Proceedings of the Eleventh ACM International Conference on Future Energy Systems最新文献_第7页

Reinforcement Learning based HVAC Optimization in Factories 基于强化学习的工厂暖通空调优化

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-06-12 DOI: 10.1145/3396851.3402363

Debmalya Biswas

引用次数: 4

The Conception of an Urban Energy Dashboard using 3D City Models 使用3D城市模型的城市能源仪表板的概念

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-06-12 DOI: 10.1145/3396851.3402650

P. Würstle, T. Santhanavanich, R. Padsala, V. Coors

{"title":"The Conception of an Urban Energy Dashboard using 3D City Models","authors":"P. Würstle, T. Santhanavanich, R. Padsala, V. Coors","doi":"10.1145/3396851.3402650","DOIUrl":"https://doi.org/10.1145/3396851.3402650","url":null,"abstract":"In this paper, we present a concept for an urban energy dashboard built using different Open Geospatial Consortium (OGC) standards integrated with 3D city models. With cities continuously pressed to cut upon their carbon emissions, it becomes vital to visualize different energy data under one application. This perfectly fits our vision of developing an interactive web-based urban energy dashboard, which shows not only static data but also real-time dynamic data such as measured data from sensors, all integrated into 3D city models. Evolution of the mentioned dashboard is presented using three different case study regions based on data availability and its urban scale: 1) Landkreis Ludwigsburg - A district in Baden Württemberg, Germany showing static urban energy data of specific heating demand 2) Brooklyn - A borough in New York City showing urban energy data of specific heating demand (incl. domestic hot water) over a temporal resolution of 5 years and 3) Wüstenrot - A small municipality in Germany showing real-time dynamic energy data streaming from sensors integrated into a 3D city model. Such an interactive dashboard presents both static and dynamic urban energy data to the citizens and city administration in the most straightforward yet effective manner.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123321280","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: 9

The Long-term Cost of Energy Generation 能源生产的长期成本

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-06-12 DOI: 10.1145/3396851.3397685

Jimmy Horn, Yutong Wu, Ali Khodabakhsh, E. Nikolova, Emmanouil Pountourakis

{"title":"The Long-term Cost of Energy Generation","authors":"Jimmy Horn, Yutong Wu, Ali Khodabakhsh, E. Nikolova, Emmanouil Pountourakis","doi":"10.1145/3396851.3397685","DOIUrl":"https://doi.org/10.1145/3396851.3397685","url":null,"abstract":"We propose a method to minimize the long-term cost of energy generation while improving grid stability. Currently, the cost of energy generation is minimized myopically (day by day) via the economic dispatch problem, which i) does not internalize the effects of generation variability, ii) does not account for the long-term effects of losing too many existing (paid off) conventional plants, and iii) has the detrimental impact of not systematically maintaining grid inertia. The current dispatch solution favors low cost but inherently more variable renewables, which require intermittent back-up from either conventionals or expensive peakers. We first propose our Augmented Dispatch for Inertia method which incorporates the cost of maintaining grid inertia stability directly in the economic dispatch selection, thus more accurately capturing the impact of renewable energy growth and conventional plant retirements. Second, to address the long-term loss of conventional plants due to their underuse, we propose our Balanced Dispatch algorithm that selects key, future-needed conventional generators with enough frequency to maintain their viability. We show via simulation that our methods result in substantially lower long-term generation cost and a notable increase in grid resilience.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124248235","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: 2

Optimal Sizing of Hybrid Renewable Energy Sources via Efficient Demand Response in Microgrid 基于微电网高效需求响应的混合可再生能源最优规模

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-06-12 DOI: 10.1145/3396851.3403516

Nilotpal Chakraborty, E. Kalaimannan

引用次数: 0

Flexible Redundancy Generation for Virtual Network Embedding with an Application to Smart Grids 虚拟网络嵌入的柔性冗余生成及其在智能电网中的应用

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-06-12 DOI: 10.1145/3396851.3397693

A. Santos, Amr Rizk, Florian Steinke

{"title":"Flexible Redundancy Generation for Virtual Network Embedding with an Application to Smart Grids","authors":"A. Santos, Amr Rizk, Florian Steinke","doi":"10.1145/3396851.3397693","DOIUrl":"https://doi.org/10.1145/3396851.3397693","url":null,"abstract":"Embedding applications consisting of interconnected logical function blocks, denoted Virtual Network Requests (VNR), onto physical compute and communication networks, denoted Substrate Networks (SN), allows for the automatic generation of a variable degree of redundancy. The need for this feature arises for instance in smart power distribution grids with many decentral devices. Their heterogeneous communication interconnections often feature low reliability and face frequently changing conditions. At the same time, high service reliability is required for critical applications such as voltage control. In this work, we show how to detect potential voltage violations in a medium voltage feeder with high probability at low monitoring cost. We employ a probabilistic power flow model to determine the time-dependent required reliability for the links of voltage monitoring VNRs and embed it onto a SN consisting of a mix of plausible smart grid communication technologies. We use a novel approach based on chance-constrained mixed integer linear programming to generate a minimal, but sufficient degree of redundancy. This allows for optimal resource usage of the SN, flexibility to adapt the embedding in case of changes of the VNR or SN parameters, and reduced design efforts in comparison to manual redundancy planning. Compared with a static redundancy setup, the operational communication costs can be more than halved in our simulation experiments.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125035081","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

