随着高渗透率分布式新能源接入电网，其出力的随机性与波动性对配电网的灵活性需求提出了更高的要求。为此提出一种计及智能软开关(soft open point, SOP)与智能负载(smart load, SL)互补特性的配电网灵活性提升方法。首先，对SOP、SL与可控分布式电源（distributed generation, DG）的灵活性特性与数学模型进行分析，从节点灵活性适应度与含SOP线路的负载裕度两个方面建立灵活性评估指标。其次，构建考虑运行成本、电压质量与灵活性指标的目标函数，力求在最小化灵活性缺额与电压越限的情况下实现经济性最优。同时提出了改进鲸鱼优化算法(reconstruction whale optimization algorithm, Re-WOA)对优化模型求解；在该算法中引入了两种改进的搜索捕食策略，并以SL容量裕度指标平衡搜索阶段的SL负载均衡度。最后，通过改进的IEEE 33节点系统验证了该模型对配电网的优化作用与所提Re-WOA算法的有效性。

The integration of new high-permeability distributed energy into the power grid has increased the demand for flexibility in the distribution network owing to the randomness and volatility of its output. A method for improving the flexibility of distribution networks that considers the complementary characteristics of soft open point (SOP) and smart load (SL) is proposed. First, the flexibility characteristics and mathematical models of the SOP, SL, controllable DG, and flexibility evaluation indicators were established from two aspects: node flexibility adaptability and the load margin of lines containing the SOP. Second, we constructed an objective function that considers the operating costs, voltage quality, and flexibility indicators, striving to achieve optimal economic performance while minimizing flexibility gaps and voltages exceeding the limits. Simultaneously, a reconstruction whale optimization algorithm (Re-WOA) was proposed to solve the optimization model, and two improved search predator strategies were introduced in the algorithm. The SL load balancing degree during the search phase was balanced using the SL capacity margin index. Finally, the optimization effect of the model on the distribution network and the effectiveness of the proposed Re-WOA were verified using an improved IEEE33 node system.

随着新能源在电力系统中的占比不断提高,新型电力系统的安全稳定运行受到极大的挑战,亟待进行新型灵活性资源容量配置。为此,计及新能源出力不确定性,构建一种考虑灵活性需求约束的两阶段鲁棒容量优化配置模型。首先,针对风光等新能源的不确定性特征,对电力系统的灵活性需求进行刻画,分析灵活性资源调节特性,对新型灵活性资源的调节能力进行建模。然后,引入不确定性参数,建立一种考虑灵活性供需平衡的两阶段鲁棒容量优化配置模型,基于列与约束生成(column-and-constraint generation,C&CG)算法与KKT定理,求解系统对应的最优规划结果。最后,选取我国某地电力系统为仿真对象进行实证分析,验证所构建模型的有效性。算例结果表明,所构建的两阶段鲁棒配置优化模型可以应对电力系统的不确定情况与新能源带来的灵活性需求,规划结果能够在新型电力系统的安全性与经济性上达成平衡。

The safe and stable operation of new power systems has become challenging, with the increasing proportion of new energy sources in power systems. Configuring new, flexible-resource capacities has become urgent. This study considers the uncertainty in the new energy output and constructs an optimal, two-stage, robust, configuration model that considers flexibility-demand constraints. The flexibility demand of the power system is modelled with respect to the uncertainty characteristics of new energy sources, such as wind power and photovoltaic (PV) power; the regulation characteristics of new flexibility resources are analyzed to model their regulation capacity; uncertainty parameters were introduced to establish a two-stage, robust, capacity optimization model considering the balance of flexible supply and demand, and the corresponding optimal planning results of the system were solved based on the CCG algorithm and the KKT theorem. The power system of a certain location in China was selected as the simulation object for empirical analysis to verify the validity of the constructed model. The results show that the optimal, two-stage, robust, configuration model constructed in this study can effectively cope both with the uncertainty of the power system and the flexibility demand brought about by new energy sources. A balance between the security and economy of the new power system can be planned.

