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Integrated generation–consumption dispatch based on compensation mechanism considering demand response behavior

Journal of Modern power systems and Clean Energy 2018年第5期6卷 1025-1041页

作者： Yumin ZHANG Xueshan HAN Li ZHANG Bo XU Mingqiang WANG Ming YANG Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University

Demand response(DR) is important to account for behaviors of the demand side to yield an optimal dispatch result. However, it is difficult for energy suppliers to collect customers' private information unless there is an incentive mechanism for customers to do so. Therefore,this paper proposes a new integrated generation–consumption dispatch based on compensation mechanism considering DR behavior. Firstly, in light of the dayahead load forecast data, we deduce the utility function model of different customers. By subtracting generating units' operation cost from consumers' total utility, the dispatch model has a decentralized demand participant structure based on this utility function. The utility function is used to describe consumers' preferences and energy consumption behaviors. Secondly, an effective compensation mechanism is designed to ensure customers to select the level of compensation appropriate to their willingness to curtail load. Finally, a new dispatch model is proposed that incorporates the DR compensation mechanism into the generation–consumption dispatch model. The new model can improve the interaction of generation and consumption,and benefit both the energy supplier and its customers. The proposed model is piecewise linearized and solved by a mixed-integer linear programming method. It is tested on a six-bus system and the IEEE 118-bus system. simulation results show that the proposed model can realize both maximum social welfare and Pareto optimal results.

关键词： Compensation mechanism Demand response Demand utility function Integrated generation– consumption dispatch

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A comparative thermodynamic analysis of Kalina and organic Rankine cycles for hot dry rock:a prospect study in the Gonghe Basin

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Frontiers in Energy 2020年第4期14卷 889-900页

作者： Xuelin ZHANG Tong ZHANG Xiaodai XUE Yang SI Xuemin ZHANG Shengwei MEI State Key Laboratory of Control and Simulation of Power System and Generation Equipments Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Jingjing Energy Storage Co. Ltd.Changzhou 213200China School of QiDi(TUS)Renewable Energy Qinghai UniversityXining 810016China

Hot dry rock is a new type of geothermal resource which has a promising application prospect in *** paper conducted a comparative research on performance evaluation of two eligible bottoming cycles for a hot dry rock power plant in the Gonghe *** on the given heat production conditions,a Kalina cycle and three organic Rankine cycles were tested respectively with different ammonia-water mixtures of seven ammonia mass fractions and nine ecofriendly working *** results show that the optimal ammonia mass fraction is 82%for the proposed bottoming Kalina cycle in view of maximum net power *** analysis suggests that wet fluids should be supercritical while dry fluids should be saturated at the inlet of turbine,*** maximum net power output of the organic Rankine cycle with dry fluids expanding from saturated state is higher than that of the other organic Rankine cycle combinations,and is far higher than the maximum net power output in all tested Kalina cycle *** the given heat production conditions of hot dry rock resource in the Gonghe Basin,the saturated organic Rankine cycle with the dry fluid butane as working fluid generates the largest amount of net power.

关键词： hot dry rock Kalina cycle organic Rankine cycle thermodynamic analysis

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Fast Monte Carlo simulation of Dynamic power systems under Continuous Random Disturbances

arXiv

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arXiv 2020年

作者： Qiu, Yiwei Lin, Jin Chen, Xiaoshuang Liu, Feng Song, Yonghua State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China Department of Electrical and Computer Engineering University of Macau 999078 China

—Continuous-time random disturbances from the renewable generation pose a significant impact on power system dynamic behavior. In evaluating this impact, the disturbances must be considered as continuous-time random processes instead of random variables that do not vary with time to ensure accuracy. Monte Carlo simulation (MCs) is a nonintrusive method to evaluate such impact that can be performed on commercial power system simulation software and is easy for power utilities to use, but is computationally cumbersome. Fast samplings methods such as Latin hypercube sampling (LHS) have been introduced to speed up sampling random variables, but yet cannot be applied to sample continuous disturbances. To overcome this limitation, this paper proposes a fast MCs method that enables the LHS to speed up sampling continuous disturbances, which is based on the Itô process model of the disturbances and the approximation of the Itô process by functions of independent normal random variables. A case study of the IEEE 39-Bus System shows that the proposed method is 47.6 and 6.7 times faster to converge compared to the traditional MCs in evaluating the expectation and variance of the system dynamic response. Copyright © 2020, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Deep learning-aided model predictive control of wind farms for AGC considering the dynamic wake effect

arXiv

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arXiv 2020年

作者： Chen, Kaixuan Lin, Jin Qiu, Yiwei Liu, Feng Song, Yonghua State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China Department of Electrical and Computer Engineering University of Macau 999078 China

