目的 在“双碳”战略目标背景下，新能源发电大比例接入电网后电力系统对灵活性调节资源的需求大幅增加，现阶段煤电是具备规模化提升调峰能力的电源侧的主要灵活性资源。自2016年以来，国内主要发电企业已实施一定规模的煤电机组灵活性改造，因此，有必要对灵活性改造后机组实际运行和检修中存在的问题进行总结分析。 方法 对某公司多台煤电机组实施灵活性改造的技术路线、投资费用、实际运行情况等进行统计分析。 结果 现役煤电机组灵活性提升改造后，先进机组最小发电出力可降至18%P_e (P_e为额定负荷)水平；在20%P_e~30%P_e时，变负荷速率可达1.8%P_e/min；平均单位容量投资101元/kW。此外，在灵活运行工况下，改造后的煤电机组发电煤耗大幅升高。 结论 针对煤电机组灵活工况下的运行、检修以及未来进一步工作提出了建议，研究结果为现役煤电机组灵活性提升改造提供参考和借鉴。

Objectives Under the background of the “dual carbon” strategic goal, the demand for flexible regulation resources in the power system has significantly increased after the large-scale integration of new energy generation into the grid. At present, the coal-fired power is the main flexible resource on the power side with the ability to scale up peak shaving. Since 2016, the major domestic power generation companies have implemented a certain scale of flexibility transformation of coal-fired power units. Therefore, it is necessary to summarize and analyze the problems existing in the actual operation and maintenance of the unit after flexibility transformation. Methods The technical route, investment cost and actual operation of several coal-fired power units with flexible transformation in a company were statistically analyzed. Results After the flexibility improvement and transformation of the active coal-fired power generation unit, the minimum power generation output of the advanced unit can be reduced to 18% P_e (P_e is rated load) level, the load change rate with 20% P_e~30% P_e can reach 1.8% P_e/min, and an average unit capacity investment is 101 yuan/kW. In addition, under flexible operating conditions, the coal consumption of coal-fired power units after the transformation has significantly increased. Conclusions Suggestions are put forward for the operation, maintenance and further work of coal-fired power units under flexible operating conditions. The research results provide reference and inspiration for the flexibility improvement and transformation of existing coal-fired power units.

为推动我国高比例清洁能源接入和高比例跨区电力输送的新型互联电力系统建设,降低源荷不确定性对清洁能源跨区消纳和省内-省间电力平衡的影响,提出考虑源荷功率矩不确定性的新型互联电力系统优化调度方法。首先,设计了计划-市场双轨制下新型互联电力系统省内-省间双层优化调度模式。其次,采用矩不确定集合刻画风光发电和负荷功率的不确定性,并提出由此引起的系统弃风弃光分布鲁棒条件风险度量模型。最后,以省间和省内总购电成本最小为目标,建立新型互联电力系统省内-省间分布鲁棒协调优化调度模型,并通过对偶优化理论将该模型转化为易求解的半定规划问题。数值仿真结果表明,所提模型促进了西部地区清洁能源跨省跨区消纳,降低受端系统运行成本的同时,有效提高了系统应对源荷功率不确定性波动的能力。

To promote the construction of a novel interconnected power system in China—one featuring a high proportion of clean energy access and significant trans-regional power transmission proportion—a new optimal dispatching method is proposed that considers the uncertainty of source load power moment. This approach aims to mitigate the impact of source load uncertainty on cross-regional clean energy consumption and intra-provincial power balance. First, a two-level optimal dispatching mode for an innovative interconnected power system between and within provinces was designed under the planning market dual-track system. Second, the uncertainties of wind and solar power generation and load power were characterized by the moment uncertainty set, and the resulting robust conditional risk measurement model of wind and light abandonment distributions was proposed. Finally, to minimize total power purchase cost between and within provinces, a novel distributed robust, coordinated optimal dispatching model for an interconnected power system was established, and the model was transformed into a semi-definite programming problem, more readily solvable by applying the dual optimization theory. Numerical simulation results show that the proposed model promotes the cross-provincial and cross-regional consumption of clean energy in the western region, reduces the operational cost of the receiving-end system, and effectively improves the ability of the system to handle uncertain fluctuations in the source-load power.

