Our test environment incorporates a unique blend of physical, emulated, and virtualized
components, spanning from electrical substations to SCADA systems,
thereby offering a versatile platform for testing against cyber threats, facilitating
educational programs, and supporting advanced traffic simulation. Key findings
from our deployment highlight the testbed’s effectiveness in identifying vulnerabilities,
enhancing cybersecurity measures, and providing valuable hands-on
learning experiences. The integration of such diverse components not only exemplifies
a significant step forward in testbed design but also showcases its potential
in fostering innovation and security in the power sector. Through detailed comparisons
with existing testbeds, we underscore our testbed’s distinct features
and its contribution to bridging the gap in current methodologies, setting a new
benchmark for future developments in smart grid testing and education.

The supplemental information provides supporting figures comparing the virtual water trade of food and electricity in Europe. Additionally, we provide a description of the contents in File S1, which contains data necessary for reproducing the figures in the manuscript, "The Changing Virtual Water Trade Network of the European Electric Grid" by Christopher M. Chini and Ashlynn S. Stillwell.

This work focuses on two Use Cases (UCs) of the Smart5Grid project (UC3 and UC4) and reports the raw data of their corresponding Network Applications: Run Time Energy Production Monitoring Predictive Maintenance (Enabler) for UC3 as well as virtual Phasor Data Concentrator (vPDC), Wide Area Monitoring (WAM), and Advisory (Enabler) for UC4. These Network Applications are developed by means of Grid Protection Alliance (GPA) open source software and GSF open source library. Another two GPA open source projects used for both UCs development are openPDC and openHistorian. Microsoft Visual Studio 2022 is the coding environment while C# и JavaScript are the programming languages engaged in the Use Cases 3&4 NetApp development process. Correspondingly, the services for both UCs are placed in Docker images that are used in Helm charts. These Helm charts are used to install the services in Kubernetes cluster, which runs Docker containers of the services in its cluster. Detailed video demonstrations of both use cases’ services are referred to in the results section of the associated manuscript. Two reproducible and reusable raw data timeseries are shared: (1) realtime photovoltaic production monitoring using the UC3 NetApps (demo of distributed renewable resources monitoring), and (2) realtime virtual Phasor Data Concentrator as UC4 demonstrator(of Wide Area Monitoring of an interconnected power system via 400 kV tie line between Bulgaria and Greece). Both demostrators run on an innovative Smart5Grid Open Experimentation Platform building on 5G PPP and detailed in the associated article. Methods The Smart5Grid development methodology is based on the concept of Network Applications (NetApps). Their main mission is to hide the complexity of a 5G telco network to for energy application developers in a way that empowers them to develop a NetApp without having to deal with the underlying network. A Virtual Infrastructure Manager (VIM) such as such as OpenStack or Kubernetes hosts every unit that composes a NetApp. The VIM provides monitoring data to a Network Function Vurtualisation Manager and Orchestrator (NFV MANO) framework, which airs information to the NAC that employs analysis algorithms to propose the optimal Virtual Network Function (VNF) and NetApp placing. A Slice Manager (SM) reserves resources for all these capabilities.

According to Cognitive Market Research, the global Virtual Power Plant VPP Market size is USD 1951.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 22.60% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 780.48 million in 2024 and will grow at a compound annual growth rate (CAGR) of 20.8% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 585.36 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 448.78 million in 2024 and will grow at a compound annual growth rate (CAGR) of 24.6% from 2024 to 2031.
Latin America's market will have more than 5% of the global revenue with a market size of USD 97.56 million in 2024 and will grow at a compound annual growth rate (CAGR) of 22.0% from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 39.02 million in 2024 and will grow at a compound annual growth rate (CAGR) of 22.3% from 2024 to 2031.
The Demand Response held the highest Virtual Power Plant VPP Market revenue share in 2024.

Market Dynamics of Virtual Power Plant VPP Market

Key Drivers of Virtual Power Plant VPP Market

Grid Flexibility and Stability to Increase the Demand Globally

Grid flexibility and stability are becoming increasingly critical as the energy landscape undergoes rapid transformation, characterized by the integration of renewable energy sources and the electrification of various sectors. The growing variability and intermittency of renewable energy generation pose challenges to grid operators in maintaining a balance between supply and demand, managing voltage and frequency fluctuations, and ensuring grid stability. As a result, there is a rising demand for solutions that enhance grid flexibility and stability. Centralized Controlled Virtual Power Plants (VPPs) are poised to play a pivotal role in addressing these challenges. By aggregating and orchestrating diverse distributed energy resources (DERs), including solar, wind, battery storage, and demand response, Centralized Controlled VPPs enable utilities and grid operators to optimize energy dispatch, mitigate grid congestion, and respond dynamically to grid conditions in real-time.

