Companion Proceedings of the 14th ACM International Conference on Future Energy Systems最新文献

Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid 迈向数据鸿沟:美国电网项目驱动的分布式能源数据集

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600250

R. Haider, Yixing Xu, Weiwei Yang

引用次数: 0

EXARL-PARS: Parallel Augmented Random Search Using Reinforcement Learning at Scale for Applications in Power Systems 基于大规模强化学习的并行增强随机搜索在电力系统中的应用

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600261

Himanshu Sharma, Joshua D. Suetterlein, Sumathi Lakshmiranganatha, T. Flynn, D. Vrabie, Christine M. Sweeney, V. Ramakrishniah

引用次数: 0

Data-Driven Co-optimization of Energy Efficiency and Indoor Environmental Quality in Commercial Buildings 数据驱动的商业建筑能效与室内环境质量协同优化

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600262

S. A. R. Naqvi, V. Chandan, S. Bhattacharya, Na Luo, K. Kar, C. Sivaraman, Nikitha Radhakrishnan

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Investigating the Impact of Space Allocation Strategy on Energy-Comfort Trade-off in Office Buildings 办公建筑空间配置策略对能源舒适权衡的影响研究

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600263

Tianyu Zhang, Omid Ardakanian

{"title":"Investigating the Impact of Space Allocation Strategy on Energy-Comfort Trade-off in Office Buildings","authors":"Tianyu Zhang, Omid Ardakanian","doi":"10.1145/3599733.3600263","DOIUrl":"https://doi.org/10.1145/3599733.3600263","url":null,"abstract":"With the global push to decarbonize the building sector and growing interest in occupant-centric building controls, numerous simulation and field studies have been conducted to explore the trade-off between energy efficiency and occupant comfort. These studies largely disregard individual differences in thermal comfort and assume each zone has a fixed occupancy schedule. In office buildings, there is often some leeway in how occupants are grouped and assigned to different building spaces (e.g., offices and meeting rooms). In this paper we investigate the extent of the impact of the space allocation strategy on the energy-comfort trade-off in office buildings, and whether it depends on specific building characteristics. Our simulation shows that varying the space allocation strategy in a medium office building can lead to over 3.5%/15.1% change in annual/monthly energy consumption, and over 15% change in average thermal comfort when using the personal comfort model. This finding calls for the joint optimization of HVAC operation and space allocation, possibly at different timescales.","PeriodicalId":114998,"journal":{"name":"Companion Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115729312","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

The Impact of Forecast Characteristics on the Forecast Value for the Dispatchable Feeder 预测特性对可调度馈线预测值的影响

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600251

Dorina Werling, Maximilian Beichter, Benedikt Heidrich, Kaleb Phipps, R. Mikut, V. Hagenmeyer

{"title":"The Impact of Forecast Characteristics on the Forecast Value for the Dispatchable Feeder","authors":"Dorina Werling, Maximilian Beichter, Benedikt Heidrich, Kaleb Phipps, R. Mikut, V. Hagenmeyer","doi":"10.1145/3599733.3600251","DOIUrl":"https://doi.org/10.1145/3599733.3600251","url":null,"abstract":"Transforming the energy system to decentralised, renewable energy sources requires measures to balance their fluctuating nature and stabilise the energy system. One such measure is a dispatchable feeder, which combines inflexible prosumption with a flexible energy storage system. The energy storage system’s management is formulated as a stochastic optimisation problem that requires energy time series forecasts as input. These forecasts can significantly influence the performance of the dispatchable feeder: the forecasts have a so-called forecast value for the dispatchable feeder, which is not directly reflected by error-based forecast quality metrics. Therefore, we analyse how the considered forecast value for the dispatchable feeder is related to the considered forecast quality and influenced by forecasts with different characteristics. Furthermore, we examine the impact of problem-specific parameters such as the data and the battery capacity. To this means, we create forecasts with different characteristics using neural networks with varying loss functions and perform the analysis using a data set with 300 buildings. The results of our analysis show that the relation between the considered forecast quality and forecast value for the dispatchable feeder is non-monotonic. Furthermore, we show that the forecast characteristics influence the forecast value differently depending on the data and the battery capacity.","PeriodicalId":114998,"journal":{"name":"Companion Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114737961","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

Exploring of Recursive Model-based Non-Intrusive Thermal Load Monitoring for Building Cooling Load 基于递归模型的建筑冷负荷非侵入式监测方法探讨

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600259

Kazuki Okazawa, Naoya Kaneko, Dafang Zhao, Hiroki Nishikawa, Ittetsu Taniguchi, Takao Onoye

引用次数: 0

Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between? 用生成模型综合建筑运行数据:VAEs、GANs还是介于两者之间?

