With the continuous adjustment of the energy structure and the reform of the power market, the power system is confronted with numerous uncertain factors, such as the intermittency and volatility of renewable energy generation, errors in load forecasting, and the uncertainties in power market transactions. These uncertainties pose significant challenges to power and energy balance analysis and dispatch operations. In this context, the construction of a power balance analysis and intelligent dispatch system under uncertain scenarios is of great importance for ensuring the safe, reliable, and economical operation of the power system. This paper proposes a functional architecture for Power Balance Assessment and Smart Grid Dispatch Systems that supports diverse operational scenarios across multiple temporal scales. The framework integrates advanced data analytics, system modeling, and optimization algorithms to address dynamic grid challenges. The deployed system has been implemented in provincial power grids, demonstrating its capability to ensure secure and cost-effective grid operations under stochastic fluctuations on both generation and load sides.

Security-constrained unit commitment (SCUC) is a fundamental problem in power systems and electricity markets. However, SCUC could be hard to solve due to the highly complicated security constraints which often result in numerical difficulties. In this paper, we develop an efficient method to identify the redundant security constraints as a preprocessing procedure. Different from the conventional redundancy detection methods which treat problem parameters as fixed, our proposed method considers the uncertainty of the GSDF parameters leveraging the theory of robust optimization. In principle, our detection procedure aims to locate the security constraints which remain redundant even if the parameters might be inaccurate and thus reinforces the robustness compared to the conventional methods. To enhance efficiency, we further show that under mild conditions a simple greedy method is sufficient to identify redundancy even in the presence of uncertainty. Numerical results on the IEEE 118-node test system verify the validity and robustness of our method.

As the penetration rate of renewable energy continues to increase, the uncertainty problem brought by it is becoming more and more serious. Robust optimization is widely used in the process of unit combination as a method of dealing with uncertainty. However, traditional uncertainty coping method, two-stage robust optimization unit commitment, has problems of nonanticipativity and all-scenario feasibility. For this reason, this paper improves the traditional two-stage robust optimization model. The extreme scenarios are first generated from the vertex scenarios of the polyhedron uncertainty set. According to the generated extreme scenarios set, the two-stage robust optimization is transformed into a stochastic programming simultaneously. Finally, this paper incorporates all-scenario-feasibility and nonanticipativity constraints into the model and an example is designed to verify the validity of the model. The results show that the designed model can meet the requirements of all-scenario-feasibility and nonanticipativity. (c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Large scale bilateral transactions may lead to extreme power grid operation mode. The trading results adjustion by post security check may affect the generation plans and increase the production and operation risks of market members. It is of great significance for the orderly development of power market in the medium and long-term to provide the security analysis service before the transaction process and guide the market members to revise the medium and long-term physical transactions. A new mode of medium and long-term electricity security analysis based on market members' transaction willingness is proposed. In the mode, a two-step security check process including centralized electricity security analysis and electric energy limitation calculation is established, and an optimization analysis model based on security-constrained unit commitment (SCUC) is developed. Through coordinating the multi-period optimal dispatching of power balance and power grid security, it is available to acquire the executable conclusion of electricity contract as well as the subsequent power tradable space. The case analysis based on actual data of provincial power grid shows the effectiveness of the mechanism.

Security-constrained unit commitment (SCUC) is the foundation to ensure the safe and economic operation of power systems. A large number of integer variables and complex network security constraints are the main barriers that limit the computation efficiency of the SCUC problem. In this paper, the congestion information is used to identify the units that play a key role in alleviating transmission congestion, in the process of iterative solving of the SCUC. Then the commitment statuses of non-critical units are fixed, and the number of integer variables is reduced. Additionally, a neighborhood search cutting plane is designed and added to the model so as to reduce the branch-and-bound search space of the mixed integer programming problem. The simulation results of the 3375-bus case demonstrate that the proposed method can significantly improve the solving efficiency compared with the traditional method.

