Computer network distributed monitoring and centralized forecasting of utility distribution system operations

Renewable-energy powered distributed generations (DGs) of electricity are becoming popular and start to show benefits, but their connection to the utility distribution systems brings operation challenges and supply uncertainty that must be carefully monitored and forecasted to provide data for correct controls of the systems. This paper proposes a new strategy for distributed monitoring and centralized forecasting of utility electricity distribution systems connected with DGs. The paper illustrates functional implementation for the distributed monitoring and centralized forecasting operations utilizing high-speed digital signal processing (DSP) technology and network classified data transmission (CDT) algorithm. The design of a new DSP-based network monitoring architecture is provided. This architecture is fault tolerant and has features from classical cascading, star, and ring architectures. The paper presents the CDT-based real-time data acquisition and DSP-based data post-processing strategy, design, and implementation.