Renewable Energy Integration to Propel Market Growth

The integration of renewable energy sources into the power grid is rapidly accelerating, driven by environmental concerns, policy initiatives, and advancements in renewable energy technologies. As countries worldwide strive to reduce greenhouse gas emissions and transition towards cleaner energy sources, there is a growing need to integrate renewable energy into the grid effectively while maintaining reliability and stability. This demand for renewable energy integration is poised to propel the growth of the market for Centralized Controlled Virtual Power Plants (VPPs). Centralized Controlled VPPs offer a sophisticated solution for aggregating, managing, and optimizing diverse renewable energy resources, including solar, wind, and hydroelectric power. By centrally coordinating the operation of distributed renewable energy assets, Centralized Controlled VPPs enable grid operators to maximize the utilization of renewable energy, minimize curtailment, and optimize energy dispatch in real time.

Restraint Factors Of Virtual Power Plant VPP Market

Cybersecurity Risks to Limit the Sales

Cybersecurity risks pose a significant challenge to the adoption and deployment of Centralized Controlled Virtual Power Plants (VPPs), potentially limiting sales and market growth. As VPPs rely heavily on digital technologies and communication networks to monitor, control, and optimize distributed energy resources (DERs), they become susceptible to various cybersecurity threats such as hacking, data breaches, and malicious attacks. These threats not only jeopardize the integrity and confidentiality of critical energy infrastructure but also pose risks to grid security, reliability, and customer privacy. Concerns about cybersecurity vulnerabilities may lead to hesitation among utilities, grid operators, and energy providers in adopting Centralized Controlled VPP solutions, especially if they perceive cybersecurity risks as significant barriers to deployment. Moreover, stringent regulatory requirements and...

Snapshot img

Virtual Power Plant Market Size 2024-2028

The virtual power plant market size is forecast to increase by USD 11.13 billion at a CAGR of 25.66% between 2023 and 2028.

The virtual power plant (VPP) market is witnessing significant growth due to the increasing integration of renewable energy sources with electric power systems. This trend is driven by the need to address the intermittency issues of renewable energy and ensure grid stability. Another key factor fueling market growth is the growing adoption of artificial intelligence (AI), machine learning, and advanced data analytics in VPPs.
These technologies enable efficient load balancing, forecasting, and optimization of energy production and consumption. However, the lack of expertise and inadequate infrastructure for VPPs poses a challenge to market growth. Despite these challenges, the market is expected to continue expanding as the benefits of VPPs, such as improved grid reliability and reduced carbon emissions, become increasingly apparent.

What will be the Size of the Virtual Power Plant Market During the Forecast Period?

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The virtual power plant (VPP) market is experiencing significant growth due to the increasing integration of renewable energy sources, such as solar generation and wind turbines, into the electricity grid. VPPs enable the aggregation and control of distributed energy resources, including solar panels, wind turbines, energy storage systems, electric vehicles, and battery banks. This centralized and decentralized approach to energy production and consumption enhances grid stability and efficiency, reducing carbon emissions and promoting sustainable energy. VPPs employ advanced technologies, including control systems, algorithms, communication technologies, and cloud platforms, to optimize energy demand and supply in real-time. Interoperability between various energy sources and utility systems is crucial for the successful implementation of VPPs.
Utilities and customers benefit from VPPs by improving capacity utilization, selling excess power to the electricity market, and ensuring a reliable energy supply. The integration of VPPs into the smart grid infrastructure is a key trend driving the market's growth, as the world transitions to a low-carbon economy in response to climate change concerns.

How is this Virtual Power Plant Industry segmented and which is the largest segment?

The virtual power plant industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Technology

  Mixed asset
  Demand response
  Distributed generation


End-user

  Industrial
  Commercial
  Residential


Geography

  Europe

    Germany
    UK
    France


  North America

    US


  APAC



  Middle East and Africa



  South America

By Technology Insights

The mixed asset segment is estimated to witness significant growth during the forecast period.

