A Quick Method for Judging the Feasibility of Security-Constrained Unit Commitment Problems within Lagrangian Relaxation Framework

Generally, the procedure for Solving Security constrained unit commitment (SCUC) problems within Lagrangian Relaxation framework is partitioned into two stages: one is to obtain feasible SCUC states;the other is to solve the economic dispatch of generation power among all the generating units. The core of the two stages is how to determine the feasibility of SCUC states. The existence of ramp rate constraints and security constraints increases the difficulty of obtaining an analytical necessary and sufficient condition for determining the quasi-feasibility of SCUC states at each scheduling time. However, a numerical necessary and sufficient numerical condition is proposed and proven rigorously based on Benders Decomposition Theorem. Testing numerical example shows the effectiveness and efficiency of the condition.

Optimal Intelligence Planning of Wind Power Plants and Power System Storage Devices in Power Station Unit Commitment Based

Renewable energy sources(RES)such as wind turbines(WT)and solar cells have attracted the attention of power system operators and users alike,thanks to their lack of environmental pollution,independence of fossil fuels,and meager marginal costs.With the introduction of RES,challenges have faced the unit commitment(UC)problem as a traditional power system optimization problem aiming to minimize total costs by optimally determining units’inputs and outputs,and specifying the optimal generation of each unit.The output power of RES such as WT and solar cells depends on natural factors such as wind speed and solar irradiation that are riddled with uncertainty.As a result,the UC problem in the presence of RES faces uncertainties.The grid consumed load is not always equal to and is randomly different from the predicted values,which also contributes to uncertainty in solving the aforementioned problem.The current study proposes a novel two-stage optimization model with load and wind farm power generation uncertainties for the security-constrained UC to overcome this problem.The new model is adopted to solve the wind-generated power uncertainty,and energy storage systems(ESSs)are included in the problem for further management.The problem is written as an uncertain optimization model which are the stochastic nature with security-constrains which included undispatchable power resources and storage units.To solve the UC programming model,a hybrid honey bee mating and bacterial foraging algorithm is employed to reduce problem complexity and achieve optimal results.

Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration

The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen(P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub(EH) with both a P2H facility(electrolyzer) and a gas-to-power(G2P) facility(hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment(SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming(MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration(HWP).

A Comprehensive Review of Security-constrained Unit Commitment

Security-constrained unit commitment(SCUC)has been extensively studied as a key decision-making tool to determine optimal power generation schedules in the operation of electricity market.With the development of emerging power grids,fruitful research results on SCUC have been obtained.Therefore,it is essential to review current work and propose future directions for SCUC to meet the needs of developing power systems.In this paper,the basic mathematical model of the standard SCUC is summarized,and the characteristics and application scopes of common solution algorithms are presented.Customized models focusing on diverse mathematical properties are then categorized and the corresponding solving methodologies are discussed.Finally,research trends in the field are prospected based on a summary of the state-of-the-art and latest studies.It is hoped that this paper can be a useful reference to support theoretical research and practical applications of SCUC in the future.

A Fast Calculation Method for Long-term Security-constrained Unit Commitment of Large-scale Power Systems with Renewable Energy

With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangement for the long-term power generation plan has become more crucial. Security-constrained unit commitment(SCUC) is a critical technical means to optimize the long-term power generation plan. However, the plentiful power sources and the complex grid structure in largescale power systems will bring great difficulties to long-term SCUC. In this paper, we propose a fast calculation method for long-term SCUC of large-scale power systems with renewable energy. First, a method for unit status reduction based on temporal decomposition is proposed, which will reduce plenty of binary variables and intertemporal constraints in SCUC. Then,an efficient redundant constraint identification(RCI) method is developed to reduce the number of network constraints. Furthermore, a joint accelerated calculation framework for status reduction and RCI is formed, which can reduce the complexity of long-term SCUC while ensuring a high-precision feasible solution. In case studies, numerical results based on two test systems ROTS2017 and NREL-118 are analyzed, which verify the effectiveness and scalability of the proposed calculation method.

Graph Theory Based N-1 Transmission Contingency Selection and Its Application in Security-constrained Unit Commitment

Contingency analysis is an important building block in the stability and reliability analysis of power grid operations. However, due to the large number of transmission lines,in practice only a limited number of contingencies could be evaluated. This paper proposes a graph theory based N-1 contingency selection method to effectively identify the most critical contingencies, which can be used in security-constrained unit commitment(SCUC) problems to derive secure and economic operation decisions of the power grid. Specifically, the power flow transferring path identification algorithm and the vulnerability index are put forward to rank individual contingencies according to potential transmission line overloads. Effectiveness of the proposed N-1 contingency selection method is quantified by applying the corresponding SCUC solution to the full N-1 security evaluation, i. e., quantifying total post-contingency generation-load imbalance in all N-1 contingencies. Numerical results on several benchmark IEEE systems, including5-bus, 24-bus, and 118-bus systems, show effectiveness of the proposed method. Compared with existing contingency selection methods which usually resort to full power flow calculations,the proposed method relies on power gird topology to effectively identify critical contingencies for facilitating the optimal scheduling of SCUC problems.

