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Global Virtual Power Plant Market to reach USD 11.38 billion by the end of 2030.

Global Virtual Power Plant Market Size study & Forecast, by Technology (Demand Response, Distributed Generation, Mixed Asset), by End-user (Residential, Commercial, Industrial) and Regional Analysis, 2023-2030

Product Code: EPPGS-98907202
Publish Date: 30-10-2023
Page: 200

Global Virtual Power Plant Market is valued at approximately USD 1.17 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 32.89% over the forecast period 2023-2030. Virtual Power Plants combines the production capabilities of several distributed energy sources to improve power generation and trade or sell power on the electricity market. It makes it possible to have a steady supply of electricity and permits utilities to produce electricity using renewable energy sources, store it in battery banks, and then provide it to users. It offers real-time information on the networked units’ capacity utilization. The market is growing due to factors such as the rising share of renewable energy in the mix of energy sources, falling solar generation prices, and improvements in energy storage. The power industry is increasing the use of cutting-edge technologies such as cloud platforms and Internet of Things (IoT) applications is also boosting the market growth for virtual power plants. The Virtual Power Plant market is expanding because of factors such as increasing demand for renewable power generation, and a growing shift towards distributed generation.

Renewable power generation, such as solar and wind, often occurs in a decentralized manner, with small-scale installations spread across various locations. Virtual Power Plants can effectively integrate these distributed energy resources into a unified system, optimizing their collective output and enhancing grid stability The International European Agency predicts that by 2026, worldwide renewable electricity capacity would have increased by more than 60% from 2020 levels to more than 4 800 GW. Thus, rising demand for renewable power generation is driving market growth. In addition, the increasing development of smart grids, increasing demand for combined renewable energy & growing investments in energy storage are creating new opportunities for the market. However, the high cost of virtual power plants and inadequate infrastructure stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Virtual Power Plant Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the dominance of key market players, an increase in renewable energy installations, such as solar and wind power, increasing penetration of energy storage technologies, and a growing trend towards decentralized energy generation, with more consumers adopting rooftop solar panels. Whereas, Asia Pacific is projected to have significant growth owing to factors such as rising investment in renewable energy power generation, and rising government support in the industry.

Major market player included in this report are:
ABB, Ltd.
Autogrid Systems, Inc.
Cisco Systems, Inc.
Cpower Energy Management
Enbala Power Networks, Inc.
Enernoc, Inc
Flexitricity Limited
General Electric Company
Hitachi, Ltd.
Robert Bosch GmbH

Recent Developments in the Market:
Ø In February 2023, -SolarEdge Technologies, Inc. launched Battery Virtual Power Plant. The service is available to thousands of SolarEdge Home Battery owners across Great Britain with eligible smart meters, that are now able to earn financial incentives utilizing their stored battery energy during DFS peak demand events, which would be used to stabilize the grid.
Ø In April 2023, – SunPower provider, and OhmConnect, launched a new virtual power plant (VPP) offering for SunPower customers across California. The homeowners in select locations with solar and SunVault battery storage can connect with OhmConnect directly through the mySunPower app to earn rewards for managing their electricity use during periods of peak demand.

Global Virtual Power Plant Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Technology, End-user, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Technology:
Demand Response
Distributed Generation
Mixed Asset

By End-user:

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Virtual Power Plant Market, by Region, 2020-2030 (USD Billion)
1.2.2. Virtual Power Plant Market, by Technology, 2020-2030 (USD Billion)
1.2.3. Virtual Power Plant Market, by End-user, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Virtual Power Plant Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Virtual Power Plant Market Dynamics
3.1. Virtual Power Plant Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing demand for renewable power generation Growing shift towards distributed generation.
3.1.2. Market Challenges High cost of virtual power plant Inadequate infrastructure
3.1.3. Market Opportunities Increasing development of smart grids Increasing demand for combined renewable energy Growing investments in energy storage
Chapter 4. Global Virtual Power Plant Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Virtual Power Plant Market, by Technology
5.1. Market Snapshot
5.2. Global Virtual Power Plant Market by Technology, Performance – Potential Analysis
5.3. Global Virtual Power Plant Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
5.4. Virtual Power Plant Market, Sub Segment Analysis
5.4.1. Demand Response
5.4.2. Distributed Generation
5.4.3. Mixed Asset
Chapter 6. Global Virtual Power Plant Market, by End-user
6.1. Market Snapshot
6.2. Global Virtual Power Plant Market by End-user, Performance – Potential Analysis
6.3. Global Virtual Power Plant Market Estimates & Forecasts by End-user 2020-2030 (USD Billion)
6.4. Virtual Power Plant Market, Sub Segment Analysis
6.4.1. Residential
6.4.2. Commercial
6.4.3. Industrial
Chapter 7. Global Virtual Power Plant Market, Regional Analysis
7.1. Top Leading Countries
7.2. Top Emerging Countries
7.3. Virtual Power Plant Market, Regional Market Snapshot
7.4. North America Virtual Power Plant Market
7.4.1. U.S. Virtual Power Plant Market Technology breakdown estimates & forecasts, 2020-2030 End-user breakdown estimates & forecasts, 2020-2030
7.4.2. Canada Virtual Power Plant Market
7.5. Europe Virtual Power Plant Market Snapshot
7.5.1. U.K. Virtual Power Plant Market
7.5.2. Germany Virtual Power Plant Market
7.5.3. France Virtual Power Plant Market
7.5.4. Spain Virtual Power Plant Market
7.5.5. Italy Virtual Power Plant Market
7.5.6. Rest of Europe Virtual Power Plant Market
7.6. Asia-Pacific Virtual Power Plant Market Snapshot
7.6.1. China Virtual Power Plant Market
7.6.2. India Virtual Power Plant Market
7.6.3. Japan Virtual Power Plant Market
7.6.4. Australia Virtual Power Plant Market
7.6.5. South Korea Virtual Power Plant Market
7.6.6. Rest of Asia Pacific Virtual Power Plant Market
7.7. Latin America Virtual Power Plant Market Snapshot
7.7.1. Brazil Virtual Power Plant Market
7.7.2. Mexico Virtual Power Plant Market
7.8. Middle East & Africa Virtual Power Plant Market
7.8.1. Saudi Arabia Virtual Power Plant Market
7.8.2. South Africa Virtual Power Plant Market
7.8.3. Rest of Middle East & Africa Virtual Power Plant Market

Chapter 8. Competitive Intelligence
8.1. Key Company SWOT Analysis
8.1.1. Company 1
8.1.2. Company 2
8.1.3. Company 3
8.2. Top Market Strategies
8.3. Company Profiles
8.3.1. ABB, Ltd. Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
8.3.2. Autogrid Systems, Inc.
8.3.3. Cisco Systems, Inc.
8.3.4. Cpower Energy Management
8.3.5. Enbala Power Networks, Inc.
8.3.6. Enernoc, Inc
8.3.7. Flexitricity Limited
8.3.8. General Electric Company
8.3.9. Hitachi, Ltd.
8.3.10. Robert Bosch GmbH
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
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Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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