为解决配网中分布式光伏渗透率持续升高引起的网损增加、功率倒送、电压越限等问题,在对分布式光伏进行集群划分的基础上,提出了一种综合考虑新能源消纳和网损的分布式光伏集群出力评估方法。首先,以基于电气距离的模块度指标和有功平衡度指标作为综合划分指标,利用遗传算法对配网中的分布式光伏进行集群划分;然后,在集群划分结果的基础上,考虑储能的调节作用及网络安全稳定约束,以包含网损成本和弃光成本的配电系统经济成本最低为优化目标,提出了分布式光伏集群出力评估方法;最后,通过在扬州某地实际41节点系统上进行仿真分析,证明了所提评估方法的可行性和有效性,所提评估方法可以根据调度中心的需求提供分布式光伏集群出力评估数据。

In order to solve the problems of the increasing power loss of network, power reverse transmission, voltage out-of-limit and so on, caused by the continuous increase of distributed photovoltaic penetration in distribution network, according to the cluster division of distributed photovoltaic generation, an output evaluation method of distributed photovoltaic cluster considering renewable energy accommodation and power loss of network is proposed. Firstly, the modular index based on electrical distance and active-power balance index are used as comprehensive division indices, and the distributed photovoltaic generation in distribution network is divided into clusters by using genetic algorithm. Then, on the basis of the cluster division results, considering the regulation effect of energy storage and the constraints of network security and stability, the output evaluation method of distributed photovoltaic cluster is proposed with the lowest economic cost of distribution system including the power-loss cost of network and distributed photovoltaic generation. Finally, the feasibility and effectiveness of the evaluation method proposed in this paper are proved by simulation analysis on an actual 41-node system in Yangzhou. The proposed method can provide output evaluation data of distributed photovoltaic cluster according to the demand of dispatching center.

随着新能源发电技术的高速发展,电网新能源消纳压力日益凸显。与此同时,随着多能转换技术发展,电网与其他类型能源网络的耦合程度不断提高,如何利用不同能源网络灵活性资源消纳受阻新能源,成为当前亟待研究的问题。为此,提出了计及综合需求响应参与消纳受阻新能源的多时间尺度优化调度策略。首先,充分考虑综合能源系统(integrated energy system,IES)特性建立了冷、热、电负荷的多类型需求响应模型。其次,在日前时间尺度,考虑新能源消纳过程中各方利益均衡,建立了基于主从博弈理论的价格型综合需求响应(integrated demand response, IDR)日前优化调度模型;在日内时间尺度,针对新能源日前预测偏差对系统优化影响,建立了考虑激励型IDR日内滚动优化调度模型。最后,通过算例仿真证明了所提策略可深入挖掘多类型负荷需求响应能力,有效提高新能源消纳量。

<p id="p00010">With the rapid development of new energy generation technology, the pressure of new energy consumption in the power grid is increasingly prominent. At the same time, with the development of multi-energy conversion technology, the degree of coupling between power grids and other types of energy networks is increasing. How to use the flexibility resources of different energy networks to dissipate the blocked new energy has become an urgent issue to be studied. This paper proposes a multi-timescale trading strategy that takes into account the multi-energy demand response to participate in the consumption of blocked new energy sources. First, a multi-type demand response model for cold, heat and electric loads is established with full consideration of the characteristics of integrated energy system (IES). Secondly, a price-based integrated demand response (IDR) day-ahead optimal scheduling model based on master-slave game theory is established in the day-ahead time scale, considering the equilibrium of interests of all parties in the process of new energy consumption. At the intra-day time scale, an incentive-based IDR intra-day rolling optimization scheduling model is developed to address the impact of the deviation from the new energy day-ahead forecast on system optimization. </p> <p>Finally, the effectiveness of the strategy proposed in this paper is verified by case simulation. This work is supported by National Key R&#x00026;D Program of China (No. 2018YFE0208400).</p>