Big-M based MILP method for SCUC considering allowable wind power output interval and its adjustable conservativeness

In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.

基于边界法的大型机组组合模型的简化方法

随着电网规模的持续扩大,市场环境下考虑网络安全约束的机组组合(security-constrained unit commitment,SCUC)模型中的变量和约束显著增加,模型的求解性能变差。当模型规模过大时,会出现现有的商用求解器无法求解的状况,造成大规模模型求解困难的问题。为实现大规模机组组合模型的快速求解,从减少模型约束数量的角度出发,提出了一种基于边界法的线性约束简化方法。通过边界法剔除模型中冗余的线性约束,可以有效降低模型规模,实现模型的快速求解。基于IEEE-39、WECC 179和IEEE-118算例,在市场环境下进行日前SCUC测试。通过对比简化前后的求解时间,表明该方法能够显著提高模型的求解速率。

Security Constrained Unit Commitment with Extreme Wind Scenarios

The rapid development of economy and society stimulates the increase of power demand. Wind power has received great attention as a typical renewable energy, and the share of wind power is continually increasing in recent years.However, the high integration of wind power brings challenges to the secure and reliable operation of power grid due to the intermittent characteristic of wind power. In order to solve the operation risk caused by wind power uncertainty, this paper proposes to solve the problem of stochastic security-constrained unit commitment(SCUC) by considering the extreme scenarios of wind power output. Firstly, assuming that the probability density distribution of wind power approximately follows a normal distribution, a great number of scenarios are generated by Monte Carlo(MC) simulation method to capture the stochastic nature of wind power output. Then, the clustering by fast search and find of density peaks(CSFDP) is utilized to separate the generated scenarios into three types: extreme, normal and typical scenarios. The extreme scenarios are identified to determine the on/off statuses of generators, while the typical scenarios are used to solve the day-ahead security-constrained economic dispatch(SCED) problem. The advantage of the proposed method is to ensure the robustness of SCUC solution while reducing the conservativeness of the solution as much as possible.The effectiveness of the proposed method is verified by IEEE test systems.

Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs

With the large-scale integration of renewable energy,the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy generation.Simultaneously,in a market-oriented operation mode,the power dispatching control center aims to reduce the overall power purchase cost while ensuring the security of the power system.Therefore,a security-constrained transmission maintenance optimization model considering generation and operational risk costs is proposed herein.This model is built on double-layer optimization framework,where the upper-layer model is used for maintenance and generation planning,and the lowerlayer model is primarily used to address the operational security risk arising from the random prediction error and N-1 transmission failure.Correspondingly,a generation-maintenance iterative algorithm based on a defined cost feedback is included to increase solution efficiency.Generation cost is determined using long-term security-constrained unit commitment,and the operational risk cost is obtained using a double-layer N-1 risk assessment model.An electrical correlation coupling coefficient is proposed for the solution process to avoid maintenance of associated equipment simultaneously,thereby improving model convergence efficiency.The IEEE 118-bus system is used as a test case for illustration,and test results suggest that the proposed model and algorithm can reduce the total cost of transmission maintenance and system operation while effectively improving the solution efficiency of the joint optimization model.

求解安全约束机组组合问题的混合整数规划算法性能分析

安全约束机组组合(SCUC)是当前国外电力生产和调度中应用的先进优化软件。简要介绍了SCUC的发展背景,给出了SCUC的完整数学模型和优化算法。基于混合整数规划算法开发了SCUC优化程序。以IEEERTS标准系统进行500台机组系统和中国某省级实际电网(161台机组,109个安全断面)的分析计算,结果验证了该算法和程序的有效性和实用性。

考虑电网N-1闭环安全校核的最优安全发电计划

提高发电计划的安全性和经济性是将短期发电计划应用于实际调度运行的关键。提出了将机组组合与电网线路N-1安全校核直接闭环的发电计划模式,实现了考虑线路N-1闭环安全校核的机组组合全空间优化,有效地提高了发电计划的安全性和经济性。基于该模式,提出了主、子问题一体控制的最优奔德斯(Benders)分解方法,确保了分解协调的最优性和高效性,并且将起作用整数变量的识别方法嵌入主问题求解流程,进一步提高了安全机组组合模型的求解效率,为所提方法的实用化奠定了计算基础。理论分析和算例测试验证了所提最优闭环发电计划的最优性和高效性。

月度安全约束机组组合建模及求解

月度发电计划的复杂性和求解规模,使得月度机组组合方案的制订变得十分困难。文中基于兼顾计算性能和月度计划关键需求的原则,通过时段简化和电力电量解耦,建立了以电量进度偏差最小为目标的月度安全约束机组组合(SCUC)模型,并采用混合整数规划(MIP)算法加以求解。实际系统算例测试验证了该模型的有效性。