In the market, advanced technologies play a pivotal role in managing energy demand and grid stability. Smart grids facilitate communication between central control systems and distributed energy resources, including solar panels, wind turbines, batteries, and electric vehicles. IoT devices enable remote access and control, optimizing energy usage based on real-time data and price signals. Predictive analytics and automated controls forecast demand fluctuations and adjust energy output accordingly. Energy management systems coordinate diverse assets, ensuring efficient capacity utilization and response to grid signals or market conditions. Key technologies include control systems, algorithms, communication technologies, interoperability, demand response, and energy storage. The market encompasses various sectors, including utilities, manufacturing, medical devices, and pilot programs, as the world transitions to renewable energy and decarbonization.

Energy security, power distribution, and efficiency are paramount In the context of climate change and increasing electricity demand. Storage technologies, renewable technologies, and digitalization are essential components of the virtual power plant ecosystem.

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The Mixed asset segment was valued at USD 1.18 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

Europe is estimated to contribute 55% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The Virtual Power Plant (VPP) market is e

Virtual Energy Storage Market Outlook

According to our latest research, the global virtual energy storage market size reached USD 2.13 billion in 2024, reflecting the rapid adoption of digital solutions in energy management. The market is poised for significant growth, projected to achieve USD 13.56 billion by 2033, expanding at a robust CAGR of 22.5% from 2025 to 2033. This remarkable growth trajectory is driven by the escalating integration of renewable energy sources, increasing demand for grid flexibility, and the growing emphasis on energy efficiency across residential, commercial, and industrial sectors worldwide.

One of the primary growth factors fueling the virtual energy storage market is the accelerating integration of renewable energy resources, such as solar and wind, into power grids. As these resources are inherently variable and intermittent, utilities and grid operators are increasingly seeking advanced solutions to balance supply and demand in real-time. Virtual energy storage leverages digital platforms and software to aggregate and control distributed energy resources, optimizing their collective impact without the need for extensive physical infrastructure. This capability enhances grid reliability and stability, enabling a smoother transition to cleaner energy and reducing dependency on fossil-fuel-based peaking plants. As governments and organizations worldwide set ambitious decarbonization targets, the adoption of virtual energy storage solutions is rapidly becoming a strategic imperative.

Another significant driver for the virtual energy storage market is the rising demand for grid services and ancillary support. With the proliferation of distributed energy resources, such as rooftop solar panels, electric vehicles, and smart appliances, there is a growing need for advanced technologies that can orchestrate these assets to deliver valuable grid services. Virtual energy storage platforms enable aggregation and real-time management of these distributed assets, providing services such as frequency regulation, voltage support, and demand response. This not only enhances overall grid efficiency but also creates new revenue streams for asset owners and utilities. The increasing deployment of smart meters and IoT devices further amplifies the potential of virtual energy storage by facilitating granular monitoring and control, thereby maximizing the value extracted from distributed resources.

The virtual energy storage market is also benefiting from advancements in cloud computing, artificial intelligence, and machine learning. These technologies are empowering solution providers to develop sophisticated algorithms and predictive analytics that optimize the operation of distributed energy resources. By leveraging real-time data and advanced forecasting models, virtual energy storage platforms can anticipate grid conditions, automate decision-making, and dynamically adjust energy flows. This not only improves operational efficiency but also reduces costs associated with traditional energy storage infrastructure. Furthermore, the scalability and flexibility offered by cloud-based solutions are making virtual energy storage accessible to a wider range of end-users, from small residential customers to large industrial facilities, thereby broadening the market’s addressable base.

From a regional perspective, North America currently leads the virtual energy storage market, driven by robust investments in smart grid infrastructure, favorable regulatory frameworks, and a high penetration of distributed energy resources. Europe follows closely, propelled by stringent emissions targets and progressive energy policies. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, increasing electricity demand, and government initiatives supporting renewable integration and grid modernization. Latin America and the Middle East & Africa are also witnessing gradual adoption, albeit at a slower pace, as energy access and grid reliability become key priorities. Overall, the global virtual energy storage market is set to experience widespread growth, with regional dynamics shaped by varying levels of technological maturity, policy support, and market readiness.

