Mitsubishi Heavy Industries Technical Review Vol. 55 No. 4 (December 2018)
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MHPS-TOMONI: Thermal Power Generation Digitalization
Platform Cloud/Edge Service and System Architecture

HIROYASU ISHIGAKI*1SATORU MOURI*2

DAISUKE GOTO*3

NAOYUKI NAGAFUCHI*2

To increase the efficiency and reliability of a power plant by utilizing ICT, collaboration
between the power plant operator and the plant manufacturer is indispensable. Mitsubishi Hitachi
Power Systems, Ltd. (MHPS, our company) places an emphasis on providing a solution in which"we work together with the customer." This report introduces the cloud/edge service, systemarchitecture, cyber security, data analysis technology and examples of service application ofMHPS-TOMONI (thermal power generation digitalization service) that our company provides.

|1. Introduction
To increase the efficiency and reliability of a power plant by utilizing ICT (Information andCommunication Technology), the combination of collaboration with the customer, which is thepower plant operator, and the insight of our experienced technicians, is indispensable. Our
company places an emphasis on providing a solution in which "we work together with thecustomer."
MHPS-TOMONI, a thermal power generation digitalization service, is a comprehensive
digital solution developed by our company to solve the problems of every customer involved in theoperation of a power plant, and consists of a variety of hardware, software and services. For
MHPS-TOMONI, information communication technology (ICT) such as big data analysis based on
partnership with customers and artificial intelligence (AI) technology, in addition to innovativetechnologies and expertise on thermal power generation and the operation and maintenance (O&M)
know-how that our company has cultivated for decades, is utilized to the utmost. In this approach,
we target the improvement of the product value of MHPS-TOMONI through not only our own
efforts, but also in cooperation with various industry-leading partner companies.
This report focuses on how MHPS-TOMONI is constructed in terms of the system andintroduces the platform, system architecture and case examples of main applications to products.

|2. System configuration of MHPS-TOMONIThe MHPS-TOMONI system consists of two components: a cloud service and an edge
service. The cloud service realizes advanced technology efficiently and stably by collaborating withindustry-leading technological partners, including global cloud platform Microsoft Azure andOSIsoft’s data management platform PI System. In addition, as a service for users, customer
applications and in-house applications are built in the cloud. Customers and internal users canaccess these applications via the internet, and various services such as the analysis and visualizationof data are available therein. Furthermore, internal users at domestic and overseas bases can use thevirtual desktop environment built on MHPS-TOMONI. With this globally-common workingenvironment, various collaborations such as data analysis and service development are possible.
As the edge service, an in-house developed edge device "Secure Gateway (data diode)" is*1

Director, ICT Operations Department, Power & Energy Solution Business Headquarters, Mitsubishi Hitachi Power Systems,Ltd.

*2

Chief Staff Manager, ICT Operations Department, Power & Energy Solution Business Headquarters, Mitsubishi Hitachi Power*3

CIS Department, ICT Solution Headquarters

Systems,Ltd.

Mitsubishi Heavy Industries Technical Review Vol. 55 No. 4 (December 2018)2

installed in the power plant. This enables data transmission to the cloud with the security of thepower plant ensured. In addition, the edge equipment provides applications requiringhigh-frequency sampling data and high-speed response, applications based on machine learningand the performance improvement functions of the power plant, whereby a mechanism to monitor
the operational status thereof in the cloud is constructed (Figure 1).

