidly due to the growing reliance on natural gas-fired generating units. Availability of natural gas for gas-fired generating units can impact the secure operation of electricity systems. Fuel supply shortage for gas-fired units can be caused by uncertain interruptible supply contracts and incorrect supply information. This article proposes a trilevel min-max-min defender-attacker-operator optimization problem to provide the power system operator a screening methodology that allocates a limited budget for best protecting critical fuel supply information, and also the strategies to sign firm supply contract to reduce natural gas supply uncertainties. We employ a column and constraint generation (c&cg) algorithm to solve the proposed problem. We illustrate the effectiveness of this trilevel formulation using a case study based on IEEE 24-node test system.

关键词： cyber attacks Natural gas Power system operation Trilevel optimization c&cg algorithm

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