Subjective experience is key to understanding affective states, characterized by valence and arousal. Traditional experiments using post-stimulus summary ratings do not resemble natural behavior. Fluctuations of affective states can be explored with dynamic stimuli, such as videos. Continuous ratings can capture moment-to-moment affective experience, however the rating or the feedback can be interfering. We designed, empirically evaluated, and openly share AffectTracker, a tool to collect continuous ratings of two-dimensional affective experience (valence and arousal) during dynamic stimulation, such as 360-degree videos in immersive virtual reality. AffectTracker comprises three customizable feedback options: a simplified affect grid (Grid), an abstract pulsating variant (Flubber), and no visual feedback. Two studies with healthy adults were conducted, each at two sites (Berlin, Germany, and Torino, Italy). In Study 1 (Selection: n=51), both Grid and Flubber demonstrated high user experience and low interference in repeated 1-min 360-degree videos. Study 2 (Evaluation: n=83) confirmed these findings for Flubber with a longer (23-min), more varied immersive experience, maintaining high user experience and low interference. Continuous ratings collected with AffectTracker effectively captured valence and arousal variability. For shorter, less eventful stimuli, their correlation with post-stimulus summary ratings demonstrated the tool’s validity; for longer, more eventful stimuli, it showed the tool’s benefits of capturing additional variance. Our findings suggest that AffectTracker provides a reliable, minimally interfering method to gather moment-to-moment affective experience also in immersive environments, offering new research opportunities to link affective states and physiological dynamics.

This data set contains the finite element generated data necessary to validate the generalized stress-strain curves. It supports the paper: Generalized stress-strain curves for IBII tests on isotropic and orthotropic materials F. Pierron, L. Fletcher Journal of the Dynamic Behaviour of Materials, 2019 DOI: 10.1007/s40870-019-00197-9

This data contains radiation fields at four different heights. we use it to build the coupled radiation field.

Code:

• Packet_Features_Generator.py & Features.py
  • To run this code:
    • pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j
    • -h, --help show this help message and exit
      -i TXTFILE input text file
      -x X Add first X number of total packets as features.
      -y Y Add first Y number of negative packets as features.
      -z Z Add first Z number of positive packets as features.
      -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,...
      -s S Generate samples using size s.
      -j
  • Purpose:
    • Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.
    • Uses Features.py to calcualte the features.
• startMachineLearning.sh & machineLearning.py
  • To run this code:
    • bash startMachineLearning.sh
    • This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags
    • Options (to be edited within this file):
      • --evaluate-only to test 5 fold cross validation accuracy
      • --test-scaling-normalization to test 6 different combinations of scalers and normalizers
        • Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use
      • --grid-search to test the best grid search hyperparameters
        - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:'
        - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'
  • Purpose:
    • Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.

Data

• Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.
• Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:
  • First number is a classification number to denote what website, query, or vr action is taking place.
  • The remaining numbers in each line denote:
    • The size of a packet,
    • and the direction it is traveling.
  • negative numbers denote incoming packets
  • positive numbers denote outgoing packets

Number-of-Days-of-Payables Time Series for State Grid Information&Communication Co Ltd. State Grid Information & Communication Co., Ltd. engages in information and communication business. The company's value-added telecom operation business, offers Internet access, Internet virtual private network, Internet information, Internet data center services (IDC), etc.; communication network construction business provides installation and commissioning of switches, routers, communication terminals, and other equipment, as well as laying of optical fibers and other project implementation services, and designing and planning of communication network schemes; and cloud network infrastructure construction business offers services including installation and commissioning of servers, storage, network equipment, and project implementation, etc. Its cloud platform business provides cloud operating systems, cloud service center, and distributed service bus; and cloud platform components business offers enterprise-level cloud infrastructure management and business cloud solutions; and customized services, including desktop and storage virtualization, network virtualization, forming cloud storage, cloud terminals, cloud desktops, and cloud operations. The company's enterprise operation support service business provides operation and maintenance consultation, system optimization, operation and maintenance for user information and communication infrastructure, and software platforms and applications. It is also involved in the enterprise portal business, which offers multi-terminal, multi-form, and multi-carrier enterprise unified information integration and access portal; ERP business, which offers system consulting and implementation business, and financial peripheral products; power marketing business provides customized research and development of power marketing systems for energy companies; and enterprise operation visualization, as well as energy trading business. The company was founded in 1997 and is headquartered in Chengdu, China.