针对含风电、光伏、火电和抽蓄联合系统中抽水蓄能电站的容量配置问题,构建了联合系统双层规划模型,并提出了求解流程。上层模型以弃风、弃光电量之和最小为目标,确定抽水蓄能电站的容量配置问题,下层模型旨在最大化联合系统的经济效益、环境价值,同时改善系统运行条件,解决抽水蓄能电站的运行调度问题,上下层目标采用基于Tent映射混沌优化的改进灰狼算法进行求解。通过对某地区冬季和夏季2个典型日场景进行仿真分析,验证了模型与算法的有效性,结果表明,所构建的双层规划模型对科学确定联合系统中抽水蓄能电站的容量是有效的,并在满足运行调度优化的条件下,能够改善系统运行条件,实现经济效益与环境价值最大化的预期目标。

Aiming at the capacity allocation of pumped-storage power stations in the association system of wind power, photovoltaic, thermal power and pumped storage, a bi-level programming of association system model is constructed and a solve loop is proposed. The upper-level model takes the minimum total curtailment of photovoltaic and wind power as the goal to determine the capacity allocation of the pumped-storage power station. The lower-level model aims to maximize the economic and environmental benefits of the association system, while improving the operating conditions of the system and solving the operation scheduling problem of pumped-storage power stations. The targets of the upper and lower-level are solved by the improved grey wolf optimizer (GWO) based on chaos optimization of Tent map. The effectiveness of the model and algorithm is verified by simulation analysis of two typical daily scenes in a certain area in winter and summer. The results show that the constructed bi-level programming model is effective for scientifically determining the capacity of pumped-storage power stations in the association system. And under the condition of satisfying the optimization of operation scheduling, it can improve the operating conditions of the system and realize the expected goal of maximizing economic and environmental benefits.

构建以新能源为主体的新型电力系统是实现碳达峰、碳中和目标的关键驱动力。传统的以可控煤电装机为主导的电源结构,转变为以强不确定性、弱可控的新能源为主体的新型电力系统,将面临着灵活性资源短缺等挑战。以提升新型电力系统灵活性为导向,提出了灵活性资源聚合两阶段调度优化模型。第一阶段模型考虑分时价格型需求响应,以净负荷波动最小为目标平滑负荷曲线;第二阶段模型考虑分段激励型需求响应市场交易机制,融合电化学储能、抽水蓄能、改造火电等灵活性资源,以系统运行成本最小为目标设计最优运行方案。最后,算例结果和场景对比表明,需求响应能够充分挖掘负荷跟随系统调节的互动能力;改造后火电机组能够降低煤耗水平,提高调节能力,加强与系统灵活性需求时空匹配;各类储能积极响应电力系统调峰,促进了新能源消纳。

The construction of the new power system dominated by new energy is a key driver to achieve the goal of carbon peaking and carbon neutrality. The traditional power supply structure dominated by controllable coal-fired power installations is transformed into a new power system dominated by new energy with strong uncertainty and weak controllability, which will face challenges such as shortage of flexibility resources. In order to improve the flexibility of the new power system, a two-stage scheduling optimization model of flexible resource aggregation is proposed in this paper. The first stage model considers time-of-price demand response, and takes the minimum net load fluctuation as the goal to smooth the load curve. The second stage model considers segmented incentive-based demand-response market trading mechanism, integrates flexibility resources such as electrochemical energy storage, pumped storage, and reformed thermal power, and designs the optimal operation scheme with the objective of minimizing system operation cost. Finally, the calculation result and scenario comparison show that demand response can fully exploit the interactive ability of load following system regulation. The reformed thermal power units can reduce coal consumption level, improve regulation ability, and enhance the spatial and temporal matching with system flexibility demand. Various types of energy storage actively respond to the power system peak regulation. Taking pumped storage power station as an example, the reservoir storage capacity presents the shape of "double peaks and double valleys" in the dispatching cycle.