This paper proposes a novel synergistic balancing control scheme for low-inertia power systems with high photovoltaic (PV) penetration in Tibet power grid (TPG). The mechanism and dispatching principle of choosing the suitable area control error (ACE) control mode for TPG are analyzed., An adaptive control mode switching method is proposed to meet the different control demands for the dynamically changing topologies. Then, we propose a new coordinated control scheme to dispatch hydropower generators and PV power stations. A set of optimum control objectives considering balancing control performance, regulation mileage of conventional generators, and power curtailment of PV are first presented. The control objectives are decomposed and simplified by step-by-step approximation and linearization, which are easily extended to be applied to real-world automatic generation control (AGC) systems. The simulation results show the effectiveness of the proposed solutions for synergistic balancing control by using the equivalent TPG test system. The equivalent system includes 63 generators with total power equal to 1618.5 MW and 51 PV power stations over 1100 MW. In addition, the actual operation cases present that the coordinated control between conventional and renewable generation dispatched by AGC has the basic conditions in the actual operation of the power grids, which will play a more significant role with the rapid increase of renewable generation sources in the future.

Electricity price prediction is the basis of power market decision-making. In recent years, it brings challenges to the accuracy of electricity price prediction because of the continuous increase of wind power installed capacity. In this paper, with the help of the wind-load ratio construction method, a new characteristic variable is introduced. Pearson correlation coefficient is used to analyze the correlation between this variable and electricity price. Based on DK1 power market data in the Nord Pool, the LSTM-Attention model is constructed to verify the validity of the variable. The experimental results show that the introduction of this variable can effectively improve the predictive accuracy compared with the wind-load ratio.

With the steady advancement of power marketization on the distribution side, power customers (PC) participation in the power demand-side response has become an important part of the construction of the power market. Due to the randomness and profitability of PC, compared with the lack of effective control methods on the power generation side, it is difficult to show the effectiveness of flexible load resources on the demand side. Therefore, this paper proposes a collaborative modeling and analysis method based on the chameleon effect (CE) of customer’ power demand response. First, the social attribute factors of the CE are analyzed, and the chameleon mirror effect (CME) of PC is proposed and modeled. Then, CME and the evaluation benefit are modeled separately for the PC set of the distribution network system. Finally, quantitatively verify the model and evaluate the benefits of the system. The analysis of calculation examples shows that the establishment of the CME of PC in this paper conforms to the laws of the market. PC who follow CME can obtain more favorable power consumption benefits, which can stimulate PC to follow CME in reverse.

The frequency regulation potential of temperature-controlled load aggregators means that, the total load reduction that all the aggregated temperature-controlled load users can participate in the frequency regulation. User demand response willingness refers to the willingness of users to adjust electricity consumption according to the price of electricity sales to provide demand response based on their own demand response elasticity. This paper establishes a user demand response willingness model including two parts of electricity cost change and temperature change, which is used to characterize the relationship between user frequency regulation potential and electricity price; then proposes a time series chained two-dimensional cloud generator algorithm for the willingness model to predict the temperature-controlled load operating state in the temperature-controlled load, and finally establish a two-layer model to optimize the frequency regulation potential of the temperature-controlled load aggregator, with the frequency regulation potential as the solution variable. The effectiveness of the algorithm and the model are verified through calculation examples, and sensitivity analysis is carried out.

在深化电力市场改革以及促进需求侧消纳清洁能源的背景下,售电商需综合考虑火电年度合同电量以及清洁能源消纳年度合同电量,在合理安排年度合同电量分解的基础上,根据月度用电量预测偏差优化月度市场交易策略,构建了售电商月度购电滚动修正优化策略框架.基于月度市场电价波动风险分析,提出了年度合同电量分解到月度合同电量的进度系数.考虑了清洁能源出力波动的季节性修正因子,从而建立了满足偏差考核的售电商月度最优购电策略模型.算例分析了电价波动以及清洁能源消纳年度合同电量对售电商月度市场竞价策略的影响,对售电商承担新能源消纳权责、降低竞价风险、满足偏差考核具有现实意义.

