2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)最新文献_第3页

A Data-Driven Approach to Assessing and Improving Stochastic Residential Load Modeling for District-Level Simulations and PV Integration 基于数据驱动的区域级模拟和光伏集成随机住宅负荷建模评估与改进方法

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183420

R. Claeys, C. Protopapadaki, D. Saelens, J. Desmet

{"title":"A Data-Driven Approach to Assessing and Improving Stochastic Residential Load Modeling for District-Level Simulations and PV Integration","authors":"R. Claeys, C. Protopapadaki, D. Saelens, J. Desmet","doi":"10.1109/PMAPS47429.2020.9183420","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183420","url":null,"abstract":"This paper presents an assessment and improvement of stochastic load modeling for district-level analyses with integration of photovoltaic panels (PV), by comparison with measurement data. Stochastic load profiles for individual households were produced using the bottom-up ‘Stochastic Residential Occupancy Behavior’ (StROBe) model. The self-consumption of households with PV installations and the district-level peak demand are examined as properties relevant for the estimation of PV hosting capacity and accompanying grid-related problems. The comparison shows that while the synthetic profiles produce reasonable estimates of simultaneity and summer peak demand, they insufficiently represent the seasonal variations. In addition, self-consumption is overestimated by the model. The observed discrepancies can be traced back to inaccurate modeling of the peak timing and seasonal variation in individual peak load and simultaneity. Furthermore, vacant homes in the measured data are found to contribute significantly to discrepancies in holiday periods. Adjusting the stochastic modeling to account for these vacant homes results in improved performance of the model. This research demonstrates that harvesting the full potential of bottom-up stochastic load modeling would require more up-to-date information on residential electricity use patterns.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129336467","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}

引用次数: 0

A Method to Evaluate the Maximum Hosting Capacity of Power Systems to Electric Vehicles 一种评估电力系统对电动汽车最大承载能力的方法

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183519

M. Kamruzzaman, Xiaohu Zhang, Michael Abdelmalak, M. Benidris, Di Shi

{"title":"A Method to Evaluate the Maximum Hosting Capacity of Power Systems to Electric Vehicles","authors":"M. Kamruzzaman, Xiaohu Zhang, Michael Abdelmalak, M. Benidris, Di Shi","doi":"10.1109/PMAPS47429.2020.9183519","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183519","url":null,"abstract":"This paper proposes a smart charging/discharging-based method to evaluate the expected maximum hosting capacity (EMHC) of power systems to electric vehicles (EVs). The rapid growth in the use of EVs increases the challenges to satisfy their charging demand using existing power system resources. Therefore, a method to quantify the EMHC of power systems to EVs is required to plan for system improvements and ensure maximum utilization of resources. In this work, a method to calculate the EMHC of power systems to EVs is developed based on variable charging/discharging rates. The EMHC is calculated for charging stations at both homes and workplaces. The charging/discharging rates are varied based on daily energy demand and parking durations of EVs and network constraints. The parking duration is calculated based on probability distribution functions (PDFs) of arrival and departure times. The energy required to travel each mile and PDF of daily travel distances are used to calculate the daily energy demand of EVs. The optimization problem to maximize the hosting capacity is formulated using a linearized AC power flow model. The Monte Carlo simulation is used to calculate the EMHC. The proposed method is demonstrated on the modified IEEE 33-bus system. The results show that the daily EMHC of the modified IEEE 33-bus system varies between 20-41 cars for selected nodes.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125647274","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}

引用次数: 3

Operating Reserve Assessment in Systems with Energy Storage and Electric Vehicles 储能和电动汽车系统的运行储备评估

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183486

J. F. C. Castro, P. Rosas, L. H. A. Medeiros, A. M. Leite da Silva

引用次数: 0

Swift Disaster Recovery for Resilient Power Grids: Integration of DERs with Mobile Power Sources 弹性电网的快速灾难恢复:DERs与移动电源的集成

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183451

Mostafa Nazemi, P. Dehghanian, Zijiang Yang

引用次数: 2

Representing Long-term Impact of Residential Building Energy Management using Stochastic Dynamic Programming 用随机动态规划表示住宅建筑能源管理的长期影响