End-Period-Cash-Flow Time Series for State Grid Information&Communication Co Ltd. State Grid Information & Communication Co., Ltd. engages in information and communication business. The company's value-added telecom operation business, offers Internet access, Internet virtual private network, Internet information, Internet data center services (IDC), etc.; communication network construction business provides installation and commissioning of switches, routers, communication terminals, and other equipment, as well as laying of optical fibers and other project implementation services, and designing and planning of communication network schemes; and cloud network infrastructure construction business offers services including installation and commissioning of servers, storage, network equipment, and project implementation, etc. Its cloud platform business provides cloud operating systems, cloud service center, and distributed service bus; and cloud platform components business offers enterprise-level cloud infrastructure management and business cloud solutions; and customized services, including desktop and storage virtualization, network virtualization, forming cloud storage, cloud terminals, cloud desktops, and cloud operations. The company's enterprise operation support service business provides operation and maintenance consultation, system optimization, operation and maintenance for user information and communication infrastructure, and software platforms and applications. It is also involved in the enterprise portal business, which offers multi-terminal, multi-form, and multi-carrier enterprise unified information integration and access portal; ERP business, which offers system consulting and implementation business, and financial peripheral products; power marketing business provides customized research and development of power marketing systems for energy companies; and enterprise operation visualization, as well as energy trading business. The company was founded in 1997 and is headquartered in Chengdu, China.

Change-To-Liabilities Time Series for State Grid Information&Communication Co Ltd. State Grid Information & Communication Co., Ltd. engages in information and communication business. The company's value-added telecom operation business, offers Internet access, Internet virtual private network, Internet information, Internet data center services (IDC), etc.; communication network construction business provides installation and commissioning of switches, routers, communication terminals, and other equipment, as well as laying of optical fibers and other project implementation services, and designing and planning of communication network schemes; and cloud network infrastructure construction business offers services including installation and commissioning of servers, storage, network equipment, and project implementation, etc. Its cloud platform business provides cloud operating systems, cloud service center, and distributed service bus; and cloud platform components business offers enterprise-level cloud infrastructure management and business cloud solutions; and customized services, including desktop and storage virtualization, network virtualization, forming cloud storage, cloud terminals, cloud desktops, and cloud operations. The company's enterprise operation support service business provides operation and maintenance consultation, system optimization, operation and maintenance for user information and communication infrastructure, and software platforms and applications. It is also involved in the enterprise portal business, which offers multi-terminal, multi-form, and multi-carrier enterprise unified information integration and access portal; ERP business, which offers system consulting and implementation business, and financial peripheral products; power marketing business provides customized research and development of power marketing systems for energy companies; and enterprise operation visualization, as well as energy trading business. The company was founded in 1997 and is headquartered in Chengdu, China.

Interest-Income Time Series for State Grid Information&Communication Co Ltd. State Grid Information & Communication Co., Ltd. engages in information and communication business. The company's value-added telecom operation business, offers Internet access, Internet virtual private network, Internet information, Internet data center services (IDC), etc.; communication network construction business provides installation and commissioning of switches, routers, communication terminals, and other equipment, as well as laying of optical fibers and other project implementation services, and designing and planning of communication network schemes; and cloud network infrastructure construction business offers services including installation and commissioning of servers, storage, network equipment, and project implementation, etc. Its cloud platform business provides cloud operating systems, cloud service center, and distributed service bus; and cloud platform components business offers enterprise-level cloud infrastructure management and business cloud solutions; and customized services, including desktop and storage virtualization, network virtualization, forming cloud storage, cloud terminals, cloud desktops, and cloud operations. The company's enterprise operation support service business provides operation and maintenance consultation, system optimization, operation and maintenance for user information and communication infrastructure, and software platforms and applications. It is also involved in the enterprise portal business, which offers multi-terminal, multi-form, and multi-carrier enterprise unified information integration and access portal; ERP business, which offers system consulting and implementation business, and financial peripheral products; power marketing business provides customized research and development of power marketing systems for energy companies; and enterprise operation visualization, as well as energy trading business. The company was founded in 1997 and is headquartered in Chengdu, China.

