Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115401
Xiwang Li, Jin Wen, E. Bai
Buildings, consuming over 70% of the electricity in the U.S., play significant roles in smart grid infrastructure. The automatic operation of buildings and their subsystems in responding to signals from a smart grid is essential to reduce energy consumption and demand, as well as improve the resilience to power disruptions. In order to achieve such automatic operation, high fidelity and computationally efficiency building energy forecasting models under different weather and operation conditions are needed. Currently, data-driven (black box) models and hybrid (grey box) models are commonly used in model based building control operation. However, typical black box models often require long training period and are bounded to weather and operation conditions during the training period. On the other hand, creating a grey box model often requires long calculation time due to parameter optimization process and expert knowledge during the model structure determining and simplification process. An earlier study by the authors proposed a system identification approach to develop computationally efficient and accurate building energy forecasting models. This paper attempts to extend this early study and to quantitatively evaluate how the most important characteristics of a building energy system: its nonlinearity and response time, affect the system identification process and model accuracy. Two commercial building: a small-size and a medium-size commercial building, with varying chiller nonlinearity, are simulated using EnergyPlus in lieu of real buildings for model development and validation. The system identification method proposed in the early study is applied to these two buildings that have varying nonlinearity and response time. Adaption of the proposed system identification method based on systems' nonlinearity and response time is proposed in this study. The energy forecasting results demonstrate that the adaption is capable of significantly improve the performance of the system identification model.
{"title":"Building energy forecasting using system identification based on system characteristics test","authors":"Xiwang Li, Jin Wen, E. Bai","doi":"10.1109/MSCPES.2015.7115401","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115401","url":null,"abstract":"Buildings, consuming over 70% of the electricity in the U.S., play significant roles in smart grid infrastructure. The automatic operation of buildings and their subsystems in responding to signals from a smart grid is essential to reduce energy consumption and demand, as well as improve the resilience to power disruptions. In order to achieve such automatic operation, high fidelity and computationally efficiency building energy forecasting models under different weather and operation conditions are needed. Currently, data-driven (black box) models and hybrid (grey box) models are commonly used in model based building control operation. However, typical black box models often require long training period and are bounded to weather and operation conditions during the training period. On the other hand, creating a grey box model often requires long calculation time due to parameter optimization process and expert knowledge during the model structure determining and simplification process. An earlier study by the authors proposed a system identification approach to develop computationally efficient and accurate building energy forecasting models. This paper attempts to extend this early study and to quantitatively evaluate how the most important characteristics of a building energy system: its nonlinearity and response time, affect the system identification process and model accuracy. Two commercial building: a small-size and a medium-size commercial building, with varying chiller nonlinearity, are simulated using EnergyPlus in lieu of real buildings for model development and validation. The system identification method proposed in the early study is applied to these two buildings that have varying nonlinearity and response time. Adaption of the proposed system identification method based on systems' nonlinearity and response time is proposed in this study. The energy forecasting results demonstrate that the adaption is capable of significantly improve the performance of the system identification model.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123411283","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115398
Velin Kounev, D. Tipper, M. Lévesque, B. Grainger, T. Mcdermott, G. Reed
Microgrids have been proposed as a key piece of the Smart Grid vision to enable the potential of renewable energy generation. Microgrids are required to operate in both grid connected and standalone island mode using local sources of power. A major challenge in implementing microgrids is the communications and control to support transition to and from grid connected mode and operation in island mode. Microgrids consists of two interdependent networks, namely; the power distribution and data communication networks. To accurately capture the overall operation of the system, we propose a co-simulation model driven by embedded power controllers. Further, we propose a novel co-simulation scheduler taking into account events from both the power and communication network simulators, as well as the timing of each embedded controller's execution loop to adaptively synchronize both simulators efficiently. The approach ensures minimal synchronization error while still providing the ability to simulate extended operational scenarios. The numerical results illustrate the novelty of the propose co- simulation to study the microgrid power and communication networks interactions, and the effect on the power stability.
