introduction
With the large-scale integration of distributed photovoltaic (PV) power stations, their management has become increasingly challenging. Domestic and international scholars and enterprises have conducted extensive research on monitoring large-scale PV power station grid connection, achieving corresponding results and developing related products. In recent years, cloud computing technology has emerged, offering different application models from traditional methods. It features shared pooled resources, self-service, and pay-as-you-go payment, integrating resources through management middleware systems to improve efficiency. This paper develops a cloud-based remote monitoring system for PV power generation, based on a B/S architecture for real-time data acquisition and push, using SSH as the web framework. To address practical issues such as uneven distribution of PV sites and large volumes of monitoring data, cloud computing technology enables real-time monitoring and analysis of various types of current and voltage data from multiple sites, ensuring system stability and security. A well-designed SQL Server database, combined with local and cloud databases, enables cloud storage, computation, and retrieval of data, improving computational efficiency and real-time performance. A user-friendly interface is used to present data through reports and other visualization methods, enhancing system usability and ease of operation.
1
Photovoltaic power generation system
A photovoltaic (PV) power generation system is a device that converts solar energy into electrical energy using photovoltaic cells. Solar panels are the core component of a PV power generation system; they convert solar energy into electrical energy and, through series and parallel connections, increase the grid-connected voltage and capacity to meet grid connection requirements. Due to the volatility and intermittency of PV power generation systems, PV power plants are equipped with energy storage devices of a certain capacity to ensure stable output and improve the smoothness of the power plant's output. Therefore, in practical PV power plant systems, a controller is needed to control the charging and discharging of the batteries to ensure the normal operation of the batteries. The structure of a PV power generation system is shown in Figure 1.
A photovoltaic power generation system mainly consists of a photovoltaic array, a battery, a controller, and an inverter.
1.1 Battery Array
The core component of a photovoltaic (PV) power generation system is the PV cell. When the system requires a large output power, PV cells are typically connected in parallel or series to form a PV array. Currently, the most commonly used cells in the industry are composed of silicon cells, which can be divided into three different models based on the different arrangements of silicon crystals.
1.2 Inverter
Since photovoltaic cells output direct current (DC), while my country's power grid is primarily AC, photovoltaic power plants need to convert DC to AC to achieve grid connection. Inverters are crucial for grid connection of photovoltaic power plants, and their efficiency directly affects the efficiency of both the photovoltaic power plant and energy storage batteries. Therefore, the operating status of inverters needs to be monitored in real time.
1.3 Battery Pack
Photovoltaic power plants require energy storage systems of a certain capacity to improve the stability of the photovoltaic system's output. Energy storage typically uses battery banks, which can store excess electricity generated by the photovoltaic array and also supply power to connected loads. Batteries are a crucial component of the photovoltaic system's grid-connected control, playing a role in peak shaving and valley filling for the overall output of the photovoltaic power generation system. Therefore, the monitoring system must monitor the energy storage battery banks in real time.
1.4 Charge/Discharge Controller
Energy storage discharge controllers can protect battery banks and prevent shortened battery life due to overcharging and discharging. Furthermore, proper charge and discharge control can significantly improve the stability of photovoltaic system output. In photovoltaic monitoring systems, the operating parameters of the charge and discharge controller need to be collected and monitored in real time.
1.5 AC distribution cabinet
Grid connection of photovoltaic power plants requires an AC distribution cabinet. This cabinet not only converts data from backup inverters to ensure normal system operation, but also monitors the transmitted power. In a photovoltaic monitoring system, real-time data from the AC distribution cabinet needs to be collected and transmitted promptly.