高比例可再生能源的大量接入和新型用电设备的增加,使得配电网逐渐向区域化、网格化转型,中低压交互、多台区互联的交直流混合配电网将成为配电网的发展趋势。鉴于此,提出了考虑多台区互联的中低压交直流混合配电网功率双层协同优化调度方法。以综合成本最小为目标建立交直流低压台区功率优化调度模型,得到各个台区内储能充放电策略和电动汽车V2G(vehicle to grid)策略;以系统综合电压偏差最小、综合运行成本最小为目标,建立中压优化模型,得到互联换流器的交换功率。将上下层结果互相传递迭代优化,直至中压配电网和各个低压台区全部收敛。最后,以改进的IEEE 33节点算例系统对所提方法进行了验证,算例结果表明,所提方法能够有效减小系统网络损耗,平抑电压波动。

With high penetration renewable energy and a new type of accessed load, traditional distribution networks have been gradually transformed into multiconnected networks. AC/DC hybrid distribution networks with multi-voltage level interaction have become the development trend of distribution networks. Based on this trend, a two-layer optimization method for an AC/DC distribution network is proposed, considering multi-connected and different voltage level interactions. The objective function of the low-voltage network problem is to minimize the schedule cost and achieve dispatching of energy storage and EV. The objective function of the mid-voltage problem is to minimize the schedule cost and voltage deviation. Next, the exchange power of the voltage-source converter is obtained. Two issues are iterated and optimized until they reach convergence. Finally, a case study was conducted based on the IEEE33 system. The results show that the proposed method can minimize power loss and voltage fluctuation.

可再生能源的大规模渗透给电力系统的稳定运行带来极大挑战。在供需两侧双重不确定性叠加驱动下,基于终端柔性负荷的需求响应资源亟待挖掘。考虑不同类型用户负荷差异化特性,引入基于合作共赢的多类型负荷聚合商,基于异类负荷响应行为互补特点参与电力系统灵活调度;同时,赋予各负荷聚合商碳交易集成商的双重身份进入碳交易市场,采用预测电负荷法为系统无偿分配碳排放配额,构建奖惩阶梯型碳交易模型。以多个负荷聚合商合作联盟运营成本之和最小为目标,构建多聚合商间交互合作的日前优化模型并进行求解;引入合作博弈Shapley值法,根据各参与者对合作联盟运营的贡献度,进行成本分摊。结果表明,合作运营机制下,联盟整体和个体的运营成本及碳排放量均大幅降低。

The large-scale penetration of renewable energy sources poses significant challenges to the stable operation of power systems. Driven by double uncertainties on both the supply and demand sides, demand response resources based on terminal flexible loads need to be explored. Considering the load differentiation characteristics of different types of users, multitype load aggregators based on cooperation and win-win were introduced. Flexible dispatching of the power system was performed based on the complementary characteristics of the heterogeneous load response behaviors. Moreover, each load aggregator was assigned the dual status of a carbon trading integrator to enter the carbon trading market. A carbon trading model based on a reward-punishment ladder was constructed using the electricity load forecasting method to allocate carbon emission quotas for a system free of charge. Based on this, to minimize the sum of the operating costs of a cooperative alliance of multiple load aggregators, a pre-day optimization model of the interaction and cooperation among multiple aggregators was developed and solved. The Shapley value method was introduced for the cooperative game, and the cost was shared according to the contribution of each participant to the operation of the cooperative alliance. The results show that the overall and individual operational costs and the carbon emissions of the alliance are significantly reduced under the cooperative operation mechanism.

