Distribution Network Management via Dynamic Energy Router Control
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Solution Overview
Problem
Existing centralized power generation systems face challenges in quickly and efficiently managing increased electric power demand, particularly due to the variability in power generation from new renewable energy systems like photovoltaic and wind power, which can lead to unstable voltage and frequency issues in distribution networks, potentially causing equipment malfunction.
Innovation Solution
A distribution network management system that employs energy routers for bidirectional power conversion, with a management apparatus adjusting communication cycles of command values based on energy router states, such as control success rates and available resources, to stabilize the network and manage variability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If new renewable energy generation systems are integrated into the distribution system, then environmental preservation is improved and power generation capacity is increased, but voltage and frequency stability deteriorate due to variability in power generation
Solution Approach 1:
An energy router is introduced as an intermediary device between the renewable energy generation system and the distribution network. The energy router includes bidirectional power conversion units that convert DC power from photovoltaic panels or other renewable sources into AC power suitable for the distribution network, and control units that manage power flow to maintain voltage and frequency stability despite variability in renewable energy generation.
Solution Approach 2:
The system dynamically adjusts operational parameters including communication cycles and command values based on the state of energy routers and variability conditions. When variability is detected, the management apparatus modifies communication frequencies and power conversion parameters to maintain stable voltage and frequency levels in the distribution network.
2Measurement precision
If communication cycle is shortened to improve control responsiveness, then control precision is improved, but computational load and energy consumption increase
Solution Approach 1:
The communication cycle is made dynamic rather than fixed. The management apparatus adjusts the communication cycle based on the state of energy routers and the level of variability detected. When the system operates normally, longer communication cycles reduce computational load. When variability is detected or control success rates drop, the communication cycle is automatically shortened to improve control precision, creating an adaptive balance between responsiveness and energy consumption.
3Reliability
If processing optimization operation is performed for all energy routers, then network stability is improved, but computational complexity increases
Solution Approach 1:
The system applies different processing optimization operations to different energy routers based on their individual states and control success rates. Rather than uniformly processing all energy routers, the management apparatus identifies specific routers that require attention and applies optimization operations selectively. This localized approach maintains network stability for critical routers while reducing overall computational complexity.
Data Source
AI summary
An embodiment provides system for managing a distribution network, the system including: a plurality of energy routers configured to control the amount of router power flowing between the distribution network and internal resources; and a distribution network management apparatus configured to transmit a command value for the amount of router power, which is produced according to variability of the distribution network, to the energy router while adjusting a communication cycle of the command value depending on a control success rate of the energy router for the command value.