There are problems such as low scalability and low convergence accuracy in the economic dispatch of smart grids. To address these situations, this study considers various constraints such as supply-demand balance cons...
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There are problems such as low scalability and low convergence accuracy in the economic dispatch of smart grids. To address these situations, this study considers various constraints such as supply-demand balance constraints, climb constraints, and capacity constraints based on the unified consensus algorithm of multi-agent systems. By using Lagrange duality theory and internal penalty function method, the optimization of smart grid economic dispatch is transformed into an unconstrained optimization problem, and a distributed second-order consistencyalgorithm is proposed to solve the model problem. IEEE6 bus system testing showed that the generator cost of the distributed second-order consistencyalgorithm in the first, second, and third time periods was 2.2475 million yuan, 5.8236 million yuan, and 3.7932 million yuan, respectively. Compared to the first-order consistencyalgorithm, the generator cost during the corresponding time period has increased by 10.23%, 11.36%, and 13.36%. The actual total output has reached supply-demand balance in a short period of time with the changes in renewable energy, while maintaining supply-demand balance during the scheduling process. The actual total output during low, peak, and off peak periods was 99MW, 147MW, and 120MW, respectively. This study uses distributed second-order consistencyalgorithm to solve the economic dispatch model of smart grid to achieve higher convergence accuracy and speed. The study is limited by the assumption that the cost functions of each power generation unit are quadratic convex cost functions under ideal conditions. This economic dispatch model may not accurately reflect practical applications.
Renewable and clean energy power generation has effectively reduced the carbon emissions of thermal power generation. Vigorously developing renewable energy power generation is an important way to achieve the dual car...
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Renewable and clean energy power generation has effectively reduced the carbon emissions of thermal power generation. Vigorously developing renewable energy power generation is an important way to achieve the dual carbon goal. The energy dispatching of DC microgrids is flexible and fast and has gradually become an important part of the distribution network. However, the distributed renewable energy generation in the DC microgrid is intermittent and random, resulting in large output fluctuations. To address the energy coordination control of DC microgrid distributed generation units, a distributed consistency algorithm-based energy optimization strategy that takes into consideration power generation costs is proposed. Graph theory is used to construct the multi-agent communication architecture of the DC microgrid for wind turbines, diesel storage, and charging. With the control goal of reducing bus voltage fluctuation and power-producing cost, distributed micro source and load power balancing equations were created. The micro source constraint equations are used to construct the equal consumption micro increment function. The microgrid utilizes the distributedconsistency approach to enhance the power distribution of wind turbine diesel storage and charging. The simulation results demonstrated that the proposed strategy maximizes distributed renewable energy generation capacity, decreases DC bus voltage fluctuation, and achieves power balance and optimal control of a DC microgrid. (c) 2023 Published by Elsevier Ltd.
At present, battery energy storage systems (BESS) have become an important resource for improving the frequency control performance of power grids under the situation of high penetration rates of new energy. Aiming at...
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At present, battery energy storage systems (BESS) have become an important resource for improving the frequency control performance of power grids under the situation of high penetration rates of new energy. Aiming at the problem that the existing control strategy is not sufficient for allocating the frequency regulation power instructions, a hierarchical distributed coordinated control strategy for BESS to participate in the automatic generation control (AGC) of a regional power grid is proposed. At the upper layer, the state of charge (SOC) of BESS and the technical characteristics of different frequency regulation power sources are comprehensively considered to complete the coordinated distribution of frequency regulation commands between BESS and traditional generators;at the lower layer, for the purpose of optimizing the economic operation of the regional power grid, the distributed consistency algorithm is used to control the distributed BESS in order to realize the fine management of power output of BESS. The simulation results indicate that this control strategy can give full play to the technical characteristics of different frequency power sources and improve the frequency regulation of the power grid. The excessive power consumption of BESS is successfully avoided, and the continuous operation of BESS is realized.
In large-scale asynchronous distributed virtual environments(DVEs), one of the difficult problems is to deliver the concurrent events in a consistent order at each node. Generally, the previous consistency control app...
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In large-scale asynchronous distributed virtual environments(DVEs), one of the difficult problems is to deliver the concurrent events in a consistent order at each node. Generally, the previous consistency control approaches can be classified into two categories: causal order and time stamped order. However, causal order approaches can merely preserve the cause-effect relation of events and time stamped order approaches seem intrinsically complex to be used in serverless large-scale asynchronous DVEs. In this paper, we proposed a novel distributedalgorithm to identify the concurrent events and preserve the consistent order delivery of them at different nodes. Simulation studies are also carried out to compare the performance of this algorithm with that of the previous ones. The results show that the new algorithm can effectively deliver the concurrent events in consistent order at each node and is more efficient than the previous algorithms in large-scale asynchronous DVEs.
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