Objectives With the continuous advancement of the national “dual carbon” strategy, integrated energy services, as a new model and new form of the energy industry, are gradually becoming an important means for China to build a new energy system and create new quality productive forces in the energy field. In order to facilitate the high-quality development of China’s integrated energy service industry, the development trends and strategies of integrated energy services are studied. Methods Through in-depth analysis of the development status of integrated energy services at home and abroad, the structure-conduct-performance (SCP) analysis model is used to analyze the development and trend of the integrated energy service industry under the new situation. Conclusions From the national level, the countermeasures and suggestions of “three synergies” for the high-quality development of the integrated energy service industry are put forward, focusing on “policy-reform-planning”. From the enterprise level, the implementation path of “four advantages” for high-quality development is put forward, focusing on “layout-model-science and innovation-brand”. These strategies aim to support the healthy and sustainable development of the integrated energy service industry, providing innovative demonstrations and value contributions to the construction of China’s new power system and the implementation of the “dual carbon” strategy.

随着可再生能源渗透率的提高,分布式可再生能源带来的波动性、间歇性会传递至主网中,对系统安全运行造成影响,研究不确定性优化方法对系统实际运行具有一定的指导作用。传统的随机优化以及鲁棒优化方法不满足系统实际运行的非预期性要求。文章以日运行期望成本最小为目标,考虑分布式可再生能源发电不确定性,建立多阶段随机规划模型,可以根据之前不确定信息的实现在每个阶段确定预调度决策,不会受到未来不确定信息的影响,符合系统实际运行规律,满足非预期性。为了避免多阶段随机规划问题求解的维数灾难,采用随机对偶动态规划(stochastic dual dynamic programming, SDDP)算法进行求解。仿真结果表明,相比于传统的确定性模型,多阶段随机优化得到的最优调度决策树较之确定性优化得到的单一决策方案具有更广泛的决策空间,可以基于上一阶段不确定信息的实现和决策来更新调度决策,降低系统的运行成本。

With the increase of renewable energy penetration, the volatility and intermittence brought by distributed renewable energy will be transferred to the main network, which will affect the safe operation of the system. The study of uncertainty optimization method plays a certain guiding role in the actual operation of the system. However, the traditional stochastic optimization and robust optimization methods do not meet the unpredictable requirements of the actual operation of the system. In this paper, a multi-stage stochastic programming model considering the uncertainty of distributed renewable power generation is established with the goal of minimizing the expected cost of daily operation. The pre-scheduling decision can be made at each stage according to the realization of the previous uncertain information, which will not be affected by the future uncertain information, and is in line with the actual operation law of the system, and meets the unexpected requirements. In order to avoid the disaster of dimensionality in solving multi-stage stochastic programming problems, the stochastic dual dynamic programming algorithm is used to solve the problem. The simulation results show that, compared with the traditional deterministic model, the optimal scheduling decision tree obtained by multi-stage stochastic optimization has wider decision space than the single decision scheme obtained by deterministic optimization. The scheduling decision can be updated according to the implementation and decision of the uncertain information in the previous stage, and the operating cost of the system can be reduced.

Modern electricity markets with large penetration of renewable energy resources require fair and accurate pricing methods to elicit generation flexibility and foster competition in electricity markets. This paper proposes the fundamental theory and closed-form formulas for continuous-time locational marginal price (LMP) of electricity, which more accurately integrates the spatio-temporal variations of load and operational constraints of power systems in the electricity price calculation. This paper first formulates the network-constrained generation scheduling and pricing problems as continuous-time optimal control problems using two methods for modeling transmission network, i.e., Theta and generation shift factor (GSF) methods. The continuous-time network-constrained scheduling and pricing problems minimize in their objective functional the total operation cost of power systems over the scheduling horizon subject to generation and transmission constraints. The closed-form continuous-time LMP formulas are derived for each transmission network model, which explicitly include terms that reflect the simultaneous spatio-temporal impacts of transmission flow limits and intertemporal generation ramping constraints in LMP formation. A scalable and computationally efficient function space solution method is proposed that converts the continuous-time problems into mixed integer linear programming problems with finite-dimensional decision space. The proposed solution method enables high-fidelity solution of transmission-constrained scheduling and pricing problems in higher dimensional spaces, while including as a special case the current discrete-time solutions. The proposed models are implemented on a three-bus system and the IEEE reliability test system, where the proposed models showcase more accuracy in reflecting the impacts of fast net-load variations over discrete-time counterparts.