Proceedings of the 14th ACM International Conference on Future Energy Systems最新文献_第3页

Incorporating Range Anxiety into Electric Vehicle Highway Charging Decisions: A Bayesian Game Analysis✱ 将里程焦虑纳入电动汽车高速公路充电决策:一个贝叶斯博弈分析

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3595195

Huanyu Yan, Xiaoying Tang

{"title":"Incorporating Range Anxiety into Electric Vehicle Highway Charging Decisions: A Bayesian Game Analysis✱","authors":"Huanyu Yan, Xiaoying Tang","doi":"10.1145/3575813.3595195","DOIUrl":"https://doi.org/10.1145/3575813.3595195","url":null,"abstract":"As the penetration of electric vehicles (EVs) increases, highway charging has become an increasing concern for EV drivers. The improvement of EV highway charging requires analysis of EV drivers’ charging decisions. However, range anxiety, the fear of running out of electricity before reaching the next charging station, is mostly ignored by literature studying EV charging behaviors on highways. In this paper, the impact of EV drivers’ subjective range anxiety on highway charging is explicitly accounted for. In particular, a non-cooperative Bayes game is formulated between EV drivers in which each driver decides whether to charge. In this game, EV drivers seek to minimize costs, including the charging fee, range anxiety, and queuing time. A novel approach based on Prospect Theory is proposed to incorporate the impact of EV drivers’ range anxiety on charging decisions. To analyze the game insights, we prove the existence and uniqueness of Bayes Nash Equilibrium (BNE) in the symmetric two-player case, and propose an algorithm to solve the BNE. Numerical experiments are conducted to illustrate the effect of range anxiety on charging decisions. In particular, the charging decisions depend significantly on the drivers’ risk aversion tendencies.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"380 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122925011","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 Best-effort Energy Storage as a Service Model for Supporting Renewable Generators in Day-ahead Electricity Markets 日前电力市场中支持可再生能源发电的最佳储能服务模式

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3597355

Vishnu P. Menon, Y. Bichpuriya, V. Sarangan, Narayanan Rajagopal

{"title":"A Best-effort Energy Storage as a Service Model for Supporting Renewable Generators in Day-ahead Electricity Markets","authors":"Vishnu P. Menon, Y. Bichpuriya, V. Sarangan, Narayanan Rajagopal","doi":"10.1145/3575813.3597355","DOIUrl":"https://doi.org/10.1145/3575813.3597355","url":null,"abstract":"Net zero targets are encouraging higher adoption of Renewable Energy Generators (REGens). The volatile nature of these sources introduces challenges such as reliability of supply and grid stability. Energy storage systems (ESS) are viewed as a solution to address these challenges at both grid-scale renewable generation and smaller distributed generation. In this paper, we propose a model for an ESS to offer its storage to multiple, independently-managed, third-party REGens participating in the day-ahead electricity markets. In anticipation of the forecast errors from these disparate REGens, the ESS operator takes suitable counter-measures (charging/ discharging of the storage system through market transactions). This is done in a way to reduce the imbalance in the market commitments made by the individual REGens without reserving any storage volume for each REGen. For this service, the ESS gets paid from each of the REGens. We call this set-up as a “best-effort energy storage as a service (ESaaS)”. To the best of our knowledge, ours is one of the very few papers to discuss this set-up. We present strategies for pricing and operating such an ESaaS system. Empirical results using real world data indicate that the proposed set-up is beneficial for both REGens and ESS operators. It also reduces the total imbalance (of REGens and ESS) thus aiding the system operator as well.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132605469","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

Energy vs Privacy: Estimating the Ecological Impact of Federated Learning 能源vs隐私:估算联邦学习的生态影响

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3597344

René Schwermer, R. Mayer, H. Jacobsen

{"title":"Energy vs Privacy: Estimating the Ecological Impact of Federated Learning","authors":"René Schwermer, R. Mayer, H. Jacobsen","doi":"10.1145/3575813.3597344","DOIUrl":"https://doi.org/10.1145/3575813.3597344","url":null,"abstract":"The increasing usage of edge devices and stricter data privacy regulations motivate the use of federated learning (FL). At the same time, more and more stakeholders are concerned about the ecological impact of machine learning and its associate network traffic. The current research in FL does not investigate the impact of different network constraints and privacy-enhancing techniques, such as differential privacy, on the network traffic and energy consumption of the clients. Most experiments run either on virtual machines or on one machine with simulated clients. In such environments, it is challenging to measure each client’s network and energy usage. Therefore, we built our \"Distributed Edge Device Testbed\" (DEDT) and evaluate a convolutional neural network trained on the MNIST data set under different network constraints on DEDT, with differential privacy and with an increasing amount of participating clients. For each experiment, we quantify the network traffic, energy consumption, and training time. The results show the importance of experiments on physically separated nodes and the need to improve software-based power monitoring. The estimated energy consumption deviates by up to 35 % from the measured ones. The accuracy of the estimated network traffic depends on the monitored network interface and gives an error of 18 % for virtual machines in combination with monitoring the Ethernet interface. The training time also increases linearly with the number of participating clients.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130431033","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 Shapley value-based Distributed AC OPF Approach for Redispatch Congestion Cost Allocation 基于Shapley值的分布式AC OPF重调度拥塞费用分配方法

