System Intro
The combination of PV, BESS, Wind, Hydro, Diesel generators offers all the advantages of the respective systems while eliminating their possible weaknesses: Solar electricity is comparatively cheap and creates almost no maintenance costs. Yet, its availability is limited to the daytime (as long as no storage devices are implemented). Diesel generators offer power all around the clock, but inevitably drive costs up.
However, the key to tapping the enormous potential of hybrid solutions is an advanced intelligent management of the power sources involved: The Sinosoar Hybrid System operates on an intelligent control unit which ensures that as much PV-energy as possible is used and still keeps the genset in its optimum working range. In this manner, Sinosoar Hybrid System offers all the benefits of a hybrid system.
System Preview



High Light
01
Energy Management
Smart Management
Reduce Fluctuation
Seamless Switchover

02
Plug-in Design
Modular Design
Compatible with all Sources
Flexible Extension

03
Web Based SCADA
Visible Control
Integrate with EMS
Fault/ Warning Alarm

04
Optimization LOCE
Improve RE Generation
Reduce fuel consumption
Improve Grid Quality

System Intro
SINOSOAR Hybrid GDP (Global Data Platform – Supervisory Control And Data Acquisition) is a micro-grid information management system supported by cloud computing, Internet of Things and other technologies which is independently developed by Sino Soar Hybrid (Beijing) Technology Co., Ltd. It is designed to provide intelligent monitoring, O&M services, as well as the full life cycle management of micro-grid solar plants for business owners and third-party O&M companies.
SINOSOAR Hybrid GDP could fulfill the full life cycle management of distributed power plants, industrial hybrid power plants, and power plants located in the remote area. It could improve the power supply efficiency of the plant and lower the cost of operation. Meanwhile, it supports third-party access.
The GDP system is based on the SAAS platform, users only need to log in the account to enjoy all the needed services. The system has the functions of real-time data display, power generation statistical reports, event records and so on. It is characterized by supporting Center SCADA, remote control, and other functions. The publishing is in WEB mode and it supports multi-platform and multi-terminal (browser, mobile APP) data access.
System Preview
High Light
1 User Friendly Multifunctional | The GDP System has “Center SCADA” function, and it supports web browser and mobile APP access. No matter when and where, users can conveniently monitor and manage all links of the power station. | 2 Remote Control Efficient Management | The GDP System is based on the Internet of Things technology and Hadoop technology. It helps customers realize centralized O&M management of multiple energy sources. GDP can perform real-time data collection, equipment remote control, measurement, parameter adjustment, and various signal alarms etc. |
3 Fault Alarm Data Report | The GDP System is equipped with a formidable cloud Hadoop platform and integrated with the data collection system to fully guarantee the different management needs of users at all stages of the power plant and ensure the stable operation of the power plant. | 4 Improve Efficiency Reduce Costs | The remote centralized O&M mode eliminates the needs of arranging a large number of management personnel and a large number of on-site inspections to save the management costs. |
5 Data Encryption Global Coverage | The system can collect data from global power plants which are connected to the internet, It adopts TSL encrypted channels for data transmission and HTTS for data access. At the same time, it applies the AWS data backup technology to achieve data security. | 6 Easy Access Plug & Play | The GDP System is based on the Saas account service and it connects with the EMS through SINOSOAR communication management machine which is convenient for access. Users only need to log in their account to access all authorized services. |
SINOSOAR Hybrid GDP