2
Cloud computing platform architecture
Cloud computing has a broad definition. It's an internet-based computing model that provides network-based distributed storage, computing, and visualization. Network access is feasible, convenient, and on-demand. When a system receives an access request and enters the shared computing resource pool, it responds quickly, providing users with resources such as servers, networks, storage, services, and application software. Only minimal interaction is required between users and service providers, significantly reducing management workload. This is a major advantage of cloud computing. The backend of a cloud computing system has a unique network topology that rationally organizes a large number of servers, ensuring stable operation. This system uses the Microsoft Windows Azure Platform, providing a flexible pay-as-you-go service model based on Microsoft data centers. This cloud platform has the following characteristics: application development in the Microsoft cloud does not require deployment and maintenance by the enterprise itself, nor does it require attention to the underlying structure. Both Windows and Linux virtual machines can be used in the Microsoft cloud, and open-source tools (PHP, Node.js, etc.) are also supported. Therefore, users only need to flexibly deploy virtual machines and allocate storage space according to their actual needs, greatly reducing program debugging time and accelerating program development. To meet the growing demands of customers, this system can also expand externally according to business changes, providing more resources. The use of cloud computing has greatly reduced the cost of purchasing and maintaining hardware, and it can be used in conjunction with local IT facilities, enabling users to experience the process of management, virtualization, storage and development from local to the cloud in an integrated manner. The cloud platform architecture is shown in Figure 2.
3
Monitoring system design
3.1 Overall Structure of Photovoltaic Power Generation Monitoring System
To ensure the system's global reach and remote operation capabilities, all online monitoring and measurement equipment within the power plant will be centrally collected, analyzed, and managed. Monitoring data acquired during power plant operation will be categorized and stored according to data type and application characteristics. Staff at each level will focus only on the information relevant to their specific tasks. Furthermore, data at each level can be traced and queried from top to bottom.
This paper designs a novel photovoltaic power generation monitoring system that combines Windows Azure and the Web. Key features include: ① A user-friendly interface at the application layer, allowing for quick and easy operation by various clients; ② A B/S architecture, fully leveraging its advantages to reduce user workload and enable real-time operation; ③ The SSH integrated development framework, separating the system layers into presentation, business logic, data persistence, and module layers, facilitating development and maintenance; ④ Utilizing cloud computing's storage and powerful computing capabilities, the system is deployed on Windows Azure, reducing equipment costs and maintenance expenses; ⑤ The ECharts plugin at the front end provides graphical data processing, enabling comparative analysis of similar or different data over a specific time period to assess the photovoltaic power plant's operational status.
The system is divided into four layers: application layer, service layer, device driver layer, and data layer. Each layer processes different data, and the layers combine to form the user-facing system functions. User interaction with the system primarily occurs in the application layer. User needs are displayed intuitively in the application layer, and user operation commands and information are entered into the application layer before being passed to the service layer for processing. All business information data processing, computation, and control are performed in the service layer. Communication with devices is handled by the driver layer, which acquires device data and performs format conversion to ensure the system can correctly recognize it. Information communication with client-side field devices is bidirectional; information is sent to the devices in a format that the devices can recognize, ensuring the system can correctly transmit information to lower-level devices, as shown in Figure 3.
3.2 Photovoltaic Power Generation Monitoring System Module
This monitoring system analyzes various types of power plant data collected. The system modules mainly include four modules: data acquisition module, data communication module, database, and monitoring terminal.
3.2.1 Data Acquisition Module
The data acquisition module collects real-time operational data from the photovoltaic power station. The operation of the photovoltaic power station involves various types of data, including data from the photovoltaic array, inverter, environmental monitoring instruments, and meters. In addition to the basic data directly acquired by the equipment itself, some data requires calculations derived from the basic data. The structure of the data acquisition module is shown in Figure 4.
3.2.2 Data Communication Module
In on-site monitoring, the collected data needs to be securely and stably uploaded to the host computer and server. Therefore, communication not only needs to fulfill the basic function of data transmission, but also needs to ensure the accuracy, real-time performance, and security of the transmitted data. This system adopts the RS-485 serial communication standard and the Modbus communication protocol. This protocol defines the rules for communication between the master and slave devices, is independent of the physical layer, and works in conjunction with the RS-485 bus standard to achieve secure, stable, and reliable data transmission.
3.2.3 Database Module
The database is responsible for both front-end interface data retrieval and back-end data storage. Photovoltaic power generation monitoring systems require monitoring diverse data structures, and the database design and data model structure are crucial to data security, integrity, and maintainability. This system uses a SQL Server relational database to implement functions such as recording, filtering, editing, deleting, sorting, and grouping statistics for both structured and unstructured data. The cloud-based SQL Azure database and SQL Server database are synchronized using SQL Server Express. Furthermore, the system utilizes the Hibernate framework to separate the data layer from the business logic layer, reducing code complexity.
