An Optimal Allocation Strategy for Multienergy Networks Based on Double‐Layer Nondominated Sorting Genetic Algorithms

Mou, Min; Lin, Da; Zhou, Yuhao; Zheng, Wenguang; Ruan, Jiongming; Ke, Dongdong

doi:10.1155/2019/5367403

Cited by 4 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e hydraulic model and thermal model can be obtained from the thermal system model. Combined with these two models, they can be transformed into the general power flow model of the thermal subsystem [17], as shown in (18):…”

Section: Ermal Network Subsystemmentioning

confidence: 99%

See 1 more Smart Citation

Integration and Modeling of Multi‐Energy Network Based on Energy Hub

et al. 2022

Self Cite

View full text Add to dashboard Cite

The energy conversion units and energy storage equipment connected to the multi-energy system are becoming diversified, and the uncertain factors brought by distributed wind power and photovoltaic power generation make the system energy flow structure more complex, which brings great difficulties to the modeling and application of traditional energy hub modeling methods. This study deeply analyzes the multi-energy flow coupling structure and operation mechanism of multi-energy systems, and carries out the power flow calculation and analysis of multi-energy systems based on an energy hub, so as to ensure the safe and stable operation of regional energy. Based on the physical characteristics of energy systems such as power systems, thermal systems, and gas systems, this article studies the comprehensive power flow model including the electric-gas-thermal multi-energy coupling network and proposes the power flow decomposition of the energy supply subsystem and its applicable equation based on Newton–Raphson method. The effectiveness of the proposed method under different operation modes is verified by case studies. The calculation results show that under constant load, the energy hub running in fixing thermal by electricity (FEL) and fixing electricity by thermal (FTL) mode has little influence on the voltage of each node in the power sub-network. Within the constraint range, the natural gas flow obtained from the natural gas subsystem is coupled with the power subsystem to meet the load demand. The influence on the power flow at each node of the heat network is not obvious.

show abstract

Section: Ermal Network Subsystemmentioning

confidence: 99%

“…(1) Input the original data of the thermal system, including network topology and node parameters; classify and number the nodes, and select the balance node of the heating network [18,19]…”

Section: Ermal Network Subsystemmentioning

confidence: 99%

Integration and Modeling of Multi‐Energy Network Based on Energy Hub

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Multisource coordination is a kind of power supply method which adopts multiple types of distributed power supply and utilizes the complementary characteristics of different distributed power supplies to improve the output characteristics of distributed power supply [27,28]. For example, solar energy and wind energy have strong intermittency and fluctuation, respectively, so the output power of solar power generation device and wind power generation device also has intermittency and fluctuation.…”

Section: Multisource Coordinated Control Strategymentioning

confidence: 99%

Modeling and Control Strategy for Multiterminal Flexible DC Distribution Network with Echelon Utilization Power Battery

et al. 2021

Self Cite

View full text Add to dashboard Cite

With the integration of distributed renewable energy to the distribution network and the development of multiterminal flexible DC transmission technology, multiterminal flexible DC distribution network has broad application prospects. At the same time, with the rapid development of new energy vehicles, the echelon utilization of power battery has become a research hotspot. By analyzing the characteristics of flexible DC distribution network and echelon utilization battery, the structure and control strategy of modular multilevel converter (MMC), DC solid-state transformer, photovoltaic power generation, wind power generation, and echelon utilization battery energy storage system are established, respectively, in this paper. To achieve a DC network connection of various types of power supply and load, this paper proposes a starting method of multiterminal flexible DC distribution network and a cooperative control strategy of the wind-solar-storage system. A six-terminal ring-shape DC distribution network model is built in real-time digital simulation (RTDS) platform. The simulation results show that the modeling methods and control strategies of each component in the real-time simulation model meet the operation requirements of the multiterminal flexible DC distribution network, which provides a reference for the construction and research of the flexible DC distribution network.

show abstract

“…In this paper, a real-time optimal control strategy of multienergy complementary microgrid system based on double-layer nondominated sorting genetic algorithm is proposed to optimize the multienergy complementary microgrid system in real-time and reasonable distribute the output of each energy supply end [8,9]. In this paper, a typical multienergy complementary microgrid system is studied.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Optimal Control Strategy for Multienergy Complementary Microgrid System Based on Double-Layer Nondominated Sorting Genetic Algorithm

et al. 2020

Self Cite

View full text Add to dashboard Cite

Because of the problems of low operation efficiency and poor energy management of multienergy input and output system with complex load demand and energy supply, this paper uses the double-layer nondominated sorting genetic algorithm to optimize the multienergy complementary microgrid system in real-time, allocating reasonably the output of each energy supply end and reducing the energy consumption of the system on the premise of meeting the demand of cooling, thermal and power load, so as to improve the economy of the whole system. According to the system load demand and operation mode, the first layer of this double-layer operation strategy calculates the power required by each node of the microgrid system to reduce the system loss. The second layer calculates the output of each equipment by using nondominated sorting genetic algorithm with various energy values calculated in the first layer as constraint conditions, considering the operation characteristics of various equipment and aiming at economy and environmental protection. In this paper, a typical model of energy input-output is established. This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.

show abstract

An Optimal Allocation Strategy for Multienergy Networks Based on Double‐Layer Nondominated Sorting Genetic Algorithms

Cited by 4 publications

References 23 publications

Integration and Modeling of Multi‐Energy Network Based on Energy Hub

Integration and Modeling of Multi‐Energy Network Based on Energy Hub

Modeling and Control Strategy for Multiterminal Flexible DC Distribution Network with Echelon Utilization Power Battery

Real-Time Optimal Control Strategy for Multienergy Complementary Microgrid System Based on Double-Layer Nondominated Sorting Genetic Algorithm

Contact Info

Product

Resources

About