Related Experiment Video
Updated: Aug 24, 2025
05:30
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
637
Distributed Cluster Regulation Strategy of Multipark Integrated Energy System Using Multilayer Deep Q Learning
Chaoqun Zhu1, Jie Shen1, Jie Li1
1State Grid Corporation of China, Marketing Department of Suzhou Branch, Suzhou 215000, China.
Computational Intelligence and Neuroscience
|October 24, 2022
Summary
This study introduces a new coordinated control strategy for multi-park integrated energy systems (MPIES). The method enhances power generation and consumption balance by leveraging flexible energy substitution across interconnected parks.
Area of Science:
- Energy Systems Engineering
- Control Theory
- Artificial Intelligence
Background:
- The power system is transitioning towards integrated energy systems.
- Park integrated energy systems (PIES) are evolving to multipark integrated energy systems (MPIES) for improved balance.
- Collaborative control strategies are crucial for MPIES performance.
Purpose of the Study:
- To develop a coordinated control strategy for MPIES.
- To enhance the power generation and consumption balance capacity of integrated energy systems.
- To fully utilize the regulation capacity of individual PIES through flexible energy substitution.
Main Methods:
- Analysis of regulation resources and incentive mechanisms on PIES flexibility.
- Development of a distributed cluster regulation model for MPIES using Markov decision process.
- Implementation of a multilayer deep Q network (MLDQN) for distributed cluster regulation optimization.
Main Results:
- The proposed strategy effectively coordinates regulation abilities across multiple PIES.
- The method capitalizes on the large-scale advantages of interconnected park energy systems.
- Overall stability of the multipark integrated energy system is significantly improved.
Conclusions:
- The coordinated control strategy enhances the stability and balance of MPIES.
- Flexible energy substitution and distributed optimization are key to MPIES performance.
- This approach provides a robust framework for managing complex, interconnected energy systems.
Related Concept Videos
01:22Multi-input and Multi-variable systems
139
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
In the absence...
139
01:21Distributed Loads: Problem Solving
697
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
697
01:37Neural Regulation
39.7K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
39.7K
01:26PD Controller: Design
318
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
318
01:25Multimachine Stability
216
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
216
01:27Transformers in Distribution System
142
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
142