{"title":"A microgrid co-simulation framework","authors":"Velin Kounev, D. Tipper, M. Lévesque, B. Grainger, T. Mcdermott, G. Reed","doi":"10.1109/MSCPES.2015.7115398","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115398","url":null,"abstract":"Microgrids have been proposed as a key piece of the Smart Grid vision to enable the potential of renewable energy generation. Microgrids are required to operate in both grid connected and standalone island mode using local sources of power. A major challenge in implementing microgrids is the communications and control to support transition to and from grid connected mode and operation in island mode. Microgrids consists of two interdependent networks, namely; the power distribution and data communication networks. To accurately capture the overall operation of the system, we propose a co-simulation model driven by embedded power controllers. Further, we propose a novel co-simulation scheduler taking into account events from both the power and communication network simulators, as well as the timing of each embedded controller's execution loop to adaptively synchronize both simulators efficiently. The approach ensures minimal synchronization error while still providing the ability to simulate extended operational scenarios. The numerical results illustrate the novelty of the propose co- simulation to study the microgrid power and communication networks interactions, and the effect on the power stability.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126220605","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115408
Avik Dayal, A. Tbaileh, Yi Deng, S. Shukla
The economic machinery of the United States is reliant on complex large-scale cyber-physical systems which include electric power grids, oil and gas systems, transportation systems, etc. Protection of these systems and their control from security threats and improvement of the robustness and resilience of these systems, are important goals. Since all these systems have Supervisory Control and Data Acquisition (SCADA) in their control centers, a number of test beds have been developed at various laboratories. Usually on such test beds, people are trained to operate and protect these critical systems. In this paper, we describe a virtualized distributed test bed that we developed for modeling and simulating SCADA applications and to carry out related security research. The test bed is a virtualized by integrating various heterogeneous simulation components. This test bed can be reconfigured to simulate the SCADA of a power system, or a transportation system or any other critical systems, provided a back-end domain specific simulator for such systems are attached to it. In this paper, we describe how we created a scalable architecture capable of simulating larger infrastructures and by integrating communication models to simulate different network protocols. We also developed a series of middleware packages that integrates various simulation platforms into our test bed using the Python scripting language. To validate the usability of the test bed, we briefly describe how a power system SCADA scenario can be modeled and simulated in our test bed.
{"title":"Distributed VSCADA: An integrated heterogeneous framework for power system utility security modeling and simulation","authors":"Avik Dayal, A. Tbaileh, Yi Deng, S. Shukla","doi":"10.1109/MSCPES.2015.7115408","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115408","url":null,"abstract":"The economic machinery of the United States is reliant on complex large-scale cyber-physical systems which include electric power grids, oil and gas systems, transportation systems, etc. Protection of these systems and their control from security threats and improvement of the robustness and resilience of these systems, are important goals. Since all these systems have Supervisory Control and Data Acquisition (SCADA) in their control centers, a number of test beds have been developed at various laboratories. Usually on such test beds, people are trained to operate and protect these critical systems. In this paper, we describe a virtualized distributed test bed that we developed for modeling and simulating SCADA applications and to carry out related security research. The test bed is a virtualized by integrating various heterogeneous simulation components. This test bed can be reconfigured to simulate the SCADA of a power system, or a transportation system or any other critical systems, provided a back-end domain specific simulator for such systems are attached to it. In this paper, we describe how we created a scalable architecture capable of simulating larger infrastructures and by integrating communication models to simulate different network protocols. We also developed a series of middleware packages that integrates various simulation platforms into our test bed using the Python scripting language. To validate the usability of the test bed, we briefly describe how a power system SCADA scenario can be modeled and simulated in our test bed.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125796211","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115405
M. Heiss, Andreas Oertl, Monika Sturm, P. Palensky, Stefan Vielguth, F. Nadler
The full potential of distributed cyber-physical systems (CPS) can only be leveraged if their functions and services can be flexibly integrated. Challenges like communication quality, interoperability, and amounts of data are massive. The design of such integration platforms therefore requires radically new concepts. This paper shows the industrial view, the business perspective on such envisioned platforms. It turns out that there are not only huge technical challenges to overcome but also fundamental dilemmas. Contradicting requirements and conflicting trends force us to re-think the task of interconnecting services of distributed CPS.
{"title":"Platforms for industrial cyber-physical systems integration: contradicting requirements as drivers for innovation","authors":"M. Heiss, Andreas Oertl, Monika Sturm, P. Palensky, Stefan Vielguth, F. Nadler","doi":"10.1109/MSCPES.2015.7115405","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115405","url":null,"abstract":"The full potential of distributed cyber-physical systems (CPS) can only be leveraged if their functions and services can be flexibly integrated. Challenges like communication quality, interoperability, and amounts of data are massive. The design of such integration platforms therefore requires radically new concepts. This paper shows the industrial view, the business perspective on such envisioned platforms. It turns out that there are not only huge technical challenges to overcome but also fundamental dilemmas. Contradicting requirements and conflicting trends force us to re-think the task of interconnecting services of distributed CPS.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131287490","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115397
Wolfgang Muller, E. Widl
The simulation of hybrid system is of interest in different areas, e.g., cyber-physical energy systems. This includes the embedding of continuous-time subsystems in discrete event systems. The difficulties of resulting synchronisation schedules are approached by precalculation within the components. The Functional Mock-up Interface (FMI) is a state of the art specification for the co-simulation of continuous systems, which is supported by a growing number of simulation software. FMI for Model Exchange components generated with OpenModelica have been embedded in the discrete event domain of Ptolemy II as a proof of concept. An example shows that the use of FMI components has a better scalability and shorter runtime than a pure Ptolemy II implementation.