To provide automatic generation control (AGC) service, wind farms (WFs) are required to control their operation dynamically to track the time-varying power reference. Wake effects impose significant aerodynamic interactions among turbines, which remarkably influence the WF dynamic power production. The nonlinear and high-dimensional nature of dynamic wake model, however, brings extremely high computation complexity and obscure the design of WF controllers. This paper overcomes the control difficulty brought by the dynamic wake model by proposing a novel control-oriented reduced order WF model and a deep-learning-aided model predictive control (MPC) method. Leveraging recent advances in computational fluid dynamics (CFD) to provide high-fidelity data that simulates WF dynamic wake flows, two novel deep neural network (DNN) architectures are specially designed to learn a dynamic WF reduced-order model (ROM) that can capture the dominant flow dynamics. Then, a novel MPC framework is constructed that explicitly incorporates the obtained WF ROM to coordinate different turbines while considering dynamic wake interactions. The proposed WF ROM and the control method are evaluated in a widely-accepted high-dimensional dynamic WF simulator whose accuracy has been validated by realistic measurement data. A 9-turbine WF case and a larger 25-turbine WF case are studied. By reducing WF model states by many orders of magnitude, the computational burden of the control method is reduced greatly. Besides, through the proposed method, the range of AGC signals that can be tracked by the WF in the dynamic operation is extended compared with the existing greedy controller. Copyright © 2020, The Authors. All rights reserved.

关键词： Model predictive control

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Wavelet-based data compression for wide-area measurement data of oscillations

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Journal of Modern power systems and Clean Energy 2018年第6期6卷 1128-1140页

作者： Lin CHENG Xinchi JI Fang ZHANG He HUANG Song GAO State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua University State Grid Jiangsu Electric Power Company

This paper proposes a wavelet-based data compression method to compress the recorded data of oscillations in power systems for wide-area measurement systems. Actual recorded oscillations and simulated oscillations are compressed and reconstructed by the waveletbased data compression method to select the best wavelet functions and decomposition scales according to the criterion of the minimum compression distortion composite index, for a balanced consideration of compression performance and reconstruction accuracy. Based on the selections, the relationship between the oscillation frequency and the corresponding optimal wavelet and scale is discussed, and a piecewise linear model of the base-2 logarithm of the frequency and the order of the wavelet is developed, in which different pieces represent different scales. As a result, the wavelet function and decomposition scale can be selected according to the oscillation frequency. Compared with the wavelet-based data compression method with a fixed wavelet scale for disturbance signals and the real-time data compression method based on exception compression and swing door trending for oscillations, the proposed method can provide high compression ratios and low distortion rates.

关键词： Data compression Oscillation Wavelet transform Wide-area measurement system(WAMS)

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key technologies of the operational reliability evaluation for the large-scale battery energy storage system 7

Key technologies of the operational reliability evaluation f...

引用

7th International Conference on Reliability of Electrical Products and Electrical Contacts, ICREPEC 2019

作者： Cheng, Lin Wan, Yuxiang Jiang, Yi Wang, Zhidong Liu, Mei State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing100084 China State Grid Economic and Technological Research Institute Corporation Limited State Grid Corporation of China Beijing102209 China

ISBN: (纸本)9789881532343

The large-scale battery energy storage system (BESS) can effectively meet the diversified needs of power grid dispatching. Therefore, the improvement of the BESS operational reliability is of great significance to ensure the operation safety of the grid. However, the BESS is composed of a large number of batteries. This fact suggests the BESS reliability depends not only on the battery operating state but also on the strategy of battery networking reconfiguration. In this paper, the analysis of the operational reliability research of largescale BESS is carried out in-depth. The research status of reliability of large-scale BESS is investigated, and some thoughts on the obstacles to the BESS operational reliability evaluation are given. The promotion of the new technology of BESS and the development of the ubiquitous Internet of Things on BESS operation reliability are analyzed. In addition, the framework of the operational reliability evaluation of a large-scale BESS is proposed. Some key technologies such as failure mechanism, equipment reliability modeling, evaluation, and optimization are summarized, providing some suggestions for the application of large-scale BESS. © 2019 by International Academic Publishers Ltd.

关键词： Electric batteries

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Consensus-Based Distributed Economic Dispatch with Optimized Transition Matrix

Consensus-Based Distributed Economic Dispatch with Optimized...

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IEEE power and Energy Society General Meeting

作者： Xinfei Yan Haiwang Zhong Jianxiao Wang Zhenfei Tan State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Beijing China

With an increasing penetration of distributed energy resources (DERs) in Energy Internet, there is a surge of interest in distributed economic dispatch (DED) problems. The existing literature mainly focuses on average consensus algorithms, the convergence of which remains a bottleneck in practical applications. To improve the convergence rate of DED, this paper proposes a consensus algorithm based on optimized transition matrix (TM) of Markov chain. A DED model is firstly developed under a consensus-based information exchange architecture, in which a generator only communicates with its neighbors. Thus DED is implemented in an iterative manner with generators exchanging information according to a predefined TM. In contrast to the aver-agely weighted TM, we minimize the Frobenius norm (F-norm) of the TM in order to limit the eigenvalues that greatly influence the convergence rate of DED. Additionally, a virtual power method is introduced to meet generators' power limits by reformulating the power allocation ratio. Case studies verify the effectiveness and efficiency of the proposed algorithm.