With the formal proposal of the double carbon goals, the proportion of renewable energy accessing in the system will further increase, and the traditional partitioning strategy is no longer applicable. This paper proposes a power market partition strategy, considering the system network topology and the locational marginal price in different renewable energy output scenarios, and uses a spectral clustering algorithm to partition the nodes. Numerical cases based on IEEE-39 system and provincial power grid of 244 nodes are carried out to demonstrate the effectiveness of the proposed approach, the results of the partition can correctly reflect the electricity market price.

伴随国家电网公司对富余可再生能源跨省区消纳的大力推进,受端电网接纳能力的精细化评估分析成为跨省区新能源消纳的核心问题,对此,基于三公调度模式下的安全约束经济调度优化技术,提出了采用多级协同方案的受端电网接纳能力评估分析方法.该方法构建了省级电网接纳能力评估分析、分中心接纳能力安全校核与校正和多回直流通道接纳能力评估分析模型.首先执行省级电网接纳能力评估分析,为分中心接纳能力评估分析提供边界条件.然后对分中心全网、单回直流通道或多回直流通道进行接纳能力有效性评估和安全校正,为国调中心跨省区现货交易出清提供可靠的边界条件.经过多场景算例和实用化运行的分析与验证,结果表明该方法可准确分析分中心全网、单回直流通道或多回直流通道等不同维度的新能源消纳能力,为跨省区现货交易的顺利进行提供了技术保障,实现了富余可再生能源跨省区最大消纳.

At present, China is carrying out the construction of electric power spot market, and the evaluation index of power spot market operation is an important basis for market operation agencies and market regulators to carry out spot market supervision monitoring and evaluation analysis. Based on the study of foreign power market index system, this paper puts forward the design principle, overall framework and evaluation index design of power spot market operation in pilot areas of China. The index system includes market supply and demand, market quotation, market concentration, market trading results and market behavior, There are 5 first-class indicators, 11 second-class indicators and 70 third-class indicators. Finally, the application scenarios of the index system are introduced.

文中分析了中国在市场出清和节点边际电价计算时,存在发用电负荷偏差和系统网损难以精确计算的问题.首先,提出2种节点边际电价计算模型,利用网损分布因子分摊系统网损与负荷偏差分配因子分配负荷偏差相结合的方法,实现系统网损与负荷偏差的精确计算.然后,基于迭代的节点边际电价模型,以母线负荷为初始点编制发电计划,每次求解后将总发电量与系统负荷的偏差分摊至节点,修正其负荷,通过多次迭代求解节点边际电价.两步法节点边际电价模型,以系统负荷为依据,建立考虑系统网损与负荷偏差的耦合模型.第1步计算负荷偏差,第2步固定偏差计算节点边际电价.最后,通过比较所提方法与网损直接分摊方法的节点边际电价,以及分析不同负荷偏差水平、不同负荷偏差分配因子对节点边际电价的影响,验证了所提模型的有效性.

In order to deepen the reform of electric power market, guide the electric power residents to bring flexible energy resources into the market, and carry out the Point-to-Point(P2P) electric power trade(PEPT)among regional residents. This paper proposes PEPT method based on blockchain and “two-round trade matching” (TRTM). Firstly, based on the blockchain technology framework, a consensus mechanism for Ripple consistency with low computing power requirements is proposed and a P2P operation architecture is designed; Secondly, the TRTM process of PEPT between residents is proposed based on the technical characteristics of blockchain. Purchasers and sellers first declare the energy transaction information for the next period, perform matching and authentication according to the pre-declared power transaction (first round, FRPT) matching mechanism, clear PEPT orders; When there is a deviation in the execution of the transaction, purchasers and sellers are matched according to the deviation power transaction (second round, SRPT) mechanism, and the transaction costs are cleared according to PEPT clearing mechanism; For the problem of power measurement and price between residents, key technology designs, such as the matching mechanism of PEPT, the design of prices with equilibrium prices (EP) and flexible prices (FP). And the clearing method of SRPT are proposed. Finally, this paper verifies the feasibility of the mechanism and model of PEPT between residents through case, and provides a reference for the design of a flexible and open power trading mechanism between distribution network residents.

