Multilevel Peer-to-Peer Co-optimization for Cyber-physical Intelligent Energy Systems
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摘要: 针对能源电力系统的优化管理与控制问题，提出了一种信息物理融合的智慧能源系统（Intelligent energy systems，IES）多级对等协同优化方法.在信息物理融合能源系统（Cyber-physical energy systems，CPES）的基础上，构建了智慧能源系统的局域和广域两级协同优化架构.综合考虑产消者能源实体对等交互过程中的社会福利、供求平衡和需求意愿等因素，基于Stone-Geary函数和双向拍卖机制构建了智慧能源系统能量优化模型，给出了通过收敛判定域引导的全局随机寻优与区域定向寻优策略，有效地提高了算法的局部搜索能力.此外，通过双向拍卖机制的理性定价以及智能合约的辅助服务，有效地实现了用户友好的对等交易模式.仿真实例表明，在社会福利最大化的前提下可获得产消者电力资源最优分配结果，进一步验证了本文方法的有效性和可行性.Abstract: A multilevel peer-to-peer co-optimization method for cyber-physical intelligent energy systems (IES) is proposed to analyze the optimal control and management problem of energy power systems. On the basis of the cyber-physical energy system (CPES), a co-optimization architecture of local and wide-area levels for intelligent energy system is constructed. With the help of Stone-Geary utility function and double auction mechanism, an energy optimization model for intelligent energy system is constructed in consideration of social welfare, supply-demand balance and demand willingness in the peer-to-peer interaction process of prosumers. At the same time, the local search ability of the intelligent optimization algorithm is further improved by the guidance of convergence judgment domain as well as the combination strategy of global random search and directional search. In addition, the user-friendly peer-to-peer trading mode is effectively realized through rational pricing of double auction mechanism and the auxiliary services of smart contract. Simulation results show that the optimal allocation of power resources can be obtained under the premise of maximizing social welfare, which further illustrates the effectiveness and feasibility of this method.1) 本文责任编委 王占山
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图 1 IES系统多级对等协同优化架构
Fig. 1 The architecture of multilevel peer-to-peer co-optimization in IES
图 6 联盟1产消者3实时电力供求平衡
Fig. 6 Real-time supply and demand balance of 3rd prosumer in the first union
图 7 联盟2产消者10实时电力供求平衡
Fig. 7 Real-time supply and demand balance of 10th prosumer in the second union
图 8 联盟3产消者6实时电力供求平衡
Fig. 8 Real-time supply and demand balance of 6th prosumer in the third union
图 9 联盟4产消者14实时电力供求平衡
Fig. 9 Real-time supply and demand balance of 14th prosumer in the fourth union
表 1 优化模型相关参数
Table 1 The values of related parameters
参数 取值 $\eta$ 0.9 $l_{1}$ 0.01 $l_{2}$ 0.015 $\rho$ 0.8 $e_{1}$ 0.03 $e_{2}$ 0.045 
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表 2 不同控制参数下的迭代次数和计算时间
Table 2 The number of iterations and calculation time with different control parameters
$\varepsilon$ 迭代次数(次) 总计算时间(s) 0.8 20 483.46 0.6 15 369.90 0.4 11 281.34 0.2 8 162.64
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表 3 联盟1产消者3某时段多级对等电力交易结果
Table 3 Multilevel peer-to-peer power trading results of the third prosumer node in the first union at a certain time
时段 偏差电量(kWh) 买方报价(元/kWh) 买方密封交易信息摘要 卖方 购买电量(kWh) 卖方收益(元) 买方支付(元) 3:15 0.457 0.348 eb45cc1d1c684ae290d373e18b260d95 联盟1产消者2 0.097 0.034 0.158 - - - a378420878294a04965be0a999054616 联盟1产消者11 0.082 0.029 - - - - d9f7bf9a2b054722913725c4335a802f 联盟2产消者5 0.144 0.050 - - - - e00a77da2c944828b304543a749562d3 联盟3产消者3 0.130 0.045 - 3:20 0.441 0.327 77298613587a49b5ae3d79a66b20b3f7 联盟1产消者4 0.002 0.001 0.144 - - - 0928c7e54bb04ab9a9405046982b1ece 联盟2产消者8 0.128 0.042 - - - - 836cdb97cb5c4eb5a10cde523126ce51 联盟3产消者13 0.201 0.065 - - - - 1b9ce86e11a0493a928491ae96ff1531 联盟4产消者7 0.110 0.036 - 3:25 0.385 0.296 700d192ebcc94008bf2834f13ebfe180 联盟1产消者6 0.084 0.025 0.114 - - - 1e25a82f6df84e13a0585f717800f703 联盟1产消者15 0.124 0.037 - - - - 5ceb8c3095014a7b90f43b8e977c8fd0 联盟3产消者9 0.092 0.027 - - - - 23d398b02ba14c84a585faf63aa05f39 联盟4产消者1 0.085 0.025 - 3:30 0.426 0.324 8bd98c74da514150914b09951289d1dd 联盟1产消者5 0.039 0.013 0.138 - - - 2c39321d56564099af552d0f605f7ece 联盟2产消者10 0.123 0.040 - - - - 84e0e44dd96e4957ae25c95c1668e7d2 联盟3产消者6 0.046 0.015 - - - - 75d10e745eb44602a352f65b3b5e084a 联盟4产消者6 0.218 0.070 - 3:35 0.377 0.291 e7318fc4dda44955ac1083961c703939 联盟1产消者12 0.090 0.026 0.110 - - - d2a7c521239b4afa9f078a7402c4b246 联盟1产消者7 0.059 0.017 - - - - 2a2cbf7036854a7bafcb34fbd868bea1 联盟1产消者4 0.081 0.024 - - - - b84c13d1b952407a9c1589d35d2d5ee4 联盟4产消者1 0.147 0.043 -
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