Common-Stock-Shares-Outstanding Time Series for State Grid Information&Communication Co Ltd. State Grid Information & Communication Co., Ltd. engages in information and communication business. The company's value-added telecom operation business, offers Internet access, Internet virtual private network, Internet information, Internet data center services (IDC), etc.; communication network construction business provides installation and commissioning of switches, routers, communication terminals, and other equipment, as well as laying of optical fibers and other project implementation services, and designing and planning of communication network schemes; and cloud network infrastructure construction business offers services including installation and commissioning of servers, storage, network equipment, and project implementation, etc. Its cloud platform business provides cloud operating systems, cloud service center, and distributed service bus; and cloud platform components business offers enterprise-level cloud infrastructure management and business cloud solutions; and customized services, including desktop and storage virtualization, network virtualization, forming cloud storage, cloud terminals, cloud desktops, and cloud operations. The company's enterprise operation support service business provides operation and maintenance consultation, system optimization, operation and maintenance for user information and communication infrastructure, and software platforms and applications. It is also involved in the enterprise portal business, which offers multi-terminal, multi-form, and multi-carrier enterprise unified information integration and access portal; ERP business, which offers system consulting and implementation business, and financial peripheral products; power marketing business provides customized research and development of power marketing systems for energy companies; and enterprise operation visualization, as well as energy trading business. The company was founded in 1997 and is headquartered in Chengdu, China.

Industrial Demand Response Resources (DRRs) are widely used in the frequency response service market. A Virtual Energy Storage System (VESS) model is developed to enable industrial DRRs to participate in the Dynamic Cointainment (DC) service by coordinating with an Energy Storage System (ESS). The power and energy capacity of the ESS are determined by considering its complementary characteristics with industrial DRRs, enabling the VESS to successfully provide the DC service as a whole under the proposed control strategy. Meanwhile, the operational baseline of the ESS is updated based on the “state of energy” management rules for energy-limited units as defined in the DC service.“Numerical results and figures.xlsx” provides the numerical results of Fig. 6 - Fig. 11 of the paper. It contains seven sheets, providing the data behind Fig. 6 - Fig. 11 of the paper.In the “Fig. 6” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes grid frequency variation (unit: Hz), delivery ratios of DC high service, related power curves (unit: MW), and state of charge (SOC) changing process of energy storage system-1 in scenario A.In the “Fig. 7” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes delivery power curves of the virtual energy storage systems (unit: MW), steam power generation (unit: MW), and energy storage system-2 in scenario A.In the “Fig. 8” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes grid frequency variation (unit: Hz), delivery ratios of DC high service, related power curves (unit: MW), and SOC changing process of energy storage system-1 in scenario B.In the “Fig. 9” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes delivery power curves of the virtual energy storage systems (unit: MW), steam power generation (unit: MW), and energy storage system-2 in scenario B.In the “Fig. 10” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes grid frequency variation (unit: Hz), delivery ratios of DC high service, related power curves (unit: MW), and SOC changing process of energy storage system-1 in scenario C.In the “Fig. 11” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes delivery power curves of the virtual energy storage systems (unit: MW), steam power generation (unit: MW), and energy storage system-2 in scenario C. Moreover, the y-axis also describes recovery power curve (unit: MW), actual power curve (unit: MW), and SOC changing process of ESS-2.

Net-Borrowings Time Series for State Grid Information&Communication Co Ltd. State Grid Information & Communication Co., Ltd. engages in information and communication business. The company's value-added telecom operation business, offers Internet access, Internet virtual private network, Internet information, Internet data center services (IDC), etc.; communication network construction business provides installation and commissioning of switches, routers, communication terminals, and other equipment, as well as laying of optical fibers and other project implementation services, and designing and planning of communication network schemes; and cloud network infrastructure construction business offers services including installation and commissioning of servers, storage, network equipment, and project implementation, etc. Its cloud platform business provides cloud operating systems, cloud service center, and distributed service bus; and cloud platform components business offers enterprise-level cloud infrastructure management and business cloud solutions; and customized services, including desktop and storage virtualization, network virtualization, forming cloud storage, cloud terminals, cloud desktops, and cloud operations. The company's enterprise operation support service business provides operation and maintenance consultation, system optimization, operation and maintenance for user information and communication infrastructure, and software platforms and applications. It is also involved in the enterprise portal business, which offers multi-terminal, multi-form, and multi-carrier enterprise unified information integration and access portal; ERP business, which offers system consulting and implementation business, and financial peripheral products; power marketing business provides customized research and development of power marketing systems for energy companies; and enterprise operation visualization, as well as energy trading business. The company was founded in 1997 and is headquartered in Chengdu, China.