3.2.4 Monitoring Terminal
The on-site monitoring system mainly consists of a data acquisition module, a host computer, a data transmission channel, and a database. Various sensors are installed on the photovoltaic modules. Data such as voltage and current are sent to the data centralization module via these sensors. After filtering by the signal conditioning circuit, the data is categorized and analyzed. Data transmission and storage are achieved on-site via an RS-485 interface. The on-site monitoring system displays various component data, power generation, alarms, reports, and other information. Simultaneously, the module can be controlled via commands, such as module parameters and circuit breaker opening/closing information. The on-site monitoring structure is shown in Figure 5.
The on-site data monitoring terminal can provide staff with real-time and historical data information of the power station and display the operating status of the power station. The terminal monitoring function is shown in Figure 6.
Local data is received by a host computer and stored in a database. The cloud environment is configured and deployed using the Eclipse platform to transfer the local database to cloud storage, enabling data interaction between the cloud database and the front-end interface. Users can conveniently query information from various sites in a browser. The remote B/S service architecture is shown in Figure 7.
4
System Implementation
4.1 Login Module
The login module serves as the system's portal, providing functions such as new user login, registration, and account authentication. To enable data interaction between the front-end and back-end, Struts2 files need to be downloaded and configured. The login module receives user login signals, uses a judgment mechanism to verify login security, and employs an interceptor to block accounts. The main interface includes power plant operation overview information and other functional options.
4.2 Administrator Module
Administrators can use permission settings to modify their own information, manage and modify user data, and send system announcements. When there are important events or notices for the company or power station, sending notifications one by one is impractical. Administrators can upload, modify, and delete announcements, while ordinary users can view and download them. Staff are the primary users of this system, mainly responsible for the operation and maintenance of the photovoltaic power station platform. They need to monitor the basic equipment status information, alarm system, real-time data, fault information data, detection data, and alarm information of the power station in a timely manner.
4.3 Monitoring Function Module
The data monitoring functions of this system are mainly divided into two categories: real-time data monitoring and historical data monitoring. Real-time data monitoring mainly displays the real-time operation data of the power station, and users can access relevant information according to their needs. Real-time data is obtained by the acquisition equipment and written to the database, and is retrieved when a user sends a real-time data request. Historical data monitoring refers to the system's ability to access historical cloud data for historical data analysis. The equipment information table query mainly displays information about the grid-connected power station equipment in the subsystem, showing the operation information of equipment such as DC cabinets, inverters, and high-voltage cabinets within the station. Its interface is shown in Figure 8.
In addition, the system has powerful data visualization capabilities, extracting power data from the database and processing the data using relevant graphics device interfaces and Java plugins. For example, it generates power curves after processing the power information, allowing users to observe and analyze the trend of power output from grid-connected generators over time. This function not only allows users to query data for the current day but also historical data. Users can select the desired time and station based on the calendar, as shown in Figure 9.
Figure 10 is a bar chart of monthly power generation in August 2016, showing the monthly power output on a daily basis. The monthly power curves are used to compare and analyze the daily, monthly, and yearly power output of the photovoltaic power generation system, improving the system's analytical and display capabilities. The main station information aggregates data from all connected subsystems and provides an interface for accessing substation information, as shown in Figure 11.
The alarm query primarily displays alarm time, location, resolution status, and fault information in a table format. Users can query by alarm information and alarm status. Alarm prompts are provided for situations such as excessive current or a sudden drop in power generation.
5
Introduction to Acrel Distributed Photovoltaic Operation and Maintenance Cloud Platform
5.1 Overview
The AcrelCloud-1200 distributed photovoltaic (PV) operation and maintenance cloud platform helps users manage PV sites scattered across various locations by monitoring inverter equipment, meteorological equipment, and camera equipment at PV sites. Key functions include: site monitoring, inverter monitoring, power generation statistics, inverter primary circuit diagrams, operation logs, alarm information, environmental monitoring, equipment files, operation and maintenance management, and role management. Users can access the platform via web and mobile app to monitor PV power generation efficiency and revenue in real time.
5.2 Application Scenarios
Currently, the two main distributed photovoltaic application scenarios in my country are: household photovoltaic systems on rural rooftops and rooftop photovoltaic systems on industrial and commercial enterprises. Both types of distributed photovoltaic power stations have developed rapidly this year.