Figure 1

System configuration of MHPS-TOMONI|3. Main technologies of MHPS-TOMONI
3.1

Cyber security

When ICT is applied to a thermal power plant, which is critical infrastructure, ensuring cybersecurity must be considered first. MHPS-TOMONI ensures security from the two aspects of cloudand edge.
(1) Cloud side security
The MHPS-TOMONI cloud adopts Microsoft Azure as its foundation. Azure conforms tovarious guidelines such as ISO 27001, 27017, etc., and provides a variety of security tools.
Making the most of these tools, MHPS-TOMONI operates ensuring cloud security compliant
with ISO/IEC 27017, NIST 800-53.
This series of security measures (firewall, encryption, vulnerability management, security
patch updates and log monitoring) compliant with NIST (National Institute of Standards andTechnology) characteristically requires two-factor authentication to access the cloud. Thesecurity is strengthened by not permitting access with simple ID/password for all customer
users, internal users and cloud operators.
(2) Edge side security
To ensure the safe operation of the power plant against recently frequent cyber-attacks,
The cyber security measure in ICT utilization is the most important task. MHPS-TOMONI
encrypts communication between the power plant and the cloud, uses digital certificates forauthentication and restricts access to both. In particular, all communication connections to thepower plant are disallowed. In addition, Secure Gateway is installed to ensure security
measures on the plant side control network. Secure Gateway has a data diode function andphysically blocks access from the outside of the plant by one-way communication, only
permitting data transmission from the plant side to the outside. In addition to this data diodefunction, the Secure Gateway permits limited communication from the outside to the insideusing a serial cable, realizing flexible operation while maintaining the security strength(Figure 2).

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Figure 2

3.2

MHPS-TOMONI security measures

Data analysis system

By accumulating the past long-term data of the power plant in the PI System (database) in
the cloud, it is possible to easily retrieve digital data and visualize trend graphs, etc. (Figure 3).
Moreover, performance calculation, life-time calculation, etc., are carried out by using thecalculation engine of PI System, Excel and a dedicated application.

Figure 3

Trend graph

Figure 4

Performance comparison screen before and after remodeling of equipment

By utilizing R, Python, etc., accumulated past data are analyzed (statistical processing andmachine learning) to provide a more valuable solution to the customer. The data analysis
environment is seamlessly and securely connected to databases and web applications. Data analysts
can perform data mining, data processing, web application development using data analysis/GUI
framework based on R and Python, so the time required to visualize the data analysis results isMitsubishi Heavy Industries Technical Review Vol. 55 No. 4 (December 2018)4

greatly shortened. Figure 4 shows an example of a web screen that displays visualized results ofstatistical analysis using R. This screen is an interactive screen created so that the user can easily
compare the performance before and after the remodeling of the equipment. Such functions can be
combined with a strong authentication system on Azure and securely provided to the customer.

|4. Application examples of services using MHPS-TOMONI
4.1

Remote monitoring service

MHPS established remote monitoring centers in the Takasago Works in 1999 and in
Orlando, U.S.A. in 2001, and operates a remote monitoring service of gas turbine combined cycle
power plant on a round-the-clock basis with specialized staff members. In 2016, we established aremote monitoring center in the Philippines as a new monitoring base and started a remotemonitoring service utilizing MHPS-TOMONI mainly for conventional power plants. Currently,
these remote monitoring centers monitor approximately 150 power plants in countries all aroundthe world, centering on large-scale gas turbines, to support customers' operations (Figure 5). The
infrastructure of the remote monitoring center in the Philippines is based on the MHPS-TOMONI
cloud, and the other centers are shifting as planned or interconnecting thereto.
In a thermal power plant, it is important to monitor a wide range of sensor signals, to detect
predictor abnormalities at an early stage, and to take appropriate measures so that the equipment
will not trip due to problems. MHPS developed its own abnormality detection system to which apattern recognition technology called MT system (Mahalanobis-Taguchi system) is applied andhave utilized it in the remote monitoring service of large gas turbines so far. We also offer anabnormality sign detecting application service, called "Pre-ACT," as a menu item of
MHPS-TOMONI in addition to 24-hour monitoring service with professional staff members.

Figure 54.2

Remote monitoring centers for thermal power plants

Pre-ACT (abnormality sign detection system)

Pre-ACT is an application that consists of two functions: abnormality sign detection andfailure area estimation, and informs the user of the estimated nonconforming part and inspection
items using e-mail or a web screen when the system detects an abnormality that is a predictor ofequipment problems.
The aforementioned MT system that has been proven in the remote monitoring of large gas
turbines is applied to the abnormality sign detection program. One of the features of the MT systemis that the correlation between multiple sensor signals can be managed with one index called
Mahalanobis distance (MD). The system can detect a slight misalignment of correlation, which isan abnormality sign, as an increase in the MD value even when each sensor signal does not exceed
the threshold of alarm or protection operation set in the control device. For this reason, the system
has achieved significant results in the early detection of abnormality signs and the efficiency
improvement of the monitoring of large-scale gas turbines requiring the monitoring of a large
number of sensor signals (Figure 6).

