Xu Fan, Zhang Dengping
State Power Investment Ronghe Investment Co., Ltd., Qinghai Huanghe Hydropower Development Co., Ltd., Xining, Qinghai, China.
Sinohydro Engineering BUREAU 4 Co., Ltd., Power Construction Corporation of China, Xining, Qinghai, China.
PLoS One. 2025 May 29;20(5):e0323340. doi: 10.1371/journal.pone.0323340. eCollection 2025.
As high-frequency technological developments happen and the variety of Microgrids (MG) grows, microgrids are going to be able to secure their own usage while competing in the electricity sector. To optimize each individual's earnings, the most efficient bidding approach for the transaction process is determined using a novel customized hunter prey optimization (CHPO), it has been established with blockchain technology and shown as a MG transactional framework in this research. To address the issue of energy underuse in a MG gaming competition, research have developed the CHPO, an innovative technique in the most effective bidding approach for the transaction process. Two market participants such as Major Users (MU) and Users of Microgrid (UoM) were explored for the performance in energy transactions. The market participants performance was creating various methods for buying and selling power at various locations in the MG framework to enhance the participant's desires and power developments in the market. In addition, the main market participants are employed as study subjects to develop a distributed energy resources (DERs) integration system that addresses the issue of real-time power pricing. The design comparison is analyzed with an authentication paradigm to demonstrate its applicability to microwave, optical, and radio frequency (RF) technologies. In addition, the main market participants are employed as research subjects to develop a DERs integration system that addresses the issue of real-time power pricing. The design comparison is analyzed with an authentication paradigm to demonstrate its applicability to microwave, optical, and RF technologies. The CHPO method demonstrated high efficiency with a mean convergence time of 54 iterations and an interval of 240, which makes it scalable. It ensures low latency at 45ms, and the unit operation metrics (UoM) range from 2,402,077-2,935,889, which is quite robust. The CHPO method also performed better in RMSE at 4.75, MAPE at 10.12, MAE at 2.31.
随着高频技术的发展以及微电网（MG）种类的增加，微电网将能够在电力领域竞争的同时确保自身的用电需求。为了优化每个个体的收益，使用一种新颖的定制猎食者猎物优化算法（CHPO）来确定交易过程中最有效的投标方法，该算法基于区块链技术构建，并在本研究中作为微电网交易框架呈现。为了解决微电网博弈竞赛中的能源利用不足问题，研究人员开发了CHPO，这是一种用于交易过程最有效投标方法的创新技术。研究探讨了主要用户（MU）和微电网用户（UoM）这两类市场参与者在能源交易中的表现。市场参与者的表现是在微电网框架内的不同地点创建各种电力买卖方法，以增强参与者在市场中的需求和电力发展。此外，主要市场参与者被用作研究对象，以开发一个解决实时电价问题的分布式能源资源（DERs）集成系统。通过认证范式对设计进行比较分析，以证明其对微波、光学和射频（RF）技术的适用性。此外，主要市场参与者被用作研究对象，以开发一个解决实时电价问题的DERs集成系统。通过认证范式对设计进行比较分析，以证明其对微波、光学和RF技术的适用性。CHPO方法表现出高效性，平均收敛时间为54次迭代，间隔为240，具有可扩展性。它确保了45毫秒的低延迟，单位运行指标（UoM）范围为2,402,077 - 2,935,889，相当稳健。CHPO方法在均方根误差（RMSE）为4.75、平均绝对百分比误差（MAPE）为10.12、平均绝对误差（MAE）为2.31时也表现得更好。