针对含微电网的配电网,提出了一种考虑微电网灵活性资源属性的配电网规划方法,该方法从变电站规划和网架规划两阶段考虑了微电网的灵活性资源属性。首先,建立了微电网内各灵活性资源的数学模型,进而组成微网的对外等效模型;然后,通过更新定容公式以及在网架规划中添加约束条件来考虑灵活性资源;最后,建立以配电网投资和运行成本最小为目标函数的规划模型,并基于改进的遗传算法进行求解。通过含3个微电网的待规划区域进行算例设计和仿真,结果表明文章提出的规划方法可以在成本少量增加的情况下提升系统传输灵活性,使得未来配电网运行过程中出现分布式电源波动或负荷预测不准确时,线路留有足够的灵活性供主网或微电网进行功率传输,证明了所提出模型的合理性和有效性。

Aiming at the distribution network with microgrid, a distribution network planning method considering the flexibility resource attribute of microgrids is proposed. The flexibility resource attribute of microgrids is considered from substation planning and grid planning. Firstly, the mathematical models of flexible resources in microgrids are established and then the external equivalent model of microgrids is formed. Then, the flexibility resources are considered by updating the constant volume formula and adding constraints in network planning. Finally, a distribution network programming model with minimum investment and operating cost as the objective function is established and it is solved by improved genetic algorithm. Case study is designed according to the area to be planned with three microgrids. The results show that the planning method proposed in the paper can improve the system transmission flexibility with a small increase in cost, so when the distributed power supply fluctuates or the load forecast is inaccurate during the operation of the distribution network in the future, the line will have enough flexibility for the main network or the microgrid to transmit power, which proves the rationality and effectiveness of the proposed model.

对于燃煤机组占比较高的国家而言,实施灵活性改造是增强电力系统灵活性的关键手段之一。然而,机组改造后系统角色及运行方式均发生了转变,原有的建模方法及调度策略已不适用。基于此,文章提出了一种考虑火电差异化灵活性改造的电-热集成系统优化调度方法。首先,对比分析了2种类型火电机组灵活性改造的相关技术及特点,采用顶点凸组合法对纯凝机组多阶段调峰、热电联产机组多模式运行过程进行统一建模。其次,以系统总运行成本最小为目标函数,以电热平衡、机组运行模式、机组爬坡和启停为约束,建立了电热集成系统优化调度混合整数规划模型。最后,通过算例对模型的有效性和适用性进行了验证。结果表明所提模型可大幅提升系统风电消纳能力,降低系统运行成本,可有效缓解“三北”地区电网调峰压力。

For countries with a relatively high proportion of coal-fired power units, the implementation of flexibility transformation is one of the key means to enhance the flexibility of the power system. However, the role and operation mode of the system have changed after the unit transformation, and the original modeling method and scheduling strategy are no longer applicable. This paper proposes an optimized dispatching method for the electro-thermal energy integrated system considering the flexibility and transformation of thermal power differentiation. Firstly, the related technologies and characteristics of the flexible transformation of the two types of thermal power units are compared and analyzed. The apex-convex combination method is used to uniformly model the multi-stage peak shaving of the pure condensing unit and the multi-mode operation process of the cogeneration unit. Secondly, with the minimum total operating cost of the system as the objective function, and the electricity and heat balance, unit operation mode, unit climbing and start-up and stop as constraints, a mixed integer programming model for optimal dispatching of electro-thermal energy integrated systems is established. Finally, an example is used to verify the validity and applicability of the model. The results show that the model proposed in this paper can greatly improve the wind power accommodation capacity of the system, reduce the operating cost of the system, and can effectively reduce the peak load of the power grid in the "Three North" area.

分布式能源的渗透率不断提高给配电网带来更加复杂的电压质量及安全稳定问题,单一的无功或储能优化配置难以满足现代化电网日渐多元化的需求。提出一种储能与无功相结合的配置策略,用以满足新能源配电网在有功调节与无功补偿两方面的需求,实现灵活性、电压质量、经济性三方面的权衡优化,适应不同渗透率新能源的影响。首先,以灵活性需求、无功需求两方面为目标建立配电网安全稳定评价体系;其次,考虑规划层与运行层的耦合性,建立配电网储能-无功优化配置双层模型;之后,使用小概率随机突变法改进标准粒子群算法,减小计算过程中陷入局部最优的可能。最后,使用改进的IEEE 33节点配电系统进行仿真测试,验证所提方案的合理性、有效性。仿真结果表明,所提方案能够有效改善配电网的经济性与安全稳定,且在不同的新能源渗透率下均能得到多目标兼顾的最优配置方案。

Increasing the permeability of distributed energy results in a greater number of complex problems related to voltage quality, safety, and stability in distribution networks. Achieving a single optimal configuration of reactive power or energy storage to satisfy the increasingly diverse requirements of modern power grids is difficult. In this study, a configuration strategy that combines energy storage and reactive power is proposed to meet the requirements of new energy distribution networks in both active-power regulation and reactive-power compensation. The strategy also realizes a balanced optimization of flexibility, voltage quality, and economy, and adapts to the influence of new energy under different permeabilities. First, a safety and stability evaluation system of the distribution network is established based on flexibility and reactive-power demands. Second, based on the coupling between the planning and operating layers, a two-layer model of optimal energy-reactive power allocation in the distribution network is established. A small-probability random mutation method is then used to improve the standard particle swarm optimization algorithm to reduce the possibility of falling into local optima. Finally, an improved IEEE-33 node distribution system is used in a simulation test to verify the rationality and effectiveness of the scheme. Simulation results show that the proposed scheme can effectively improve the economy, security, and stability of the distribution network, and a multi-objective optimal configuration scheme can be obtained under new energy permeabilities.

