2022 IEEE International Conference on Energy Internet (ICEI)最新文献

{"title":"Large-Signal Modeling for Full-Bridge LLC Resonant Converter Using Extended Hyperbolic Tangent Function","authors":"Rui Wang, Chenghao Sun, Junqi Liu, Yujia Huang, Qiuye Sun","doi":"10.1109/ICEI57064.2022.00006","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00006","url":null,"abstract":"The accuracy of continuous model is important for characteristic analysis and real-time simulation of power electronic converters. Due to unique resonant tank structure, LLC resonant converter operates in continuous current mode and discontinuous current mode respectively in different operating frequency regions. It is difficult to realize unified description of its various operating modes by continuous model. To deal with this problem, this paper proposes a large-signal modeling method for full-bridge LLC resonant converter using extended hyperbolic tangent function. Firstly, characteristics of full-bridge LLC converter in each operating frequency region are analyzed. Based on this, a large-signal discontinuous model is established, which can realize unified description of various operating modes of the LLC converter. Then, an extended hyperbolic tangent function with steepness factor/impulse coefficient is constructed, and the large-signal continuous model of full-bridge LLC converter is established by using this function. Based on this model, continuous system approach can be directly applied for real-time simulation and controller design. Compared with the existing large-signal continuous model, the proposed model has lower order and higher accuracy. In addition, it can provide high-accuracy switching information of secondary-side power devices in time domain, which can be used as a reference for synchronous rectification design. Finally, simulation and experimental results verify the accuracy and effectiveness of the proposed model.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114183070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-period Two-stage Stochastic DER Aggregation for Power Flexibility Reserve","authors":"Yingying Deng, P. Zhou, Yuhao Guo, Bo Wang, H. Hua","doi":"10.1109/ICEI57064.2022.00009","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00009","url":null,"abstract":"The high penetration of distributed energy resources (DERs) and the development of the energy internet bring a huge opportunity for distribution system. Although the individual DER capacity and visibility are small, aggregating various DERs can provide more flexibility for distribution system operation. This paper proposes a multi-period two-stage DER aggregation method for different types DERs considering the operating cost minimization. In the day-ahead stage, an aggregator determines the expected power trajectory of the aggregated DERs for energy trading and the optimal interval of flexibility reserve, which are in turn submitted to the distribution system operator (DSO). During the day, with the DSO dispatch signal, the aggregator re-optimizes the scheduling of the aggregated DERs to realize the power adjustment. To handle uncertainty, a stochastic optimization method with conditional value-at-risk is adopted, aiming to achieve the trade-off between power flexibility and operating cost reduction. The proposed method is compared with the conventional method which maximizes the flexibility reserve interval. The simulation results show that the proposed method can achieve a lower operating cost with only 0.6% infeasibility rate, verifying its high efficiency.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"9 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134413265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Message from the Chairs: ICEI 2022","authors":"","doi":"10.1109/icei57064.2022.00005","DOIUrl":"https://doi.org/10.1109/icei57064.2022.00005","url":null,"abstract":"","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128779421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Bidding Strategy of Onsite Energy Storage Subject in Multi-Market Collaborated with Wind Power Plants","authors":"Yijun Ji, Lei Gan, Mingxuan Zhang, Yingyin Gong","doi":"10.1109/ICEI57064.2022.00012","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00012","url":null,"abstract":"Target on realizing carbon neutrality, energy industry is brewing great reform with the character of high penetration of renewable energy. To overcome the intermittence and fluctuation of wind farms or PV stations, onsite battery energy storage systems (BESSs) becomes a promising solution. Whereas, current profit model of onsite BESSs is not clearly enough to attract investment, not even in an association mode with renewable generation companies. Here, taking a collaboration comprised of a wind power plant (WPP) and it onsite BESS as an example, the revenue of several possible markets, including energy, reserve and frequency control (FC) market, that the joint venture can participate in was first assessed. Then, a bidding optimization model was proposed for the BESS subject in joint multi-markets collaborated with WPP as a mixed-integer linear programming model. Numerical result shows the feasibility and effectiveness of the proposed joint bidding method for the further promotion and application of joint venture mode.