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183623

K. Thorvaldsen, Sigurd Bjarghov, H. Farahmand

{"title":"Representing Long-term Impact of Residential Building Energy Management using Stochastic Dynamic Programming","authors":"K. Thorvaldsen, Sigurd Bjarghov, H. Farahmand","doi":"10.1109/PMAPS47429.2020.9183623","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183623","url":null,"abstract":"Scheduling a residential building short-term to optimize the electricity bill can be difficult with the inclusion of capacity-based grid tariffs. Scheduling the building based on a proposed measured-peak (MP) grid tariff, which is a cost based on the highest peak power over a period, requires the user to consider the impact the current decision-making has in the future. Therefore, the authors propose a mathematical model using stochastic dynamic programming (SDP) that tries to represent the long-term impact of current decision-making. The SDP algorithm calculates non-linear expected future cost curves (EFCC) for the building based on the peak power backwards for each day over a month. The uncertainty in load demand and weather are considered using a discrete Markov chain setup. The model is applied to a case study for a Norwegian building with smart control of flexible loads, and compared against methods where the MP grid tariff is not accurately represented, and where the user has perfect information of the whole month. The results showed that the SDP algorithm performs 0.3 % better than a scenario with no accurate way of presenting future impacts, and performs 3.6 % worse compared to a scenario where the user had perfect information.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"374 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122605397","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}

引用次数: 3

Power System Resiliency During Wildfires Under Increasing Penetration of Electric Vehicles 在电动汽车日益普及的情况下，火灾时电力系统的弹性

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183683

Daniel L. Donaldson, Manuel S. Alvarez‐Alvarado, D. Jayaweera

{"title":"Power System Resiliency During Wildfires Under Increasing Penetration of Electric Vehicles","authors":"Daniel L. Donaldson, Manuel S. Alvarez‐Alvarado, D. Jayaweera","doi":"10.1109/PMAPS47429.2020.9183683","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183683","url":null,"abstract":"Rising electric vehicle (EV) adoption is introducing new challenges to the operation and planning of the electric grid. Currently power system planners perform analysis to ensure adequate levels of reliability following contingencies such as loss of a substation. However, existing planning standards do not explicitly mandate studies of the redistribution of EV charging demand that would take place in the case of extreme events. Planning to serve the charging demand from EVs during extreme events is paramount to ensure the resiliency of the grid. This paper presents a novel framework for power system planners to reflect the impact of EV evacuations on grid resiliency during wildfire events. The method consists of resiliency analysis coupled with probabilistic models of load redistribution taking into account potential evacuation routes. A case study using the 2019 update to the IEEE 24 bus Reliability Test System (RTS) is performed to demonstrate the efficacy of the proposed strategy. The framework results in a more specific resiliency trapezoid that reflects a more realistic resiliency behaviour of the system.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117078359","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}

引用次数: 10

A Sensitivity-based Approach for Optimal Siting of Distributed Energy Resources 基于灵敏度的分布式能源优化选址方法

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183471

Mukesh Gautam, N. Bhusal, M. Benidris, C. Singh, J. Mitra

{"title":"A Sensitivity-based Approach for Optimal Siting of Distributed Energy Resources","authors":"Mukesh Gautam, N. Bhusal, M. Benidris, C. Singh, J. Mitra","doi":"10.1109/PMAPS47429.2020.9183471","DOIUrl":"https://doi.org/10.1109/PMAPS47429.2020.9183471","url":null,"abstract":"This paper presents a sensitivity-based approach for the placement of distributed energy resources (DERs) in power systems. The approach is based on the fact that most planning studies utilize some form of optimization, and solutions to these optimization problems provide insights into the sensitivity of many system variables to operating conditions and constraints. However, most of the existing sensitivity-based planning criteria do not capture ranges of effectiveness of these solutions (i.e., ranges of the effectiveness of Lagrange multipliers). The proposed method detects the ranges of effectiveness of Lagrange multipliers and uses them to determine optimal solution alternatives. Profiles for existing generation and loads, and transmission constraints are taken into consideration. The proposed method is used to determine the impacts of DERs at different locations, in presence of a stochastic element (load variability). This method consists of sequentially calculating Lagrange multipliers of the dual solution of the optimization problem for various load buses for all load scenarios. Optimal sizes and sites of resources are jointly determined in a sequential manner based on the validity of active constraints. The effectiveness of the proposed method is demonstrated through several case studies on various test systems including the IEEE reliability test system (IEEE RTS), the IEEE 14 and 30 bus systems. In comparison with conventional sensitivity-based approaches (i.e., without considering ranges of validity of Lagrange multipliers), the proposed approach provides more accurate results for active constraints.","PeriodicalId":126918,"journal":{"name":"2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115241319","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}

引用次数: 1

Linear State and Parameter Estimation for Power Transmission Networks 输电网的线性状态和参数估计

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183473

Aleksandar Jovici, G. Hug

引用次数: 1

Deriving Transformer Equivalent Age for Power System Reliability Assessment from Asset Condition Score 从资产状态分数求电力系统可靠性评估变压器等效年龄

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183412

S. Awadallah, J. Milanović, P. Jarman

引用次数: 0

Distributionally Robust Co-Optimization of Energy and Reserve Dispatch of Integrated Electricity and Heat System 电热一体化系统能量与储备调度的分布式鲁棒协同优化

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI: 10.1109/PMAPS47429.2020.9183678

Mikhail Skalyga, Quiwei Wu

引用次数: 3