随着分布式电源渗透率不断提高,配电网运行面临着源荷不确定性带来的灵活性不足问题。合理配置储能(energy storage system, ESS)和智能软开关(soft open point, SOP)等灵活性资源是解决该问题的关键。为此,从灵活性供需匹配度和传输能力2个方面提出了考虑配电网灵活性提升的ESS和SOP三层协同规划模型。其中,上层以ESS投资成本最小为目标对蓄电池和超级电容器等多时间尺度储能进行规划,中层以配电网年综合成本最小为目标对SOP进行规划,下层以各场景下的网络灵活性最优为目标进行优化,并采用自适应粒子群算法和二阶锥规划算法对模型进行求解。最后,在IEEE 33节点系统上验证了所提方法的有效性。结果表明,相比仅考虑单一时间尺度的规划方法,所提的ESS和SOP协同规划方法的配电网年综合成本降低了4.59%,实现了配电网经济灵活运行。

With the increasing penetration rates of distributed generators, the operation of distribution networks faces the challenge of insufficient flexibility owing to uncertainties in supply and demand. The key to addressing this issue lies in properly allocating flexible resources, such as energy storage systems (ESS) and soft open points (SOP). To this end, a three-level coordinated planning model for ESS and SOP that considers the flexibility of the distribution network is proposed in terms of flexibility, supply-demand matching, and transmission capacity. Within this model, the upper-level plans for multi-timescale energy storage, such as storage batteries and supercapacitors, aim to minimize the ESS investment costs. The middle-level plans for the SOP are intended to minimize the annual comprehensive operation cost of the distribution network. The lower-level plans optimize the objective of network flexibility in each scenario and solve the model using an adaptive particle swarm algorithm and a second-order cone planning algorithm. Finally, the effectiveness of the method is verified using an IEEE 33-bus system. The results show that, compared with the planning method that only considers a single time scale, the coordinated planning approach of the ESS and SOP proposed in this study reduces the annual comprehensive cost of the distribution network by 4.59%, thereby achieving the economic and flexible operation of the distribution network.

高比例新能源接入配电网络和传统可控发电机组占比下降导致电力系统调节能力严重不足,需求侧灵活性资源可以通过一定的控制手段,在多尺度下为电力系统提供调节能力。基于此,文章介绍了需求侧灵活性资源的基本概念、特征及类型,归纳了新型电力系统需求侧灵活性资源时空协同优化与动态均衡机制的研究热点与进展,并总结需求侧灵活性资源时空协同优化与动态均衡机制在形态结构解耦分析、供需平衡协调配置、聚合调度与协同优化及集群效益动态均衡分配方面的关键技术和实现算法的优劣势。最后,对需求侧灵活性资源时空协同优化与动态均衡机制研究的关键技术进行展望,旨在对实现需求侧灵活性资源在新型电力系统中的应用提出一定的建设性思路。

The high proportion of new energy access to the distribution network and the decline in the proportion of traditional controllable generating units have led to a significant shortage of power system regulation capacity. Demand-side flexibility resources can provide regulation capacity for power systems at multiple scales through certain control means. In this context, this paper first introduces the basic concept, characteristics, and types of demand-side flexibility resources. Then, it summarizes the research hotspots and progress of the spatio-temporal co-optimization and dynamic equilibrium mechanism of new power-system demand-side flexibility resources. It also summarizes the key technologies and achievements of the spatio-temporal co-optimization and dynamic equilibrium mechanism in the areas of morphology and structure decoupling analysis, coordinated allocation of supply-demand equilibrium, aggregated dispatch, and co-optimization and dynamic and equilibrium allocation of cluster benefits. Finally, this paper summarizes the advantages and disadvantages of key technologies and implementation algorithms of demand-side flexibility resource spatio-temporal cooperative optimization and dynamic balancing mechanism in terms of morphological structure decoupling analysis, supply-demand balance coordination allocation, aggregation scheduling and cooperative optimization, and cluster benefit dynamic balancing allocation.