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129455573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Power Generation Portfolio Considering the Trading of Generation Right and Carbon Emission Allowance","authors":"Fangshu Li, Kun Yu, Xingying Chen, H. Hua","doi":"10.1109/ICEI57064.2022.00031","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00031","url":null,"abstract":"Due to increasingly prominent climate change and environmental pollution problems caused by carbon emission, the carbon emission from some enterprises has been concerned and restricted within a certain range. As one of the enterprises with high carbon emission, the generation companies with thermal power units are faced with the increased cost, since they will be charged with extra fees or required to purchase carbon emission allowance if their carbon emission exceeds certain upper limit, which is unfavorable to generation companies aiming at profitability. On the other hand, the fluctuating electricity price in the wholesale market makes the profit of generation company instable, which may bring bankruptcy risk. In this sense, how to stabilize and increase the profitability has become an urgent problem for the generation company with thermal power units. In this paper, an optimal power generation strategy considering the trading of carbon emission allowance and generation right is proposed. Firstly, the profit function of generation company is modeled. Secondly, the risk is measured using conditional value at risk (CVaR), and the generation portfolio model aiming at maximizing the profit and minimizing the risk is constructed. Then, the desired optimal generation strategy is obtained via existing solver OPTI. Finally, the feasibility of the proposed portfolio is demonstrated in simulation.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127480346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research On Optimization Of Electric Vehicle Charging Scheduling Based On Blockchain","authors":"Yuhong Di, R. Huo, Chuanglu Sun, Shiqin Zeng, Zongxuan Sha, Tao Huang","doi":"10.1109/ICEI57064.2022.00017","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00017","url":null,"abstract":"With the popularization and application of new energy, the vigorous development of electric vehicles is facilitated. While the number of electric vehicles has increased significantly, a large number of electric vehicles are charged in disorder, resulting in the problems of low charging efficiency and serious grid load. This paper proposes a blockchain-based charging scheduling strategy for electric vehicles. Firstly, a trusted information platform based on blockchain is built, and a secure scheduling architecture for electric vehicle charging based on blockchain is designed. Furthermore, considering the factors of user reputation, time-of-use electricity price, and distance consumption, a user behavior-based calculation method of the cost is proposed. Finally, an electric vehicle charging scheduling strategy based on Particle Swarm Optimization is constructed to achieve the goal of orderly charging scheduling and peak shaving and valley filling of a large number of electric vehicles. The theoretical analysis and simulation experiments show that the proposed optimization scheme could effectively reduce user overhead and grid pressure.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128138654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Trading Strategy of Multi-Integrated Energy System Considering Carbon Emissions","authors":"Tong Li, Heyang Sun","doi":"10.1109/ICEI57064.2022.00027","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00027","url":null,"abstract":"The traditional energy trading method between integrated energy systems has the problems of uneven distribution of income and information leakage. In view of the above problems, this paper proposes a comprehensive energy system trading strategy based on the bargain game. Firstly, this paper analyzes the pricing scheme of the integrated energy system, uses the method of bargain game to distribute the gains fairly, and introduces the non-cooperative cost to encourage energy trading among the integrated energy systems. Secondly, a distributed algorithm is proposed, which uses the alternating direction multiplier method to decompose the barrier game problem into two subproblems, and the optimal solution of the game problem can be obtained by using limited information between the sub-problems. Finally, verified by an example, the proposed game method and distributed algorithm can solve the energy trading strategies of multiple integrated energy systems, distribute the income fairly, and protect the information security of the integrated energy system.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114230157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel design for Data Processing Framework of Park-level Power System with Data Mesh concept","authors":"Jin Li, Shixia Cai, Lei Wang, Mingyang Li, Jiamao Li, Hui Tu","doi":"10.1109/ICEI57064.2022.00032","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00032","url":null,"abstract":"Building a new-type power system with renewable energy is the key to achieving the target of carbon peak and carbon neutrality, which has been the consensus of the clean, low-carbon, and safe energy transition. The construction of a new-type power system at the industrial park level is the first demonstration of the coordinated optimization and intelligent control of power sources, grid, load, and energy storage to make overall planning to