5.3 System Structure
Inverters and multi-functional power metering instruments are installed in the photovoltaic substation. Data collected is uploaded to a server via a gateway and centrally stored and managed. Users can access the platform via PC to obtain real-time information on the operation of the distributed photovoltaic power station and the status of each inverter. The overall platform structure is shown in the figure.
5.4 System Functions
AcrelCloud-1200 distributed photovoltaic operation and maintenance cloud platform software adopts a B/S architecture. Any user with the necessary permissions can monitor the operation status of photovoltaic power stations distributed in various buildings within the area (such as the geographical distribution of power stations, power station information, inverter status, power generation curve, grid connection status, current power generation, total power generation, etc.) through a web browser according to their permission scope.
5.4.1 Photovoltaic power generation
5.4.1.1 Comprehensive Dashboard
● Displays the number of all photovoltaic power plants, their installed capacity, and real-time power generation.
●Cumulative daily, monthly, and annual power generation and revenue.
● Cumulative social benefits.
● Bar chart showing monthly power generation
5.4.1.2 Power Plant Status
● Power station status display shows the current photovoltaic power station's power generation capacity, subsidy price, peak power and other basic parameters.
●Statistics on the daily, monthly, and annual power generation and revenue of the current photovoltaic power station.
●The camera monitors the on-site environment in real time and integrates environmental parameters such as irradiance, temperature, humidity, and wind speed.
● Displays the number of inverters connected to the current photovoltaic power station and their basic parameters.
5.4.1.3 Inverter Status
●Inverter basic parameter display.
● Display of daily, monthly, and annual power generation and revenue.
● Display inverter power and ambient irradiance curves using graphs.
● DC side voltage and current query.
●Query AC voltage, current, active power, frequency, and power factor.
5.4.1.4 Power Generation Statistics
● Displays hourly, daily, monthly, and annual power generation statistics reports for the selected power station.
5.4.1.5 Inverter Power Generation Statistics
● Displays hourly, daily, monthly, and yearly power generation statistics reports for the selected inverter.
5.4.1.6 Power Distribution Diagram
● Real-time display of data from both the AC and DC sides of the inverter.
● Displays the number of components currently connected to the inverter.
● Displays current environmental parameters such as irradiance, temperature, humidity, and wind speed.
● Showcase inverter models and manufacturers.
5.4.1.7 Inverter Curve Analysis
● Displays AC and DC side voltage, power, irradiance, and temperature curves.
5.4.2 Event Log
● Operation Log: User login status query.
●SMS Log: Query SMS push time, content, sending result, reply, etc.
●Platform operation log: View the offline status of instruments and gateways.
● Alarm Information: Alarms are classified and processed according to their severity, and the alarm content, occurrence time, and confirmation status are recorded.
5.4.3 Operating Environment
● Video surveillance: The operation of the photovoltaic station can be monitored in real time through video cameras installed on site. For cameras with the necessary hardware, video playback and PTZ control functions are also supported.
5.5 System Hardware Configuration
5.5.1 220V AC grid connection
220V AC grid-connected photovoltaic power generation systems are mostly used for residential rooftop photovoltaic power generation, with an installed capacity of around 8kW.
Some small-scale photovoltaic (PV) power plants operate on a self-consumption model, with surplus electricity not fed into the grid. These types of PV power plants require the installation of anti-reverse current protection devices to prevent the transmission of electricity to the grid. PV power plants are relatively small in scale and dispersed, making cloud platform management essential for their managers. Acrel's solutions for these types of PV power plants include the following:
5.5.2 380V AC grid connection
According to the State Grid's Q/GDW1480-2015 "Technical Regulations for Distributed Power Generation Access to the Grid," photovoltaic power stations with capacities between 8kW and 400kW can be connected to the grid at 380V. For photovoltaic power stations exceeding 400kW, multi-point 380V grid connection may be adopted depending on the circumstances, subject to the approval of the local power department. These distributed photovoltaic systems are mostly rooftop photovoltaic systems for industrial and commercial enterprises, used for self-consumption with surplus electricity fed into the grid. Before connecting distributed photovoltaic systems to the distribution network, metering points should be clearly defined. The setting of metering points should consider not only the property boundary but also the location of the distributed power source outlet and the user's self-use power line. Each metering point should be equipped with a bidirectional energy metering device, whose equipment configuration and technical requirements comply with the relevant provisions of DL/T448, as well as relevant standards and regulations. Smart meters should be used, and their technical performance should meet the relevant standards of the State Grid Corporation of China for smart meters. Distributed power generation metering devices used for settlement and assessment should be equipped with data acquisition equipment and connected to the electricity consumption information acquisition system to achieve remote automatic collection of electricity consumption information.