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3576881

Rebecca Bauer, Xinliang Dai, V. Hagenmeyer

{"title":"A Shapley value-based Distributed AC OPF Approach for Redispatch Congestion Cost Allocation","authors":"Rebecca Bauer, Xinliang Dai, V. Hagenmeyer","doi":"10.1145/3575813.3576881","DOIUrl":"https://doi.org/10.1145/3575813.3576881","url":null,"abstract":"The progressing energy transition induces a growing need for redispatch congestion management, and, thereby, a fair distribution of its respective costs among the different system operators. In this light, a very recent paper uses the Shapley value as such a fair allocation rule to assign redispatch congestion costs to system operators. However, this approach is based on DC optimal power flow (OPF) and requires the sharing of detailed grid models from all system operators. This is not preferred by them due to data privacy concerns. W.r.t. real-world implementation, the present paper extends the method by using AC OPF problem formulations for more realistic results, and solving them by using a distributed optimization algorithm, i.e., Augmented Lagrangian based Alternating Direction Inexact Newton method (aladin), for preserving data privacy. Simulation results of an illustrative example show great potential of the proposed distributed approach in the aspects of both solution accuracy and computing time. This makes the presented approach generically feasible for real applications in the energy transition.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134468546","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

Uncertain FlexOffers: a scalable, uncertainty-aware model for energy flexibility 不确定柔性报价:一个可扩展的，不确定性意识模型的能源灵活性

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3576873

F. Lilliu, T. Pedersen, Laurynas Siksnys, B. Neupane

{"title":"Uncertain FlexOffers: a scalable, uncertainty-aware model for energy flexibility","authors":"F. Lilliu, T. Pedersen, Laurynas Siksnys, B. Neupane","doi":"10.1145/3575813.3576873","DOIUrl":"https://doi.org/10.1145/3575813.3576873","url":null,"abstract":"As the usage of Renewable Energy Sources (RES) in electricity grids increases in popularity, energy flexibility has a crucial role. The most common weaknesses of current flexibility models are: i) being hard-coded for specific devices, ii) not scaling for long time horizons and many devices, iii) losing a lot of flexibility if the model is approximated, and iv) not considering the uncertainty affecting flexibility representations, which causes the model to capture too much excess flexibility when imbalance penalties are high. The FlexOffer (FO) model can perform approximations of flexibility with good accuracy across different devices, and scales well to long time horizons and many devices: this work extends FOs to uncertain FOs (UFOs), which keep the good properties while capturing uncertainty. We show that UFOs are very fast by performing optimization in under 5.27 seconds for a 24 hours time horizon, while exact models use more than 29.05 hours for even a 6 hours 15 minutes time horizon, making them totally infeasible in practice. UFOs can capture more flexibility than other uncertain models: UFOs considering energy dependencies can model flexibility without losses for a charging battery, and retain of the total flexibility for batteries and for EVs when imbalance penalties are high, compared to and respectively for other models. UFOs allow to aggregate up to 6000 loads for up to 96 time units while retaining of the total flexibility: exact models fail already for 330 loads or 21 time units.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123474436","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

Adversarial Attacks on Machine Learning-Based State Estimation in Power Distribution Systems 基于机器学习的配电系统状态估计的对抗性攻击

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3597352

Afia Afrin, Omid Ardakanian

引用次数: 0

Optimizing Demand Response in Distribution Network with Grid Operational Constraints 考虑电网运行约束的配电网需求响应优化

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3595206

Tianyu Zhao, Min Zhou, Yanfang Mo, Jason Min Wang, Jun Luo, Xiang Pan, Minghua Chen