achieve diversified development. To sustain the ‘balance, security, diversity, and low cost’ construction goals of the new-type power system at the park level, the power grid dispatching and control system is transformed to the direction of intelligence and automation, which is reflected in the rapid emergence and construction of complex systems such as digital twin, simulation, reinforcement learning, model training and prediction, and intelligent decision-making of the EMS (Energy Manage System). This brings more complex data sharing, interaction, construction, and other technical requirements than ever before. At the same time, along with the simultaneous construction of new power systems such as micro-grids, virtual power plants, and distributed photovoltaic systems, it has exacerbated the problems of data divergence from business, low data utilization, and centralized architecture brought by the data lakes and data warehouses under the previous monolithic architecture, leading to the data model hard to deploy to meet the demand for efficient collection, interaction, and sharing of scattered and heterogeneous data under the new generation energy structure and greatly increases the work pressure of the data team, making the data team a bottleneck for business applications. Therefore, this paper proposes a novel design scheme of data processing framework with the data mesh concept, supports the federal computing and analysis engine by building a distributed metadata center, changes the previous centralized data modeling method through data service and productization, realizes data sharing and interaction between complex multi-systems by defining service invocation and encapsulation technology means, improves data utilization, and better supports the automation, rationalization, and balanced construction of the intelligent dispatch system to meet the challenges and requirements brought by the new-type park-level power system.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121914146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on optimal operation strategy of load aggregator considering energy data transaction","authors":"Junni Li, Jimeng Song, Yu Zhang, Ziqi Sheng, Tianguang Yang, Mengting Jiao, Y. Wen","doi":"10.1109/ICEI57064.2022.00029","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00029","url":null,"abstract":"In the power market, the load aggregator can reasonably allocate resources, but it is difficult for the load aggregator to obtain the detailed data of the user side, which hinders the formulation of operation strategies. The market-oriented transaction of data is an important way to meet data supply and demand, and can promote data interconnection. This paper introduces energy data trading into the operation strategy of load aggregators. First, a load aggregator operation architecture considering energy data transactions is constructed; Secondly, a differentiated data pricing method is developed for power load and photovoltaic output data; Finally, with the goal of maximizing the daily profit of load aggregators, an optimized operation model of load aggregators considering energy data transactions is constructed. The simulation results show that under the scenario of energy data transaction, the load aggregator improves the prediction accuracy of load and PV output through data transaction, thereby effectively reducing the real-time power purchase cost and maximizing the daily profit, thus verifying the effectiveness of this strategy.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123645431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of SVM and ANN Based on GAPA and Its Application in Short-Term Load Forecasting","authors":"Jingyi Zhang, Yueting Wang, Wenpeng Jing, Zhaoming Lu, X. Wen, Yong Liu","doi":"10.1109/ICEI57064.2022.00035","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00035","url":null,"abstract":"Widespread employment of renewable energy such as wind and solar pushes power grids to move towards comprehensive data and predictive analysis. At present, a large number of researches have been conducted especially on machine learning methods to achieve load forecast. However, premature convergence and redundant iteration are two major defects of existing machine learning-based load forecasting methods, resulting in poor prediction effect and high time consumption. In this paper, a novel combined intelligent optimization algorithm based on genetic algorithm (GA), artificial fish swarm algorithm (AFSA) and particle swarm optimization (PSO) is proposed for optimizing machine learning-based load forecasting models. By replacing GA's mutation process with AFSA operator and PSO operator, the proposed algorithm named GA-AFSA-PSO Algorithm (GAPA) enhances both global search ability and local search ability, leading to its high prediction accuracy and fast convergence speed. To validate its effectiveness, GAPA is applied to the optimization of support vector machine (SVM) and artificial neural network (ANN) to predict one-day ahead load data. Moreover, two different sets of comparative tests are carried out to confirm the advantages of GAPA. The simulation results illustrate that, compared with GA, AFSA, PSO, AFSA-GA and GA-PSO, GAPA brings forth advancement in prediction accuracy, convergence rate and global search ability.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129793417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}