The Robot@VirtualHome dataset is a raw collection of data from 30 virtual homes with different appearance obtained through the Robot@VirtualHome ecosystem. Each virtual house imitates a real house, keeping the same room layout and imitating real objects with virtual object models. The objectives of this dataset are: first, to be used as a testbed for diverse algorithms such as semantic mapping through the categorization of objects and/or rooms, active exploration of the environment, localization by appearance, or others where the data presented are of interest, and second to provide a basic example of the results that can be obtained through the Robot@VirtualHome ecosystem.

The dataset consists of 113278 captures in 30 houses, with 236 rooms, 2569 objects and 4 different appearance conditions. Each data capture has stored an RGB image, a depth image, a semantic mask image, the measurements from a laser scanner and a log with information about the position at which the data was taken. In addition, for each house we have added the occupancy map obtained with the laser scanner and a log with the ground truth of all objects and rooms.

Five raids have been carried out for each house: the first one, capturing data at the nodes of a grid using standard appearance, in the remaining four raids the data were taken by wandering around visiting all the rooms and using different appearance conditions.

More detailed information is provided in the article.

An API is available here to facilitate access to the dataset data.

Virtual Power Line Market Outlook

According to our latest research, the global Virtual Power Line market size in 2024 stands at USD 1.85 billion, with the market expected to reach USD 8.21 billion by 2033, reflecting a robust compound annual growth rate (CAGR) of 17.9% during the forecast period. This significant expansion is primarily driven by the increasing demand for flexible, cost-effective, and scalable energy management solutions, as well as the rapid digitization of power infrastructure across industries.

One of the key growth factors fueling the Virtual Power Line market is the global shift toward renewable energy integration and smart grid modernization. As energy consumption patterns evolve and the adoption of distributed energy resources accelerates, utilities and grid operators are seeking innovative ways to optimize grid performance and reliability. Virtual Power Line solutions allow for the dynamic allocation of power, real-time monitoring, and predictive analytics, reducing the need for costly physical infrastructure upgrades. This capability is particularly critical in urban centers and rapidly developing regions, where energy demand is surging but physical grid expansion is constrained by space, regulatory, and financial limitations. The transition to smart grids, coupled with stringent government policies on energy efficiency and sustainability, further amplifies the adoption of Virtual Power Line technologies.

Another driving force behind market growth is the increasing prevalence of digital transformation initiatives within the energy sector. Utilities and industrial players are investing heavily in advanced software, IoT devices, and cloud-based platforms to enhance operational efficiency and reduce downtime. Virtual Power Line solutions, which leverage artificial intelligence, machine learning, and big data analytics, are becoming indispensable tools for predictive maintenance, load balancing, and grid resilience. The proliferation of smart meters and connected devices is generating vast amounts of data, enabling more accurate forecasting and demand response strategies. As energy markets become more dynamic and decentralized, the ability to manage virtual power flows in real-time is emerging as a critical competitive differentiator.

The market is also benefiting from the rising need for cost optimization and improved asset utilization across sectors such as manufacturing, IT & telecommunications, and transportation. Virtual Power Line technologies enable organizations to defer or avoid expensive capital investments in new transmission infrastructure by maximizing the capacity of existing assets. This approach not only reduces operational expenditures but also supports sustainability goals by minimizing environmental impact. The convergence of energy and information technology is fostering the development of integrated solutions tailored to specific industry needs, further accelerating market penetration. Collaborative efforts among technology vendors, utilities, and regulatory bodies are also creating a favorable environment for the widespread adoption of Virtual Power Line systems.

Regionally, the Virtual Power Line market exhibits strong growth prospects across North America, Europe, and Asia Pacific, with each region contributing unique drivers and opportunities. North America leads in terms of technological innovation and early adoption, supported by substantial investments in smart grid infrastructure and favorable regulatory frameworks. Europe is witnessing rapid growth due to its ambitious renewable energy targets and grid modernization initiatives, particularly in countries such as Germany, the UK, and France. Meanwhile, Asia Pacific is poised for the highest CAGR during the forecast period, fueled by the rapid urbanization, expanding industrial base, and government-led initiatives to enhance grid reliability and energy access. Latin America and the Middle East & Africa are also emerging as promising markets, driven by infrastructure development and increasing focus on energy efficiency.

This version of the fully coupled catchment simulation features the atmospheric model COSMO run at 1.1km (0.01°rotlat/lon grid), the land surface model CLM and the groundwater model Parflow, both run at 400m (regular lat/lon grid). Coupled with OASIS3-MCT.