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Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 51-65页

作者： Yonghua Song Ge Chen hongcai zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China School of Electrical and Computer Engineering Purdue UniversityWest LafayetteIN 47907 USA

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable *** to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their *** tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible ***,since ADNs are mostly operated in a normal status,only very few historical samples are ***,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network *** address this issue,we propose an enhanced constraint learning ***,it leverages constraint learning to train a neural network as surrogate of ADN's ***,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical *** incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural ***,we establish a trust region to constrain and thereafter enhance reliability of the *** confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

关键词： Deep learning demand response distribution networks imbalanced data optimal power flow

Wind Power Prediction Based on Multi-class Autoregressive Moving Average Model with Logistic Function

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Journal of Modern Power Systems and Clean Energy 2022年第5期10卷 1184-1193页

作者： Yunxuan Dong Shaodan Ma hongcai zhang Guanghua Yang IEEE State Key Laboratory of Internet of Things for Smart City and the Department of Electrical and Computer Engineering University of MacaoMacao S.A.R.999078China Institute of Physical Internet and the School of Intelligent Systems Scienceand Engineering Jinan UniversityZhuhai 519070China

The seasonality and randomness of wind present a significant challenge to the operation of modern power systems with high penetration of wind generation. An effective shortterm wind power prediction model is indispensable to address this challenge. In this paper, we propose a combined model, i.e.,a wind power prediction model based on multi-class autoregressive moving average(ARMA). It has a two-layer structure: the first layer classifies the wind power data into multiple classes with the logistic function based classification method;the second layer trains the prediction algorithm in each class. This two-layer structure helps effectively tackle the seasonality and randomness of wind power while at the same time maintaining high training efficiency with moderate model parameters. We interpret the training of the proposed model as a solvable optimization problem. We then adopt an iterative algorithm with a semi-closed-form solution to efficiently solve it. Data samples from open-source projects demonstrate the effectiveness of the proposed model. Through a series of comparisons with other state-of-the-art models, the experimental results confirm that the proposed model improves not only the prediction accuracy,but also the parameter estimation efficiency.

关键词： Wind power prediction wind generation time series analysis logistic function based classification

Time-efficient Strategic Power Dispatch for District Cooling Systems Considering Evolution of Cooling Load Uncertainties

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CSEE Journal of Power and Energy Systems 2022年第5期8卷 1457-1467页

作者： Ge Chen Biao Yan hongcai zhang Dongdong zhang Yonghua Song State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China

District cooling system(DCS)provides centralized chilled water to multiple buildings for air conditioning with high energy-efficiency and operational *** is one of the most popular cooling systems for large buildings in modern cities and an important demand response source for power *** order to enhance its energy efficiency and utilize its flexibility,strategic operation is ***,finding an optimal policy for DCS operation is a challenging task because of the high inter-connectivity among *** evolution of cooling load uncertainties further increases the *** paper addresses the aforementioned challenges by proposing a novel optimal power dispatch model for *** proposed model optimizes water temperature and mass flow rates simultaneously to improve the energy efficiency as much as *** also explicitly describes the uncertainty accumulation and ***-constrained programming is employed to guarantee the cooling service *** further propose a more timeefficient formulation to overcome the computational intractability caused by the non-smooth and non-convex *** experiments based on a real DCS confirm that a time-efficient formulation can save about half of solution time with negligible cost increase.

关键词： District cooling system HVAC cooling power dispatch demand-side flexibility chance-constrained programming

Blockchain-assisted virtual power plant framework for providing operating reserve with various distributed energy resources

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iEnergy 2023年第2期2卷 133-142页

作者： Hongyi Li Hongxun Hui hongcai zhang State Key Laboratory of Internet of Things for Smart City University of MacaoTaipaMacao SARChina

The paradigm shift from a coal-based power system to a renewable-energy-based power system brings more challenges to the supply-demand balance of the *** energy resources(DERs),which can provide operating reserve to the grid,are regarded as a promising solution to compensate for the power fluctuation of the renewable energy ***-scale DERs can be aggregated as a virtual power plant(VPP),which is eligible to bid in the operating reserve *** the DERs usually belong to different entities,it is important to investigate the VPP operation framework that coordinates the DERs in a trusted *** this paper,we propose a blockchain-assisted operating reserve framework for VPPs that aggregates various *** the heterogeneity of various DERs,we propose a unified reserve capacity evaluation method to facilitate the aggregation of *** considering the mismatch between actual available reserve capacity and the estimated value,the performance of VPP in the operating reserve market is improved.A hardware-based experimental system is developed,and numerical results are presented to demonstrate the effectiveness of the proposed framework.

