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Price-Based Residential Demand Response Management in Smart Grids: A Reinforcement Learning-Based Approach 下载免费PDF全文
Yanni Wan Jiahu Qin Xinghuo Yu Tao Yang Yu Kang 《IEEE/CAA Journal of Automatica Sinica》2022,9(1):123-134
This paper studies price-based residential demand response management(PB-RDRM)in smart grids,in which non-dispatchable and dispatchable loads(including general loads and plug-in electric vehicles(PEVs))are both involved.The PB-RDRM is composed of a bi-level optimization problem,in which the upper-level dynamic retail pricing problem aims to maximize the profit of a utility company(UC)by selecting optimal retail prices(RPs),while the lower-level demand response(DR)problem expects to minimize the comprehensive cost of loads by coordinating their energy consumption behavior.The challenges here are mainly two-fold:1)the uncertainty of energy consumption and RPs;2)the flexible PEVs’temporally coupled constraints,which make it impossible to directly develop a model-based optimization algorithm to solve the PB-RDRM.To address these challenges,we first model the dynamic retail pricing problem as a Markovian decision process(MDP),and then employ a model-free reinforcement learning(RL)algorithm to learn the optimal dynamic RPs of UC according to the loads’responses.Our proposed RL-based DR algorithm is benchmarked against two model-based optimization approaches(i.e.,distributed dual decomposition-based(DDB)method and distributed primal-dual interior(PDI)-based method),which require exact load and electricity price models.The comparison results show that,compared with the benchmark solutions,our proposed algorithm can not only adaptively decide the RPs through on-line learning processes,but also achieve larger social welfare within an unknown electricity market environment. 相似文献
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分布式优化在电力系统中发挥着越来越重要的作用。本文研究一类包含分布式发电机(DGs)和储能设备(ESs)的动态能源资源(DERs)协调问题,其目标是在满足局部耦合物理约束的前提下,使得总成本(包括发电成本, 储能成本和环境成本)最小化。首先,本文将动态DERs协调问题等价转换为更具一般性的分布式复合约束优化模型,并利用拉格朗日对偶理论分析得到原问题的对偶形式。 其次,提出一种新的分布式原对偶优化算法。特别地,所提算法使用局部常数步长,同时采用基于边的通信方式,这本质上区别于基于节点的一致性优化方法。最后,利用基于IEEE 39-bus系统的仿真实验进一步验证了所提算法在求解DERs协调问题上的有效性与可行性。 相似文献
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随着国家“双碳”重大战略的提出, 高比例新能源并网将成为我国电力能源转型的重要态势. 针对火电机组、配电网和需求侧关联的系列运行约束制约了电网对高比例新能源的有效消纳这一问题, 本文提出重大耗能企业这一主要电力负荷参与网需求响应(Demand response, DR)的研究思路, 通过重大耗能企业与电网协调调度促进新能源消纳, 并获得经济补偿以减少运行成本. 研究首先基于混合需求侧响应机制, 提出以重大耗能企业、新能源、火电机组为核心的协调调度方法, 并根据新能源预测值−预测误差的信息依存顺序提出了两步调度策略. 在此基础上, 进行生产过程行为建模以实现重大耗能企业需求侧响应决策描述, 并建立高比例新能源并网的重大耗能企业需求响应与电网协调调度优化模型. 最后, 基于烟台电网实际系统进行算例分析, 验证了重大耗能企业通过需求响应参与电网协调调度以及两步调度策略的有效性. 相似文献
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Hassan Shokouhandeh Mehrdad Ahmadi Kamarposhti William Holderbaum Ilhami Colak Phatiphat Thounthong 《计算机系统科学与工程》2023,47(1):809-822
The widespread penetration of distributed energy sources and the use of load response programs, especially in a microgrid, have caused many power system issues, such as control and operation of these networks, to be affected. The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid. In this paper, the optimum operation of distributed generation resources and heat and power storage in a microgrid, was performed based on real-time pricing through the proposed gray wolf optimization (GWO) algorithm to reduce the energy supply cost with the microgrid. Distributed generation resources such as solar panels, diesel generators with battery storage, and boiler thermal resources with thermal storage were used in the studied microgrid. Also, a combined heat and power (CHP) unit was used to produce thermal and electrical energy simultaneously. In the simulations, in addition to the gray wolf algorithm, some optimization algorithms have also been used. Then the results of 20 runs for each algorithm confirmed the high accuracy of the proposed GWO algorithm. The results of the simulations indicated that the CHP energy resources must be managed to have a minimum cost of energy supply in the microgrid, considering the demand response program. 相似文献
