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PDF(3597 KB)
考虑电能-备用-碳多元资源交易的配-微电网协同调度
Coordinated Scheduling of Distribution and Microgrids Considering Energy-Reserve-Carbon Multi-Resource Trading
【目的】针对现有配电网与多微网协同灵活性挖潜不足导致两者运行成本高昂的问题，提出一种考虑电能-备用-碳排放多元资源交易的配-微电网协同优化调度策略。【方法】首先，充分计及微网个体入市资格差异，构建一种兼容差异化主体参与现货和备用市场竞价的新型非对称微网联盟（asymmetric microgrid alliance，AMGA）框架。在此基础上，设计计及多级市场出清机制的配网运营商（distribution network operator，DNO）与AMGA主从博弈策略，其中上层DNO充分考虑配网潮流约束，针对不同市场主体实施电能量、备用及碳动态定价，下层AMGA挖掘电动汽车（electric vehicle，EV）能量转供潜力，进行多微网协同调度。最后，采用融合二分法的优化算法迭代求解调度模型。【结果】所提策略能够降低配微网运行成本，系统经济性提高12.83%，保障电网高效运行。【结论】该方法在兼顾经济性与环保性的基础上，实现了多主体间的协同优化与公平收益分配。
[Objective] To address the issue of high operational costs in existing distribution networks and multi-microgrids caused by insufficient exploitation of synergistic flexibility， this paper proposes a coordinated optimal scheduling strategy for distribution-microgrids considering multi-resource trading of energy， reserve， and carbon emissions.[Methods] First， by fully considering the heterogeneity in market access qualifications among individual microgrids， a novel asymmetric microgrid alliance （AMGA） framework is established to enable differentiated entities participating in spot and reserve market bidding. On this basis， a Stackelberg game strategy between the distribution network operator （DNO） and AMGA is designed， incorporating a multi-level market clearing mechanism. In the upper-level， the DNO fully accounts for the power flow constraints of the distribution network and implements dynamic pricing of energy， reserve， and carbon targeting different market entities. In the lower-level， AMGA explores the energy transfer potential of Electric Vehicles （EV） to achieve coordinated scheduling of multi-microgrids. Subsequently， an optimization algorithm integrating a bisection method is employed to iteratively solve the scheduling model.[Results] The proposed strategy effectively reduces the operational costs of distribution- microgrid system， improves system economic performance by 12.83%， and ensures efficient grid operation.[Conclusions] This method achieves collaborative optimization and fair benefit distribution among multiple entities while balancing economic efficiency and environmental sustainability.
配电网 / 微网联盟 / 主从博弈 / 市场出清机制 / 二分法
distribution network / microgrid alliance / Stackelberg game / market clearing mechanism / bisection method
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园区综合能源系统(park-integrated energy system, PIES)是能源系统优化升级、电力行业减碳的重点，园区如何通过制定交易策略参与电碳绿证市场，提高整体效益并降低系统碳排放，是未来开放市场环境下园区快速发展的关键。基于园区三方主体非合作博弈模式，构建绿电日前市场、常规能源日前市场、实时市场的电力市场运行框架，并引入绿证-碳排等价抵消机制以实现绿证交易和碳交易的衔接，提出一种考虑电碳绿证市场耦合的园区综合能源系统日前优化调度模型。最后，采用改进粒子群算法和交替方向乘子法对非线性模型进行求解，并在上海市某典型园区进行验证。结果表明，所提方法可以有效减少园区碳排放量，园区绿电在电力消费总量占比提高6.4%。
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现代化农业园区温室环境系统与光伏发电系统易出现“源荷错峰”运行问题。为此，提出一种考虑农作物生长需求的农业园区微能源网(agricultural park microgrid，APMG)参与配电市场出清的能量管理双层优化模型，以实现农作物快速生长与多类型能源高效利用。双层模型中，上层模型以APMG运营成本最小为优化目标，在考虑配电市场电价、光伏发电等因素的基础上，计算农业园区温室环境系统的最佳能量管理策略模型；下层模型为配电市场出清模型，其目标为实现配电网最佳电能配置，并得到出清价格。进一步，利用自适应交替方向乘子法求解双层模型。最后，以IEEE-12节点配电系统和66节点内蒙古某县农村配电系统为例，验证所提模型及方法的有效性。算例结果表明，该模型可有效降低农业园区23.2%的用能成本，同时还能降低配电网用户6.2%购电费用。
Greenhouse environmental systems and photovoltaic power plants in modernized agricultural parks are prone to “source-load peaking” operation problems. To address this issue, this study proposes a two-layer optimization model for energy management of the agricultural park micro energy network (APMEN) participating in distribution market clearing, considering the crop growth characteristics to achieve rapid growth of crops and efficient use of multiple types of energy. The upper-layer model calculates the optimal energy management strategy for the greenhouse environmental system of the agricultural park, with the objective function of minimizing the operating cost of the APMEN, considering the accessory market tariff and photovoltaic power generation. The lower-layer model corresponds to the distribution market-clearing model, which aims to achieve optimal power allocation in the distribution network. Furthermore, the two-layer model is solved using the adaptive alternating direction multiplier method. Finally, the IEEE 12-node distribution system and 66-node Inner Mongolia Autonomous County rural distribution system were used as examples to verify the effectiveness of the proposed model and method. The results show that the model can effectively reduce the energy cost of agricultural parks by 23.2% and the power purchase cost of distribution network users by 6.2%.
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利益冲突声明（Conflict of Interests）： 所有作者声明不存在利益冲突。
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