{"title":"Optimizing Demand Response in Distribution Network with Grid Operational Constraints","authors":"Tianyu Zhao, Min Zhou, Yanfang Mo, Jason Min Wang, Jun Luo, Xiang Pan, Minghua Chen","doi":"10.1145/3575813.3595206","DOIUrl":"https://doi.org/10.1145/3575813.3595206","url":null,"abstract":"Despite the extensive studies on end-user participation in distribution networks, incorporating grid operational constraints and the incentive/dynamic pricing in demand response (DR) is still a challenging and open problem. To fill this gap, we propose a novel three-stage game framework to enable the DR among the utility company, distribution system operator (DSO), and prosumers. In Stage I, utility determines the incentive price to DSO for social welfare maximization. In Stage II, DSO decides the dynamic prices to prosumers and respects grid operational constraints. In Stage III, each prosumer adjusts the local generation and demand on its behalf. We show that the DR game admits an equilibrium that maximizes social welfare and DSO/prosumers’ benefits while satisfying operational constraints. We prove the uniqueness of the optimal power supply of utility and the demand-generation adjustments and derive the explicit form of optimal incentive/dynamic price-setting at equilibrium. We further develop a robustness-enhanced design against DSO/prosumers’ fault information and explore the impact of renewable/uncontrollable load uncertainty. Meanwhile, we develop an efficient distributed algorithm to help DR participants cooperatively reach equilibrium. Simulations show that the proposed scheme improves social welfare by 20.1% and DSO/prosumers’ benefit by 32.5% on IEEE 30/118-bus systems while respecting all grid operational constraints.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131513791","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

Budget-constrained optimal and equitable retrofitting problems for achieving energy efficiency 实现能源效率的预算约束的最优和公平的改造问题

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3597354

Aparna Kishore, S. Thorve, M. Marathe

引用次数: 0

Fingerprinting Battery Health Using Relaxing Voltages 使用放松电压识别电池健康状况

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3576875

Liang He, K. Shin

{"title":"Fingerprinting Battery Health Using Relaxing Voltages","authors":"Liang He, K. Shin","doi":"10.1145/3575813.3576875","DOIUrl":"https://doi.org/10.1145/3575813.3576875","url":null,"abstract":"Mobile devices are only as useful as their battery lasts. Unfortunately, the operation and life of a mobile device’s battery degrade over time and usage. The state-of-health (SoH) of batteries quantifies their degradation, but mobile devices are unable to support its accurate estimation — despite its importance — due mainly to their limited hardware and dynamic usage patterns, causing various problems such as unexpected device shutoffs or even fire/explosion. To remedy this lack of support, we design, implement and evaluate V-Health, a low-cost user-level SoH estimation service for mobile devices based only on their battery voltage, which is universally available on all commodity mobile devices. The design of V-Health is inspired by our empirical finding that the relaxing voltages of a device battery fingerprint its SoH, and is steered by extensive measurements with 15 batteries used for various commodity mobile devices, such as iPhone 6 Plus, Nexus 6P, Galaxy S3, etc. These measurements consist of 13,377 battery discharging/charging/resting cycles and have been conducted over 72 months cumulatively. V-Health has been evaluated via both laboratory experiments and field-tests with multiple Android devices over 4–6 months, showing < error in SoH estimation.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116565359","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 Data-Driven and Human-Centric EV Charging Recommendation System at City-Scale 数据驱动、以人为本的城市电动汽车充电推荐系统

Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-16 DOI: 10.1145/3575813.3597350

Jingping Nie, S. Xia, Yanchen Liu, Shengxuan Ding, Lanxiang Hu, Minghui Zhao, Yuang Fan, M. Abdel-Aty, M. Preindl, Xiaofan Jiang

{"title":"A Data-Driven and Human-Centric EV Charging Recommendation System at City-Scale","authors":"Jingping Nie, S. Xia, Yanchen Liu, Shengxuan Ding, Lanxiang Hu, Minghui Zhao, Yuang Fan, M. Abdel-Aty, M. Preindl, Xiaofan Jiang","doi":"10.1145/3575813.3597350","DOIUrl":"https://doi.org/10.1145/3575813.3597350","url":null,"abstract":"Electric vehicles (EVs) have gained widespread popularity in recent years, and the scheduling and routing of EV charging have impacted the welfare of both EV drivers and the grid. In this paper, we present a practical, data-driven, and human-centric EV charging recommendation system at the city-scale based on deep reinforcement learning (DRL). The system co-optimizes the welfare of both the EV drivers and the grid. We augmented and aggregated data from various sources, including public data, location-based data companies, and government authorities, with different formats and time granularities. The data includes EV charger information, grid capacity, EV driving behavior information, and city-scale mobility. We created a 30-day per-minute unified EV charger information dataset with charging prices and grid capacity, as well as an EV driving behavior dataset with location and State of Charge (SoC) information. Our evaluation of the recommendation system shows that it is able to provide recommendations that reduce the average driver-to-charger distance and minimize the number of times chargers switch to a different driver. The dataset we prepared for training the DRL agent, including augmented EV driving data and charging station information, will be open-sourced to benefit future research in the community.","PeriodicalId":359352,"journal":{"name":"Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122176345","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