碳达峰、碳中和对可再生能源提出了更迫切的发展要求。为缓解电网调峰压力的同时降低碳排放，提出了一种基于绿证碳交易机制的风火蓄联合调峰控制策略。该策略为分层控制，上层模型为保证抽蓄电站的削峰填谷效果和收益，以净负荷峰谷差最小和抽蓄收益最大为目标；下层模型以系统总运行成本最低为目标，并引入了划分区间的阶梯式碳交易机制和量化罚款幅度的绿色证书交易机制，旨在保证系统经济性的同时满足低碳性。仿真结果表明，所提出的绿证碳交易机制控制策略可减少火电机组出力1.69%，降低系统总运行成本4.09%，验证了策略在低碳经济发展方面的作用。

Peak carbon dioxide emissions and carbon neutrality require urgent renewable energy development. This paper proposes a peak regulation control strategy for wind-thermal-storage combined with the green certificate-carbon trading mechanism to ease peak shaving pressure and reduce carbon emissions. The strategy employs a hierarchical control approach. First， the upper model aims to optimize the peak-valley difference of the net load and maximize the revenue from pumping and storage power stations， ensuring their peak-shaving， valley-filling effect， and revenue. Second， the lower model aims at the lowest total operating cost of the system and incorporates a carbon trading mechanism with segmented boundaries and a green certificate mechanism with quantified fines to ensure the economy of the system while meeting the low carbon requirements. Through simulation analysis， the proposed green certificate-carbon trading mechanism control strategy can reduce the output of thermal power units by 1.69% and the total operating cost of the system by 4.09%， verifying the role of the strategy in developing a low-carbon economy.

农业园区用能需求集中且源荷多元化,当多个农业园区缺少合理运行方法且分布式接入农网,势必会对农业园区效益与农网安全产生不利影响。针对上述问题,提出一种基于中枢解耦与演化博弈的多农业园区综合能源系统(agricultural integrated energy system,AIES)优化运行方法。首先,构建含电-气-热的AIES耦合供能结构和农业园区需求侧响应模型;然后,利用能量中枢解耦方法将农网与园区解耦,建立农网层与多园区层的博弈模型,农网层考虑电压安全和用能成本,园区层考虑经济效益和农作物供能满意度;再次,提出基于多目标粒子群优化的演化博弈算法,解决了多园区、多目标复杂博弈下的强理性、难以达到Nash均衡的问题;最后,通过算例仿真验证了所提方法的可行性和有效性,实现了多农业园区综合能源系统的优化运行。

There are concentrated energy demands and a variety of sources and loads in agricultural parks. When the multiple agricultural parks are dispersedly accessed to rural distribution network and lack of reasonable operation methods, it is bound to have a negative impact on the safety of rural distribution network and the benefit of agricultural parks. In view of the above problems, an optimal operation method based on central decoupling and evolutionary game for multiple agricultural integrated energy system (AIES) is proposed. Firstly, the AIES architecture with electricity-gas-heat and model of the demand response are constructed. Secondly, the rural distribution network is decoupled from the AIES by central decoupling. A two-layer game model including rural network layer and multi-park layer is established. The voltage safety margin and the energy cost are considered in the rural distribution network layer. The satisfaction of crop energy supply and economic benefit are considered in the agricultural park layer. Thirdly, the evolutionary game based on multi-objective particle swarm optimization is proposed. The problem of strong rationality and difficulty in achieving Nash equilibrium in a complex game with multiple parks and goals are solved. Finally, the feasibility and effectiveness of the method are verified by simulation examples. The optimal operation of multiple AIES is achieved.