新能源机组具有控制灵活以及响应迅速等特点,在技术上具有参与电力系统调频的能力,如将其作为一种调频资源,将有利于缓解系统调频压力.考虑到新能源机组出力具有一定的波动性与不确定性,文中提出了新能源参与调频的辅助服务市场机制,以调频准确性概率指标评估其调频性能指标,进行其调频风险损失量化计算,建立了考虑新能源调频风险的市场出清模型;在实际调度过程中,考虑新能源机组实时调频准确性与历史数据的偏差,构建了基于模型预测控制的实时调频调度模型,根据调度结果和机组实时出力的准确性指标对调度进行反馈校正.提出的市场机制和调度策略既充分利用新能源作为调频资源,又有效地控制了新能源调频出力不确定性的风险.仿真结果验证了模型和算法的有效性.

Energy storage has attracted more and more attention for its advantages in ensuring system safety and improving renewable generation integration. In the context of China’s electricity market restructuring, the economic analysis, including the cost and benefit analysis, of the energy storage with multi-applications is urgent for the market policy design in China. This paper uses an income statement based on the energy storage cost–benefit model to analyze the economic benefits of energy storage under multi-application scenarios (capacity, energy, and frequency regulation markets) in China’s future electricity market. The results show that the economic benefits of energy storage can be improved by joining in the capacity market (if it exists in the future) and increasing participation in the frequency regulation market. Nevertheless, the benefits under multi-application scenarios can hardly guarantee the cost recovery of energy storage under the current market mechanism or at the current price levels. Moreover, the economic benefits under different subsidy policies are studied, and the results show that energy storage can recover the cost with appropriate subsidy policies (the subsidy of 0.071 USD/kWh for pumped storage power stations is sufficient while the subsidy of 0.142 USD/kWh is required for electrochemical power stations). Finally, the sensitivity analysis of an energy storage power station to different price levels is carried out considering the difference in electricity price between China and the United States.

为使基于电压源型换流器的柔性直流(VSC-HVDC)互联系统中的新能源端整体参与交流电网的频率调整,提出一种带频率-电压死区的换流站端有功控制策略.该控制策略利用频率-电压死区限值,通过VSC-HVDC输出功率的实时控制,在系统侧交流电网发生频率变化时,风机转子的动能储备短时内增加或减少有功输出,使风机转速下降或增高,通过增加或减少风机转子中的动能储备来缓解交流系统端的不平衡有功功率,通过VSC-HVDC互联系统作出频率响应参与调频.最后,利用PSCAD/EMTDC对该控制策略进行仿真验证,结果表明所提策略提高了含新能源接入的两端VSC-HVDC互联系统的频率稳定性.

Abstract With the continuous development of social economy, energy and environmental issues deserve more and more attention. In order to improve the new energy’s consumption, this paper proposes an optimized social income strategy for clean energy consumption based on transmission channel constraints. The main method combines the method of cooperative game to maximize the value of social income, so as to determine the optimal combination of power generation, then taking into account the constraints of transmission channels and other issues, and then solving the problem of cross-regional clean energy trade with the goal of maximal social benefits. At the same time, the proceeds from the cooperative game can be distributed to each power transaction entity through the method of nuclear solution.

This paper proposes a prospect theory (PT)-based bidding model of a prosumer in the power market. Unlike existing efforts of the bidding model that assume the rational behavior of the prosumers, the model incorporates irrationality and individual preferences to capture the prosumer-related subjective perceptions on the bidding results. Considering the impacts of the bidding rules of the power market, we build up the PT-based bidding models with 1-segment and multi-segment bidding rules, respectively. A case study with four different prosumers, i.e., rational, conservative, neutral, and aggressive prosumers is conducted, and the simulation results between expected value theory-based and the PT-based methods are compared. Simulation results validate the effectiveness of the proposed method.