{"title":"Using FMI components in discrete event systems","authors":"Wolfgang Muller, E. Widl","doi":"10.1109/MSCPES.2015.7115397","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115397","url":null,"abstract":"The simulation of hybrid system is of interest in different areas, e.g., cyber-physical energy systems. This includes the embedding of continuous-time subsystems in discrete event systems. The difficulties of resulting synchronisation schedules are approached by precalculation within the components. The Functional Mock-up Interface (FMI) is a state of the art specification for the co-simulation of continuous systems, which is supported by a growing number of simulation software. FMI for Model Exchange components generated with OpenModelica have been embedded in the discrete event domain of Ptolemy II as a proof of concept. An example shows that the use of FMI components has a better scalability and shorter runtime than a pure Ptolemy II implementation.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130522953","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115407
Michael H. Spiegel, F. Leimgruber, E. Widl, G. Gridling
Comprehensive models of cyber-physical energy systems often require the integration of automation infrastructure and energy system models. While energy system models mostly focus on the physics of these systems, automation infrastructure targets control aspects of the modelled systems. Currently, both parts are coupled via tool-dependent interfaces and in most cases the deployed couplings do not consider timing aspects. This article describes the usage of an established interface for model exchange to include models in a standardized automation infrastructure. It discusses a novel projection-based approach and its real-time capabilities, describes its implementation and presents first test results.
{"title":"On using FMI-based models in IEC 61499 control applications","authors":"Michael H. Spiegel, F. Leimgruber, E. Widl, G. Gridling","doi":"10.1109/MSCPES.2015.7115407","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115407","url":null,"abstract":"Comprehensive models of cyber-physical energy systems often require the integration of automation infrastructure and energy system models. While energy system models mostly focus on the physics of these systems, automation infrastructure targets control aspects of the modelled systems. Currently, both parts are coupled via tool-dependent interfaces and in most cases the deployed couplings do not consider timing aspects. This article describes the usage of an established interface for model exchange to include models in a standardized automation infrastructure. It discusses a novel projection-based approach and its real-time capabilities, describes its implementation and presents first test results.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130972838","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115402
A. Valdes, C. Hang, Prosper Panumpabi, N. Vaidya, Christopher Drew, D. Ischenko
The IEC 61850 protocol suite provides significant benefits in electrical substation design and enables formal validation of complex device configurations to ensure that design objectives are met. One important benefit is the potential for protective relays to react in a collaborative fashion to an observed fault current. Modern relays are networked cyber-physical devices with embedded systems, capable of sophisticated protection schemes that are not possible on legacy overcurrent relays. However, they may be subject to error or cyber attack. Herein, we introduce the CODEF (Collaborative Defense) project examining distributed substation protection. Under CODEF, we derive algorithms for distributed protection schemes based on distributed agreement. By leveraging Kirchhoff's laws, we establish that certain fast agreement protocols have important equivalences to linear coding and error correction theory. In parallel, we describe a cyber-physical simulation environment in which these algorithms are being validated with respect to the strict time constraints of substation protection.