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600260

Alessandro Salatiello, Ye Wang, G. Wichern, T. Koike-Akino, Yoshihiro Ohta, Yosuke Kaneko, C. Laughman, A. Chakrabarty

{"title":"Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between?","authors":"Alessandro Salatiello, Ye Wang, G. Wichern, T. Koike-Akino, Yoshihiro Ohta, Yosuke Kaneko, C. Laughman, A. Chakrabarty","doi":"10.1145/3599733.3600260","DOIUrl":"https://doi.org/10.1145/3599733.3600260","url":null,"abstract":"The generation of time-series profiles of building operation requires expensive and time-consuming data consolidation and modeling efforts that rely on extensive domain knowledge and need frequent revisions due to evolving energy systems, user behavior, and environmental conditions. Generative deep learning may be used to provide an automatic, scalable, data-source-agnostic, and efficient method to synthesize these artificial time-series profiles by learning the distribution of the original data. While a range of generative neural networks have been proposed, generative adversarial networks (GANs) and variational autoencoders (VAEs) are most popular models; GANs typically require considerable customization to stabilize the training procedure, while VAEs are often reported to generate lower-quality samples compared to GANs. In this paper, we propose a network architecture and training procedure that combines the strengths of VAEs and GANs by incorporating Regularized Adversarial Fine-Tuning (RAFT). We imbue the architecture with conditional inputs to reflect ambient/outdoor conditions and operating conditions, and demonstrate its effectiveness by using operational data collected over 585 days from SUSTIE: Mitsubishi Electric’s net-zero energy building. Comparing against classical GAN, VAE, Wasserstein-GAN, and VAE-GAN, our proposed conditional RAFT-VAE-GAN outperforms its competitors in terms of mean accuracy, training stability, and several metrics that ascertain how close the synthetic distribution is to the measured data distribution.","PeriodicalId":114998,"journal":{"name":"Companion Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"123 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132518336","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

Leveraging Solar PV and Storage for Deep Decarbonization of Residential Heating Systems 利用太阳能光伏和储能技术实现住宅供暖系统的深度脱碳

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3606302

Anupama Sitaraman, Noman Bashir, David E. Irwin, P. Shenoy

引用次数: 0

Exploring Models of Electricity Price Forecasting: Case Study on A FCAS Market 电价预测模型探索:以FCAS市场为例

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600258

Kenshiro Kato, Koki Iwabuchi, Daichi Watari, Dafang Zhao, Hiroki Nishikawa, Ittetsu Taniguchi, Takao Onoye

{"title":"Exploring Models of Electricity Price Forecasting: Case Study on A FCAS Market","authors":"Kenshiro Kato, Koki Iwabuchi, Daichi Watari, Dafang Zhao, Hiroki Nishikawa, Ittetsu Taniguchi, Takao Onoye","doi":"10.1145/3599733.3600258","DOIUrl":"https://doi.org/10.1145/3599733.3600258","url":null,"abstract":"VPPs (Virtual Power Plants) play an important role in balancing supply and demand. In order to make VPP revenue, it is necessary to forecast market prices and bidding energy for supply and demand adjustment markets, called FCAS (Frequency Control Ancillary Service) markets. However, price forecasting for FCAS markets is still challenging because they have multiple different response times and one price, directly and indirectly, influences each other. There is no study on electricity price forecasting in FCAS markets, and a novel forecasting model considering not only its price but also the other prices of the different response times is necessary. This work presents a market price forecasting model for a FCAS market by exploring the forecasting models derived from a wholesale market, and then it takes into account the markets with different response times as well as the target one from AEMO (Australian Energy Market Operator). Through the experiments, our forecasting model achieves 7.8$/MWh of RMSE on the electricity price in AEMO’s 6-Second-Raise market. The proposed forecasting model reduces RMSE by 80% compared to the forecast price published by AEMO.","PeriodicalId":114998,"journal":{"name":"Companion Proceedings of the 14th ACM International Conference on Future Energy Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121243175","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

Cost Optimization for the Edge-Cloud Continuum by Energy-Aware Workload Placement 基于能量感知工作负载配置的边缘云连续体成本优化

Companion Proceedings of the 14th ACM International Conference on Future Energy Systems Pub Date : 2023-06-20 DOI: 10.1145/3599733.3600253

Rickard Brännvall, Tina Stark, Jonas Gustafsson, Mats Eriksson, J. Summers

引用次数: 0