SPACE Grid: Smart and distributed Power Architecture and Control for Electrical Grid

2019 ◽  
Author(s):  
Quentin Hilpert ◽  
Stephane Caux ◽  
Francois Bonnet ◽  
Marc Malagoli
Keyword(s):  
Distributed Power ◽  
Electrical Grid ◽  
Space Grid ◽  
And Control ◽  
Power Architecture

Development of Modern Electronic Control Systems for Power Distribution

2002 ◽  
Author(s):  
Brian D. Gaffney
Keyword(s):  
Control System ◽  
Control Systems ◽  
Power Distribution ◽  
Power Plants ◽  
Distribution Systems ◽  
Electronic Control ◽  
Distributed Power ◽  
Future Needs ◽  
And Control

The power industry is increasingly affected by several trends, which require improvements in the distributed generation and control systems of on-site power. These trends include the ability to share load across generators more effectively, seamless sequencing of generators, and the ability to monitor and control power that is being produced. Electronic control systems can provide these advantages in a cost effective solution. The application of electronic controls to a power distribution system requires a thorough development program. It is imperative to assure that the controls will provide reliable, long-term performance, as well as meeting the plant’s current and future needs for power distribution. This paper describes the development and field evaluation required to apply electronic controls to existing switchgear and power distribution systems in the power generation industry. The microprocessor based electronic control system for today’s power plants replaces out-dated analog equipment and antiquated relay logic. The new systems incorporate three main functions: Paralleling generators, monitoring power requirements, and effective sequencing of generators in power plants. Integration of these functions into the microprocessor based control system provides increased reliability, reduced cost, and enhanced performance, while concurrently providing increased flexibility in the operation of the plant. Additional benefits can be realized including reduced operator requirements, reduced training costs, and reduced burden on instrumentation electricians. A primary focus of this paper is the process used to qualify the control system needed for specific types of existing distributed power systems. This process consists of current system evaluation and categorization, establishment of classification of plant (utility, merchant plant, peak shaving facility, IPP), and determining the future needs of individual plants for power distribution. Local regulatory and utility protection and interconnect requirements must also be assessed to assure that the new control system meets or exceeds them. Methods of accurately monitoring, improving performance, and providing generator sequencing are defined, including accounting for improvements in the long-term expansion of the distributed power control and monitoring system.

scholarly journals Development of Digital Twin for Load Center on the Example of Distribution Network of an Urban District

2020 ◽  
Vol 209 ◽  
pp. 02029
Author(s):  
Nikita Tomin ◽  
Victor Kurbatsky ◽  
Vadim Borisov ◽  
Sergey Musalev
Keyword(s):  
Data Exchange ◽  
Physical Object ◽  
Electrical Network ◽  
Urban District ◽  
Automatic Data ◽  
Electrical Grid ◽  
Digital Twin ◽  
Node Network ◽  
Optimization And Control ◽  
And Control

The paper proposes a concept of building a digital twin based on the reinforcement learning method. This concept allows implementing an accurate digital model of an electrical network with bidirectional automatic data exchange, used for modeling, optimization, and control. The core of such a model is an agent (potential digital twin). The agent, while constantly interacting with a physical object (electrical grid), searches for an optimal strategy for active network management, which involves short-term strategies capable of controlling the power supplied by generators and/ or consumed by the load to avoid overload or voltage problems. Such an agent can verify its training with the initial default policy, which can be considered as a teacher’s advice. The effectiveness of this approach is demonstrated on a test 77-node scheme and a real 17-node network diagram of the Akademgorodok microdistrict (Irkutsk) according to the data from smart electricity meters.

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