关键词： Blockchain technology distributed energy resources operating reserve reserve capacity evaluation virtual power plant

Optimal transmission switching to eliminate voltage violations during light-load periods using decomposition approach

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Journal of Modern Power Systems and Clean Energy 2019年第2期7卷 297-308页

作者： Boshi ZHAO Zechun HU Qian ZHOU hongcai zhang Yonghua SONG Department of Electrical Engineering Tsinghua UniversityBeijing 100084China State Grid Jiangsu Electric Power Research Institute Nanjing 211103China Department of Electrical and Computer Engineering University of MacaoMacaoChina

With the rapid load increase in some countries such as China, power grids are becoming more strongly interconnected, and the differences between peak and valley loads are also increasing. As a result, some bulk power systems are facing high voltage limit violations during light-load periods. This paper proposes to utilize transmission switching(TS) to eliminate voltage violations. The TS problem is formed as a mixed-integer nonlinear program(MINLP) with AC power flow constraints and binary variables. The proposed MINLP problem is non-deterministic polynomial *** efficiently solve the problem, a decomposition approach is developed. This approach decomposes the original problem into a mixedinteger linear programming master problem and an AC optimal power flow slave problem that is used to check the AC feasibility. Prevention of islanding is also taken into consideration to ensure the feasibility of the TS *** modified IEEE 39-bus and IEEE 57-bus test systems are used to demonstrate the applicability and effectiveness of the proposed method.

关键词： Transmission switching Voltage violation Optimal power flow Decomposition approach Mixedinteger programming

Mixed Deep Reinforcement Learning Considering Discrete-continuous Hybrid Action Space for Smart Home Energy Management

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Journal of Modern Power Systems and Clean Energy 2022年第3期10卷 743-754页

作者： Chao Huang hongcai zhang Long Wang Xiong Luo Yonghua Song IEEE State Key Laboratory of Internet of Things for Smart City University of MacaoMacao S.A.R.China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Shunde Graduate School University of Science and Technology BeijingFoshan 528399China State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao S.A.R.China

This paper develops deep reinforcement learning(DRL)algorithms for optimizing the operation of home energy system which consists of photovoltaic(PV)panels,battery energy storage system,and household ***-free DRL algorithms can efficiently handle the difficulty of energy system modeling and uncertainty of PV ***,discretecontinuous hybrid action space of the considered home energy system challenges existing DRL algorithms for either discrete actions or continuous ***,a mixed deep reinforcement learning(MDRL)algorithm is proposed,which integrates deep Q-learning(DQL)algorithm and deep deterministic policy gradient(DDPG)*** DQL algorithm deals with discrete actions,while the DDPG algorithm handles continuous *** MDRL algorithm learns optimal strategy by trialand-error interactions with the ***,unsafe actions,which violate system constraints,can give rise to great *** handle such problem,a safe-MDRL algorithm is further *** studies demonstrate that the proposed MDRL algorithm can efficiently handle the challenge from discrete-continuous hybrid action space for home energy *** proposed MDRL algorithm reduces the operation cost while maintaining the human thermal comfort by comparing with benchmark algorithms on the test ***,the safe-MDRL algorithm greatly reduces the loss of thermal comfort in the learning stage by the proposed MDRL algorithm.