基于奔德斯算法的安全约束机组组合方法

针对采用混合整数规划算法直接求解安全约束机组组合,将使计算效率大幅度降低,而利用奔德斯算法求解则存在着算法振荡和受系统规模制约求解效率下降的问题,提出了一种基于奔德斯算法的安全约束机组组合新方法。该方法在奔德斯算法的基础上,通过纳入新增越限约束校正环节,控制了奔德斯割的寻优方向,通过增加起作用约束识别环节,缩小了奔德斯算法的寻优空间,进而提高了安全约束机组组合优化问题的求解效率。6机3节点和54机118节点算例验证了所提方法的有效性。

机组组合算法中起作用整数变量的辨识方法

应用成熟的数学规划方法求解机组组合问题是当前的发展趋势,但是整数变量太多使得该问题的求解效率太低。在深入研究机组组合的模型特点以及电力系统的物理本质的基础上,提出了混合整数规划问题中起作用整数变量的新概念,据此提出了能够综合考虑系统时段耦合约束、网络安全约束以及机组启停费用的规范化起作用整数变量辨识方法。通过对起作用整数变量进行组合优化计算,将不起作用整数变量直接转化为连续变量求解,有效缩小了机组组合的寻优空间,在不影响机组组合最优解的前提下,提高了求解效率,对大幅度提高机组组合的计算效率和应用水平具有重要的价值。理论分析和算例测试验证了该方法的有效性。

安全约束机组组合理论与应用的发展和展望

安全约束机组组合作为编制发电计划的核心环节,在国外电力市场中已经得到广泛的应用。随着中国电网全面推进精益化的调度管理和节能发电调度的实施,电网运行部门对安全经济运行的要求日益提高,安全约束机组组合的研究和应用也越来越受到重视。总结了安全约束机组组合的模式、数学模型和主要求解方法;在综述国内外最新研究动态和工业应用现状的基础上,展望了未来有待进一步研究的内容。希望本文的工作能够为推动中国发电计划领域的研究和应用提供重要参考。

考虑跨区直流调峰的日前发电计划优化方法及分析

阐述了中国跨区直流输电对促进西北地区新能源消纳的重要性,分析了目前跨区直流外送模式对新能源消纳的不利影响。综合考虑分析直流输电系统的运行特性和跨区电能交易需求,建立了跨区直流计划调整的混合整数线性约束模型,提出了考虑跨区直流互动调峰的新能源与常规能源协调优化的两阶段日前发电计划编制方法。首先,基于安全约束经济调度(SCED)模型分析了受端电网直流接纳能力。然后,基于安全约束机组组合(SCUC)模型,综合考虑直流计划调整约束、系统平衡、机组运行、新能源出力预测和电网安全等约束条件,以节能环保和新能源消纳最大为优化目标,编制送端电网的机组组合、出力计划和直流送出计划。最后,通过某省级电网及其跨区直流计划优化调整的算例验证了所提方法的有效性。

松弛约束发电计划优化模型和算法

安全约束机组组合和安全约束经济调度是发电计划优化的核心,算法鲁棒性是影响其工程应用的关键因素。在对通用安全约束机组组合优化模型分析基础上,提出安全约束发电计划的松弛约束模型。通过松弛机组发电量约束、环保约束、网络约束、机组速率约束和机组调节范围约束等,提高算法收敛性能。文中所提出的模型和算法已成功应用于某省级电网。

基于风险指标与非支配故障筛选理论的安全约束机组组合算法

安全约束机组组合(SCUC)是一种常用的电力系统运行调度方法,但在实际的大规模系统应用中需要大量的预想故障及多个时间断面的信息,求解困难。针对如何加快SCUC求解速度的问题,在传统安全约束机组组合算法的基础上,采用改进过载风险指标代替传统的过载严重度指标,结合非支配故障筛选理论,提出一种基于风险指标与非支配故障筛选理论的安全约束机组组合算法。算例结果表明:算法采用的故障集更合理,具有迭代速度快、安全性高和经济性好的特点,可为调度员的实时快速决策提供重要帮助。

全周期变时段“三公”调度发电计划优化模型

以年度合同进度为主要控制目标的"三公"调度是我国目前最为普遍的调度模式,常用的安全约束机组组合(security constrained unit commitment,SCUC)/安全约束经济调度(security constrained economic dispatch,SCED)模型不能满足"三公"调度计算周期要求,为此建立了考虑电网安全约束的全周期发电计划优化模型,并依据不同时段发电计划的需求差异,进一步建立了全周期变时段发电计划优化模型,该模型可根据时段长度自动选择各种约束。算例结果表明全周期变时段发电计划优化模型能够适应"三公"调度需要,计算性能能够满足大规模电网发电计划精细化管理需要。