The photovoltaic array is connected to a string photovoltaic inverter, or to the inverter via a combiner box, and then connected to the enterprise's 380V power grid to achieve self-consumption of electricity and grid connection of surplus power. A meter needs to be installed before the 380V grid connection point to measure photovoltaic power generation. A bidirectional meter also needs to be installed at the connection point between the enterprise's power grid and the public power grid to measure the enterprise's grid-connected electricity. All data should be uploaded to the power supply department's electricity information collection system for photovoltaic power generation subsidies and grid-connected electricity settlement.
Some photovoltaic (PV) power plants require monitoring of power quality at their grid connection points, including power frequency, voltage magnitude, voltage imbalance, voltage spikes/drops/interruptions, rapid voltage changes, harmonics/interharmonics (THD), flicker, etc., necessitating the installation of separate power quality monitoring devices. Some PV power plants operate on a self-consumption model, with surplus power not fed into the grid. These types of PV power plants require the installation of backflow prevention devices to prevent the transmission of power to the grid. A system diagram is shown below.
This grid-connected photovoltaic power plant is of moderate size and can utilize photovoltaic power generation data and energy storage system operation data through a cloud platform. Acrel's solutions for this type of photovoltaic power plant include the following aspects:
5.5.3 10kV or 35kV grid connection
According to the "Notice of the National Energy Administration on Relevant Matters Concerning the Construction of Wind Power and Photovoltaic Power Generation Projects in 2019" (Guofa Xineng [2019] No. 49), newly built industrial and commercial distributed photovoltaic power generation projects that require national subsidies must meet the requirements that the single-point grid-connected installed capacity is less than 6 MW and is not for residential use. Under the premise of meeting the technical requirements for grid operation safety, they are supported to access the distribution system through multiple internal points.
These types of distributed photovoltaic (PV) installations typically have large capacities and require step-up transformers to boost the voltage before connecting to the grid. Due to their large capacity, they can cause significant interference to the public power grid. Therefore, power supply departments have high requirements for the stability control system, power quality, and communication with dispatching for distributed PV power plants of this scale.
Photovoltaic power plants need to monitor the power quality at the grid connection point, including power frequency, power voltage magnitude, voltage imbalance, voltage surge/dip/interruption, rapid voltage changes, harmonics/interharmonics (THD), flicker, etc., requiring the installation of a separate power quality monitoring device.
The diagram above shows a schematic of a 1MW distributed photovoltaic (PV) power station. The PV array is connected to a PV combiner box, and after passing through a DC switchgear, it is connected to a centralized inverter (the DC switchgear may or may not be required). Finally, the voltage is stepped up to 10kV or 35kV by a step-up transformer and then connected to the medium-voltage grid. Because PV power stations have a relatively large installed capacity, there are many protection and control devices involved, mainly as shown in the table below:
6
Conclusion
To address the shortcomings of current photovoltaic (PV) power generation monitoring systems in monitoring large-scale PV power plants connected to the grid, this paper proposes a cloud-based PV power generation system monitoring platform. By analyzing the technical architecture of existing monitoring systems, this paper fully leverages the centralized processing and storage scalability of cloud technology, reducing the economic cost of hardware facilities and facilitating subsequent system maintenance. Through analyzing the data acquisition module of the PV monitoring system, studying the hardware structure and communication connection methods of PV power plant inverters, environmental monitors, and data concentrators, a master-slave control system based on the Modbus communication protocol is designed between the host computer and various devices to achieve the goal of uploading data collected by the acquisition module to the host computer and the cloud platform. Finally, the feasibility and reliability of the system are verified through application in a real PV power plant.