关键词： Demand response deep reinforcement learning discrete-continuous action space home energy management safe reinforcement learning

Probabilistic earthquake early warning times in Fujian Province

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Earthquake Science 2013年第1期26卷 33-41页

作者： hongcai zhang Xing Jin Fujian Earthquake Administration Institute of Earthquake Mechanic China Earthquake Administration

Earthquake early warning （EEW） systems are a new and effective way to mitigate the damage associated with earthquakes. A prototype EEW system is currently being constructed in the Fujian Province, a region along the Southeast coast of China. It is anticipated that the system will be completed in time to be tested at the end of this year （2013）. In order to evaluate how much advanced warning the EEW system will be able to provide different cities in Fujian, we established an EEW information release scheme based on the seismic monitoring stations distributed in the region. Based on this scheme, we selected 71 historical earthquakes. We then obtained the delineation of the region＇s potential seismic source data in order to estimate the highest potential seismic intensities for each city as well as the EEW system warning times. For most of the Fujian Province, EEW alarms would sound several seconds prior to the arrival of the destructive wave. This window of time gives city inhabitants the opportunity to take protective measures before the full intensity of the earthquake strikes.

关键词： Earthquake early warning systems Lead time Fujian region

Truncated Strategy Based Dynamic Network Pricing for Energy Storage

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Journal of Modern Power Systems and Clean Energy 2023年第2期11卷 544-552页

作者： Xiaohe Yan hongcai zhang Chenghong Gu Nian Liu Furong Li Yonghua Song State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University) BeijingChina State Key lab of Internet of Things for Smart City University of MacaoMacaoChina Department of Electronic and Electrical Engineering University of BathBathU.K.

With the increasing penetration of local renewable energy and flexible demand,the system demand is more unpredictable and causes network overloading,resulting in costly system *** the energy storage(ES)helps reduce the system peak power flow,the incentive for ES operation is not sufficient to reflect its value on the system investment deferral resulting from its *** paper designs a dynamic pricing signal for ES based on the truncated strategy under robust operation corresponding to the network charge ***,the operation strategy is designed for ES to reduce the total network investment cost considering the uncertainties of flexible load and renewable *** nodal uncertainties are converted into branch power flow uncertainties by the cumulant and Gram-Charlier expansion ***,a time of use(ToU)pricing scheme is designed to guide the ES operation reflecting its impact on network investment based on the longrun investment cost(LRIC)pricing *** proposed To U LRIC method allocates the investment costs averagely to network users over the potential curtailment periods,which connects the ES operation with network *** curtailment amount and the distribution of power flow are assessed by the truncated strategy considering the impact of *** demonstrated in a Grid Supply Point(GSP)distribution network in the UK,the network charges at the peak time reduce more than 20%with ES *** proposed method is cost-reflective and ensures the fairness and efficiency of the pricing signal for ES.

关键词： Energy storage network investment renewable energy robust optimization uncertainty

Continuous estimates on the earthquake early warning magnitude by use of the near-field acceleration records

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Earthquake Science 2013年第5期26卷 351-356页

作者： Jun Li Xing Jin Yongxiang Wei hongcai zhang Earthquake Administration of Fujian Province Institute of Engineering Mechanics China Earthquake Administration Fuzhou University

In this article, the seismic records of Japan＇s Kik-net are selected to measure the acceleration, displacement, and effective peak acceleration of each seismic record within a certain time after P wave, then a continuous estimation is given on earthquake early warning magnitude through statistical analysis method, and Wenchuan earthquake record is utilized to check the method. The results show that the reliability of earthquake early warning magnitude continuously increases with the increase of the seismic information, the biggest residual happens if the acceleration is adopted to fit earthquake magnitude, which may be caused by rich high-frequency components and large dispersion of peak value in acceleration record, the influence caused by the high-frequency components can be effectively reduced if the effective peak acceleration and peak displacement is adopted, it is estimated that the dispersion of earthquake magnitude obviously reduces, but it is easy for peak displacement to be affected by long-period drifting. In various components, the residual enlargement phenomenon at vertical direction is almost unobvious, thus it is recommended in this article that the effective peak acceleration at vertical direction is preferred to estimate earthquake early warning magnitude. Through adopting Wenchuan strong earthquake record to check the method mentioned in this article, it is found that this method can be used to quickly, stably, and accurately estimate the early warning magnitude of this earthquake, which shows that this method is completely applicable for earthquake early warning.

关键词： Earthquake early warning Near-fieldacceleration record Effective peak value