随着信息技术的发展和工业4.0时代的到来,安全生产逐渐向数字化、智能化转变。本文基于制度性集体行动框架,构建了基于综合监管部门、行业监管部门和生产经营单位的三方主体随机演化博弈模型,研究集体行动因素对主体策略演化的影响。结果表明:随机干扰环境下,博弈主体策略呈现出明显的波动趋势。生产经营单位对成本因素的敏感度高于监管部门。激励性干预举措对于集体行动的一致性动机效果显著。通过增强部门联动机制、积累协同关系资本可以促使集体行动趋于稳定。因此,要完善安全生产领域数字化协同监管跨部门协作机制,增加对安全生产数字化转型的专项扶持力度,捋顺并强化不同主体的监管责任,促进安全生产数字化协同监管集体行动的持续稳定。

In the context of the current superimposed risk society and the digital age, improving emergency early warning and response, handling capabilities through digital and information technology, reducing the adverseimpact of risks, crises and disasters on society, and improving public safety performance have gradually become the direction for development in the field of safety production. The “Industrial Internet+Safety Production” Action Plan (2021—2023) clearly aims to improve the digital, networked, and intelligent level of safety production in industrial enterprises. Through the industrial Internet, the new infrastructure in the digital economy era, a new format and model of safety production will be built.<br/>According to the “14th Five-Year Plan for National Work Safety”, the promotion of digital supervision of safety production relies on the joint efforts of comprehensive supervision departments, industry supervision departments, and production work units, showing the characteristics of collective action of multi-subject collaboration. However, safety production is essentially a public good, with the distinctive features of non-competitiveness and non-exclusivity. Advancing the digital transformation process is influenced by stakeholder factors. In the pursuit of collective action, the regulator and the regulated party are affected by problems such as information asymmetry, responsibility sharing, and lack of coordination, which may lead to free-rider behavior, moral hazard, and other tendencies that undermine collective action, showing a tripartite game relationship in the digital supervision of safety production. Coupled with the contingency and randomness of accidents and disasters, the complexity of risks exacerbates the randomness and uncertainty of the game system. How to find the game stability of the collective action of safety production supervision under the digitalization process among comprehensive supervision departments, industry supervision departments, and production work units, and analyze the evolutionary logic of multi-party achieving collective action is the core proposition of this paper, which can provide a certain theoretical reference for the construction of intelligent emergency development under the background of the digital economy.<br/>Based on the institutional collective action framework, this paper constructs a tripartite random evolutionary game model, discusses the strategic impact and evolution trend of different factors on the digital collaborative supervision of safety production from the perspectives of cooperation benefits and transaction costs, and then analyzes the cooperation mechanism of various parties to achieve collective action. The Gaussian white noise is introduced into the three-party evolutionary game replication dynamic system to reflect that the process of digital collaborative supervision of safety production is disturbed by random factors. Thus, a stochastic evolutionary game model is established, and the model is solved by stochastic process theory. The system dynamics is further used for simulation analysis, and a causal feedback loop among comprehensive supervision departments, industry supervision departments, and production work units is established, parameter assignments are set according to the model solving conditions, and simulation analysis of initial probability and intervention by different factors is carried out respectively.<br/>The study results show that the initial willingness has a certain impact on the implementation of the digital transformation of production work units. However, with the cost input and the action cycle lengthening, the regulatory authorities and production units gradually reduce the collective action willingness in the absence of further incentives. Production work units are the key entities that consider cost factors, and their sensitivity to the impact of relevant transaction costs is much higher than that of the two types of regulatory entities. At the same time, incentive intervention has a more significant effect on the realization of consistent motivation, especially the credibility benefit as a collective benefit has a greater continuous incentive for collective action. Accumulating collaborative relationship capital by strengthening communication and establishing institutional or informal multilateral cooperation, consultation and coordination mechanisms can effectively remove the collaborative barriers to collective action, thereby promoting the game system to a positive and stable state.<br/>According to the conclusions, this paper proposes to rely on the existing safety production deliberation and coordination institutions to establish a cross-departmental cooperation mechanism for safety production digitalization, at the same time increase the government’s special support for the digital transformation of safety production in production work units, and further coordinate the responsibility boundaries of the regulatory authorities and strengthen the main responsibility of the production units.