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CCF early warning method of LCC-HVDC based on XG boost algorithm 8

CCF early warning method of LCC-HVDC based on XG boost algor...

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8th Renewable power generation Conference, RPG 2019

作者： Li, Zhizhong Wang, Bin Wang, Haigang Yu, Bin Xie, Min Chen, Shi Dong, Xinzhou Key Lab of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China State Grid Anhui Electric Power Company Hefei 230061 China

ISBN: (纸本)9781839531255

The lack of analytical mechanism of continuous commutation failure (CCF) process hinders the development of CCF early warning algorithm and further obstructs the coordination strategy of relay protection between AC and DC size in hybrid grid. However, summarizing the protection threshold of CCF in the form of electrical quantity analytically under different fault types is a nontrivial pattern recognition problem. To overcome the difficulty of directly analysing the electromagnetic process of CCF, a statistical learning modelling approach is adapted to propose a CCF warning system, in which XGBoost algorithm was used as the backbone to regress on the relationship between AC/DC electrical quantities and the possibility of the occurrence of CCF. The design of the feature vector in XGBoost-based classifier considers not only the analytical expression of key electrical quantity during single commutation failure but also the important state variable of control system. Additionally, a special data windowing method was proposed to enrich of information encoded by the feature vector while ensuring the speed requirement posed by the protection system. Validation on multi-fault scenes simulation shows that the proposed early warning system can trigger warning signal correctly with sufficiently small measured data required, proving the practicability in engineering practice. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： HVDC power transmission

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Energy Management of a Residential Consumer with Uncertain Renewable generation: A Robust Dual Dynamic Programming Approach

Energy Management of a Residential Consumer with Uncertain R...

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Chinese control Conference (CCC)

作者： Dangwu Liu Zhongjie Guo Feng Chen Xiaodai Xue Shengwei Mei State Grid Anhui Electric Power CO. LTD Hefei P. R. China State Key Lab of Control and Simulation of Power Systems and Generation Equipments Tsinghua University Beijing China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper studies the dynamic operation of a residential electric energy system with distributed renewable generation. Energy streams among the power grid, local renewable plant, storage unit, and demand are considered; the temporal volatility of renewable generation is described by an uncertainty set, and the optimal operation problem gives rise to a multi-stage robust optimization. To deal with the non-anticipativity issue, the robust model is solved via robust dual dynamic programming (RDDP) approach. The the cost-to-go function is approximated by iteratively updating the upper and lower bounds, which can be obtained from forward-pass and backward pass procedures. Case studies validate the performance and advantage of the proposed method.

关键词： Uncertainty Robustness Dynamic programming Upper bound Optimization Heuristic algorithms Energy storage

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Tertiary regulation of cascaded run-of-the-river hydropower in the islanded renewable power system considering multi-timescale dynamics

arXiv

引用

arXiv 2020年

作者： Qiu, Yiwei Lin, Jin Liu, Feng Dai, Ningyi Song, Yonghua Chen, Gang Ding, Lijie State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China State Key Laboratory of Internet of Things for Smart City University of Macau 999078 China State Grid Sichuan Electric Power Research Institute Chengdu610000 China

To enable power supply in rural areas and to exploit clean energy, fully renewable power systems consisting of cascaded run-of-the-river hydropower and volatile energies such as pv and wind are built around the world. In islanded operation mode, the primary and secondary frequency control, i.e., hydro governors and automatic generation control (AGC), are responsible for the frequency stability. However, due to limited water storage capacity of run-of-the-river hydropower and river dynamics constraints, without coordination between the cascaded plants, the traditional AGC with fixed participation factors cannot fully exploit the adjustability of cascaded hydropower. When imbalances between the volatile energy and load occur, load shedding can be inevitable. To address this issue, this paper proposes a coordinated tertiary control approach by jointly considering power system dynamics and the river dynamics that couples the cascaded hydropower plants. The timescales of the power system and river dynamics are very different. To unify the multi-timescale dynamics to establish a model predictive controller that coordinates the cascaded plants, the relation between AGC parameters and turbine discharge over a time interval is approximated by a data-based second-order polynomial surrogate model. The cascaded plants are coordinated by optimising AGC participation factors in a receding-horizon manner, and load shedding is minimised. simulation of a real-life system with real-time pv data collected on site shows the proposed method significantly reduces load loss under pv volatility. Copyright © 2020, The Authors. All rights reserved.

关键词： Electric load shedding

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