{"title":"Design and simulation of fast substation protection in IEC 61850 environments","authors":"A. Valdes, C. Hang, Prosper Panumpabi, N. Vaidya, Christopher Drew, D. Ischenko","doi":"10.1109/MSCPES.2015.7115402","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115402","url":null,"abstract":"The IEC 61850 protocol suite provides significant benefits in electrical substation design and enables formal validation of complex device configurations to ensure that design objectives are met. One important benefit is the potential for protective relays to react in a collaborative fashion to an observed fault current. Modern relays are networked cyber-physical devices with embedded systems, capable of sophisticated protection schemes that are not possible on legacy overcurrent relays. However, they may be subject to error or cyber attack. Herein, we introduce the CODEF (Collaborative Defense) project examining distributed substation protection. Under CODEF, we derive algorithms for distributed protection schemes based on distributed agreement. By leveraging Kirchhoff's laws, we establish that certain fast agreement protocols have important equivalences to linear coding and error correction theory. In parallel, we describe a cyber-physical simulation environment in which these algorithms are being validated with respect to the strict time constraints of substation protection.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132446225","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115399
Aaron Mills, Joseph Zambreno
Much of current research on State-of-Charge (SOC) and State-of-Health (SOH) tracking for rechargeable batteries such as Li-ion focuses primarily on analyzing single cells, or otherwise treat a set of series-connected cells as a homogeneous unit. Since no two cells have precisely the same properties, for applications involving large batteries this can severely limit the accuracy and utility of the approach. In this paper we develop an model-driven approach using a Dual Unscented Kalman Filter to allow a Battery Monitoring System (BMS) to monitor in real time both SOC and SOH of each cell in a battery. A BMS is an example of a Cyber-Physical System (CPS) which requires deep understanding of the behavior of the physical system (i.e., the battery) in order to obtain reliability in demanding applications. In particular, since the SOH of a cell changes extremely slowly compared to SOC, our dual filter operates on two timescales to improve SOH tracking. We show that the use of the Unscented Kalman Filter instead of the more common Extended Kalman Filter simplifies the development of the system model equations in the multiscale case. We also show how a single “average” cell model can be used to accurately estimate SOH for different cells and cells of different ages.
{"title":"Estimating state of charge and state of health of rechargable batteries on a per-cell basis","authors":"Aaron Mills, Joseph Zambreno","doi":"10.1109/MSCPES.2015.7115399","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115399","url":null,"abstract":"Much of current research on State-of-Charge (SOC) and State-of-Health (SOH) tracking for rechargeable batteries such as Li-ion focuses primarily on analyzing single cells, or otherwise treat a set of series-connected cells as a homogeneous unit. Since no two cells have precisely the same properties, for applications involving large batteries this can severely limit the accuracy and utility of the approach. In this paper we develop an model-driven approach using a Dual Unscented Kalman Filter to allow a Battery Monitoring System (BMS) to monitor in real time both SOC and SOH of each cell in a battery. A BMS is an example of a Cyber-Physical System (CPS) which requires deep understanding of the behavior of the physical system (i.e., the battery) in order to obtain reliability in demanding applications. In particular, since the SOH of a cell changes extremely slowly compared to SOC, our dual filter operates on two timescales to improve SOH tracking. We show that the use of the Unscented Kalman Filter instead of the more common Extended Kalman Filter simplifies the development of the system model equations in the multiscale case. We also show how a single “average” cell model can be used to accurately estimate SOH for different cells and cells of different ages.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"135 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113992110","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}
Pub Date : 2015-04-13DOI: 10.1109/MSCPES.2015.7115409
J. Venkatesh, Sheng-hua Chen, P. Tinnakornsrisuphap, T. Rosing
Batteries are an important element for residences that are in grid-connected systems with energy procurement. They provide storage for local generation and a buffer against the inconsistent output from renewables such as rooftop solar. In addition, they can independently provide a medium for buying and selling retail energy. The growing deployment of reverse power-operation systems provides residences with the ability to buy and sell energy at the retail time-of-use rate. While the nonlinear models of chemical batteries have been extensively studied, they have not been applied to strategies for residential battery use. In this work, we develop a formulation for battery usage based on more realistic battery models, optimizing the benefit of discharging the battery. We design the scheme for the actual use of batteries in an energy-trading environment, considering the total cost of ownership and return on investment. Finally, we simulate the system in different geographic locations using the actual time-of-use pricing for each, and demonstrating return on investment in as few as 5 years.
{"title":"Lifetime-dependent battery usage optimization for grid-connected residential systems","authors":"J. Venkatesh, Sheng-hua Chen, P. Tinnakornsrisuphap, T. Rosing","doi":"10.1109/MSCPES.2015.7115409","DOIUrl":"https://doi.org/10.1109/MSCPES.2015.7115409","url":null,"abstract":"Batteries are an important element for residences that are in grid-connected systems with energy procurement. They provide storage for local generation and a buffer against the inconsistent output from renewables such as rooftop solar. In addition, they can independently provide a medium for buying and selling retail energy. The growing deployment of reverse power-operation systems provides residences with the ability to buy and sell energy at the retail time-of-use rate. While the nonlinear models of chemical batteries have been extensively studied, they have not been applied to strategies for residential battery use. In this work, we develop a formulation for battery usage based on more realistic battery models, optimizing the benefit of discharging the battery. We design the scheme for the actual use of batteries in an energy-trading environment, considering the total cost of ownership and return on investment. Finally, we simulate the system in different geographic locations using the actual time-of-use pricing for each, and demonstrating return on investment in as few as 5 years.","PeriodicalId":212582,"journal":{"name":"2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133193913","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}
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