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Figure 6 Abnormality sign detection by MT system

The failure area estimation program automatically estimates nonconforming points based on
pattern matching between sensor signal behavior and a nonconformance database (learningdatabase). When the MT system detects an abnormality, a nonconformity of a pattern close to thebehavior of the actual sensor signal is automatically extracted from the learning database, andnotification of the nonconformity and the inspection item for the nonconformity is made by email.
Using this information, the customer performs inspection and check (Figure 7).

Figure 7

Failure area estimation by pattern matching

A Pre-ACT web screen for the customer is also available. Figure 8 shows the web screen fora large gas turbine. This screen displays the power generation output and the trend of the MD value
during normal operation, and displays the sensor signal considered to be the cause of the increaseof the MD value and the top 10 ranking of the estimated nonconformity point when the system
detects an abnormality.

Figure 8 Web screen of Pre-ACT for large gas turbine

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64.3

MHPS-TOMONI Edge Enabler

We provide a device called MHPS-TOMONI Edge Enabler as a mechanism to efficiently
and effectively apply control expansion solutions such as performance enhancement andoperational improvement (Figure 9).
By installing the system at the edge and interfacing with the control device on the plantnetwork, it is possible to provide the results calculated and processed by the Edge Enabler to thecontrol device. By linking with DIASYS NetmationTM, which is our in-house developed control
device, more advanced plant control is realized.
The Edge Enabler also includes the functions of Secure Gateway, and can be connected
securely to the MHPS-TOMONI cloud. Periodic monitoring of the control improvement status by
MHPS makes it possible to provide the best condition. In addition, since the customer can selectwhether to enable or disable the function, it is possible to use the system while confirming thereturn on investment. The Edge Enabler is applied to the adjustment of the opening of a gas turbine
inlet guide vane (IGV), optimization of the gas turbine cooling air flow rate, automation of control
valve adjustment and digital twinning of a boiler(1).

Figure 94.4

Conceptual diagram of MHPS-TOMONI Edge Enabler

Support of customer's digitalization

In recent years, there have been an increasing number of cases where power generationcompanies themselves build monitoring systems that store, visualize and analyze operational datato inherit the knowledge of experts, nurture and secure young employees, operate a power plant asa stable social infrastructure and enhance their competitiveness through the use of ICT technology.
For these customers, as one of the MHPS-TOMONI services, our company utilizes our knowledgeof the power plant business and MHPS-TOMONI construction experience to support customers inestablishing their remote monitoring systems. Specifically, we propose an architecture thatconsiders the operational form and initial/running cost, provide security education and examine
connecting methods between the power plant and PI System.
In particular, in terms of security measures, since the number of connections between power
plants and external networks resulting from constructing remote monitoring systems is on the riseas mentioned above, we understand the overview of the security risks of power plants based on theglobal standard (IEC 62443-2-1) and support the formulation of action plans to deal with risks.

Mitsubishi Heavy Industries Technical Review Vol. 55 No. 4 (December 2018)7|5. Conclusion
This report introduced the platform, cloud/edge service and system architecture ofMHPS-TOMONI (thermal power generation digitalization). At present, many solutions are undertrial operation, but we will promote research and development in the future and create solutions
that further match customer needs. In addition, we will continue to provide highly-competitive
solutions by incorporating the latest technologies.
DIASYS NetmationTM and all related marks and logos are registered trademarks of Mitsubishi Hitachi Power
Systems, Ltd. in Japan and other countries.

References(1)

H. Aiki, et.al. Development of Boiler Digital Twin by Applying Machine Learning，Mitsubishi HeavyIndustries Technical Review，Vol.55 No.4 (2018)