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A fully distributed microgrid system model is presented in this paper. In the user side, two types of load and plug-in electric vehicles are considered to schedule energy for more benefits. The charging and discharging states of the electric vehicles are represented by the zero-one variables with more flexibility. To solve the nonconvex optimization problem of the users, a novel neurodynamic algorithm which combines the neural network algorithm with the differential evolution algorithm is designed and its convergence speed is faster. A distributed algorithm with a new approach to deal with the inequality constraints is used to solve the convex optimization problem of the generators which can protect their privacy. Simulation results and comparative experiments show that the model and algorithms are effective. 相似文献
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随着分布式电源在电网中所占比重的不断提升,针对分布式电源的攻击将给电网带来更严重的安全威胁。攻击者可以通过网络入侵手段协同控制电网中防御较弱的配网侧分布式电源功率输出,最终影响发电侧发电机等关键设备的安全运行。为保障电网安全稳定运行,亟需研究针对分布式电源接入场景下的安全威胁及其防御措施。首先,本文在电力系统动态模型基础之上建立了电网振荡攻击的最小代价攻击模型,通过协同控制多个分布式电源的功率,在牺牲最少被控节点的前提下导致电网发生振荡。其次,针对现有振荡检测算法的不足,本文提出一种启发式的攻击源检测算法,通过分析系统内各节点的势能变化,可有效辅助定位攻击源。算例仿真分析结果验证了通过最小代价攻击影响电网稳定运行的可行性,以及攻击检测方法的有效性。 相似文献
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一种完全分布的网格任务调度算法 总被引:1,自引:1,他引:1
目前国内外网格项目采用集中的网格资源管理和发现机制,在网格中有明确的信息中心,随着网格规模的不断扩大,维护和管理网格信息中心的开销过大,从而影响提高网格性能和成为扩大网格规模的瓶颈。论文提出了一种完全分布的网格资源管理模型,即在网格中没有任何全局的资源信息,同时提出了与此资源模型相适应的基于任务压力的网格任务调度算法。模拟试验表明该资源模型和任务调度算法在不知道整个网格资源处于何种状况的情况下,能够将任务调度到网格的每一个角落,同时具有较好的负载平衡。 相似文献
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一个基于网格服务的分布式关联规则挖掘算法 总被引:4,自引:0,他引:4
分布式关联规则挖掘在知识发现中占着不可忽视的地位,在以往分布式算法的基础上提出了一个加优先权值的PDDM算法,并将修改后的算法与抽样算法、知识网格的思想相结合形成一个GDS算法.GDS算法改善了以往分布式算法中通信量过载,算法难于扩展的问题,而且只扫描一遍数据库,减缓了大数据集挖掘中的I/O问题.理论分析和试验结果表明提出的算法是有效可行的. 相似文献
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选举算法被广泛应用于分布式计算中,而且它已经被证明比合意问题更难.在分析了选举问题和合意问题的关系之后,提出了一种新的容错选举算法.该算法是稳定的、通信有效的,并且该算法可以容忍进程和链路的暂时性错误.所提出的算法不仅解决了选举问题,并且也提供了解决合意问题的一条新的途径. 相似文献
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分布式存储的并行串匹配算法的设计与分析 总被引:7,自引:0,他引:7
并行串匹配算法的研究大都集中在PRAM(parallel random access machine)模型上,其他更为实际的模型上的并行串匹配算法的研究相对要薄弱得多.该文采用将最优串行算法并行化的技术,利用模式串的周期性质,巧妙地将改进的KMP(Knuth-Morris-Pratt)算法并行化,提出了一个简便、高效且具有良好可扩放性的分布式串匹配算法,其计算复杂度为O(n/p+m),通信复杂度为O(ulogp相似文献
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Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson 《IEEE/CAA Journal of Automatica Sinica》2022,9(5):812-833
The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchang... 相似文献
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把周期性广播算法和批处理算法运用到分布式视频点播系统中,推导出实时混合型播放算法,新算法有效地解决了视频点播系统资源瓶颈问题;性能分析结果显示,新算法能够及时响应用户的请求,对客户端无存储要求,并且具有良好的效率、稳定性和扩展性。在当前带宽等资源相对匮乏及客户端无缓存的情况下,该文所述的播放算法是一个很好的选择。 相似文献
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在对两种SVM学习算法(SMO和SVMlight)进行分析的基础上,提出了一种改进的基于集合划分和SMO的算法SDBSMO。该算法根据样本违背最优化条件的厉害程度将训练集划分为多个集合,每次迭代后利用集合信息快速更新工作集和相关参数,从而减少迭代开销,提高训练速度。实验结果表明该算法能很好地提高支持向量机的训练速度。 相似文献
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