Uberizing the Charging Ecosystem for Electric Vehicles 优步化电动汽车充电生态系统

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-06-12 DOI: 10.1145/3396851.3397758

A. Krishna, A. Narayanan, S. Krishnakumar, P. Misra, Arunchandar Vasan, V. Sarangan, A. Sivasubramaniam

{"title":"Uberizing the Charging Ecosystem for Electric Vehicles","authors":"A. Krishna, A. Narayanan, S. Krishnakumar, P. Misra, Arunchandar Vasan, V. Sarangan, A. Sivasubramaniam","doi":"10.1145/3396851.3397758","DOIUrl":"https://doi.org/10.1145/3396851.3397758","url":null,"abstract":"In many metropolitan cities, multi-unit residential buildings (MURB) are becoming more common than single-family independent homes due to lack of urban space. MURB residents (around 42% in Europe) are potential adopters of electric vehicles (EV), but lack a private garage for EV charging. They need to exclusively rely on public charging, which currently serves only 5% of EVs. As EVs become more prevalent, the lack of extensive public charging can create a short-term demand-supply mismatch in specific city neighbourhoods, as well as preclude long-term growth in EV adoption. We believe that uberization of private garage chargers that are typically under-utilized during day-time can alleviate this problem. In this work, we examine how a charging service provider can match public charging demand with private suppliers while using a demand-response based pricing model. We base our study on real-world traffic patterns for the city of Luxembourg by augmenting the Luxembourg SUMO traffic scenario (LuST) simulator. Specifically, an EV's charging demand is modeled by a state machine with charge/discharge dynamics based on Tesla Model-S. Our preliminary results suggest that the proposed uberization strategy has the potential to gracefully handle demand spikes with higher revenue yield for a charging service provider, even while handling different categories of service users.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"354 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133174270","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

Optimizing carbon tax for decentralized electricity markets using an agent-based model 基于代理模型的分散电力市场碳税优化

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-05-28 DOI: 10.1145/3396851.3402369

Alexander J. M. Kell, A. McGough, M. Forshaw

{"title":"Optimizing carbon tax for decentralized electricity markets using an agent-based model","authors":"Alexander J. M. Kell, A. McGough, M. Forshaw","doi":"10.1145/3396851.3402369","DOIUrl":"https://doi.org/10.1145/3396851.3402369","url":null,"abstract":"Averting the effects of anthropogenic climate change requires a transition from fossil fuels to low-carbon technology. A way to achieve this is to decarbonize the electricity grid. However, further efforts must be made in other fields such as transport and heating for full decarbonization. This would reduce carbon emissions due to electricity generation, and also help to decarbonize other sources such as automotive and heating by enabling a low-carbon alternative. Carbon taxes have been shown to be an efficient way to aid in this transition. In this paper, we demonstrate how to to find optimal carbon tax policies through a genetic algorithm approach, using the electricity market agent-based model ElecSim. To achieve this, we use the NSGA-II genetic algorithm to minimize average electricity price and relative carbon intensity of the electricity mix. We demonstrate that it is possible to find a range of carbon taxes to suit differing objectives. Our results show that we are able to minimize electricity cost to below £10/MWh as well as carbon intensity to zero in every case. In terms of the optimal carbon tax strategy, we found that an increasing strategy between 2020 and 2035 was preferable. Each of the Pareto-front optimal tax strategies are at least above £81/tCO2 for every year. The mean carbon tax strategy was £240/tCO2.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"2 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134577744","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

Emission-aware Energy Storage Scheduling for a Greener Grid 基于排放意识的绿色电网储能调度

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-05-25 DOI: 10.1145/3396851.3397755

Rishikesh Jha, Stephen Lee, Srinivasan Iyengar, M. Hajiesmaili, David E. Irwin, P. Shenoy

{"title":"Emission-aware Energy Storage Scheduling for a Greener Grid","authors":"Rishikesh Jha, Stephen Lee, Srinivasan Iyengar, M. Hajiesmaili, David E. Irwin, P. Shenoy","doi":"10.1145/3396851.3397755","DOIUrl":"https://doi.org/10.1145/3396851.3397755","url":null,"abstract":"Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions --- equivalent to a drop of 23.3% in our electric grid emissions.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115890255","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: 8

Peak Forecasting for Battery-based Energy Optimizations in Campus Microgrids 校园微电网基于电池的能量优化峰值预测

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-05-25 DOI: 10.1145/3396851.3397751

Akhil Soman, Amee Trivedi, David E. Irwin, B. Kosanovic, B. McDaniel, P. Shenoy

引用次数: 11

Pareto-optimal energy sharing between battery-equipped renewable generators 配备电池的可再生发电机之间的帕累托最优能量共享

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-05-19 DOI: 10.1145/3396851.3397740

Vivek Deulkar, J. Nair

引用次数: 1