发展新能源是应对环境污染和能源危机的根本性措施,有助于推动“双碳”目标的实现。可再生能源发电固有的间歇性、波动性给电网规划和运行带来严峻挑战。针对高比例新能源电力系统,分析了以最小功率波动为目标的新能源和储能容量最佳配比。立足风光资源的互补性,构建了最小化系统功率波动的风光最优配比模型,并提出了基于线性规划的求解算法。最后建立了面向平滑新能源出力的储能容量配置参数线性规划模型,得到波动性指标关于储能容量的解析表达式,并根据成本确定了最优储能容量。所提方法为政策制定提供了可视化工具以及比单一最优解更加丰富的信息。

The development of renewable energy is a fundamental measure to resolve environmental pollution and energy crisis, and achieve the carbon peaking and carbon neutrality goals. However, the inherent volatility and fluctuation of renewable energy output bring unprecedented challenges to the planning and operation of the power grid. This paper studies the optimal ratio of renewable energy and energy storage, aiming to minimize power fluctuation. According to the complementary nature of wind and solar resources, the mode of optimal ratio of wind and solar power that leads to minimal power fluctuation is established and is further transformed into linear programming. The optimization problem of energy storage capacity aiming to smooth the renewable energy output is formulated as a multi-parameter linear program, where storage charging power and energy capacities are parameters. The power fluctuation index is expressed as an analytical function in storage parameters, which is convex and piecewise linear. On the basis of the fluctuation index function, the optimal storage capacities can be determined according to the costs. The proposed method provides an illustrative tool and more abundant information for policy and decision-making.

为保障省级区域的可再生能源电量在电力消费中的占比,政府推出了可再生能源消纳责任权重考核制度,受考核方从发电侧转移至用户侧。考核方式的变动,将很大程度影响火电厂商的利益和参与绿色证书(tradable green certificate,TGC)交易的积极性。火电在我国的发电占比较高,火电厂商能否积极响应绿电市场,将极大影响新政策的实施效果。政府需要设置合理的政策参数引导火电厂商的交易策略,以实现理想的博弈均衡结果。以此新变动构建了有限理性下结合绿电厂商、火电厂商、受考核用户三方的演化博弈理论(evolutionary game theory,EGT)模型,模拟了不同参数条件下的火电厂商策略演化和TGC市场的变化趋势。研究结果表明:现有条件下政策参数在±10%波动内所有火电厂商都会达到参与TGC交易的理想演化稳定策略(evolutionary stable strategies,ESS)点。但当政策负担加重时,火电厂商达到ESS点的速率都将大幅减缓。政府应维持或适当降低现阶段政策负担水平,促使火电厂商积极响应TGC交易,以保障新政策高效稳定的推行。

In order to ensure the proportion of renewable energy in power consumption in provincial regions, the government has introduced an assessment system for the responsibility weight of renewable energy consumption, which transfers the assessed party from the generation side to the user side. The change of assessment method will greatly affect the interests of thermal power producers and their enthusiasm to participate in tradeable green certificate (TGC). Thermal power accounts for a relatively high proportion of electricity generation in China. Whether thermal power producers respond positively to the green power market will greatly affect the implementation effect of the new policy. The government needs to set reasonable policy parameters to guide the trading strategies of thermal power producers so as to achieve the ideal equilibrium result of the game. According to the new changes, this paper constructs an evolutionary game theory (EGT) model that combines green power producers, thermal power producers and assessed users under bounded rationality, and simulates the evolution of thermal power producers’ strategies and the changing trend of TGC market under different parameters. The results show that, under the existing conditions, all thermal power producers will reach the ideal evolutionary stable strategies (ESS) point to participate in TGC trading within the policy parameter fluctuation of ±10%. However, when the policy burden increases, the rate of thermal power producers to reach ESS point will slow down significantly. The government should maintain or appropriately reduce the current policy burden level, and encourage thermal power producers to actively respond to TGC transactions, so as to ensure the efficient and stable implementation of the new policy.