Unit commitment health analysis for interconnected systems

The concepts previously published for unit commitment and operating reserve assessment in an isolated power system using a system well-being framework are extended in this paper to evaluate unit commitment and spinning reserve requirements in interconnected power systems. The problem of interconnected power systems unit commitment is decomposed into two subproblems. Unit scheduling is first performed in each isolated power system in accordance with the specified operating criterion. This is then followed by interconnected power system evaluation. The analysis is further extended to determine the operating state probabilities for the overall interconnected power system. The paper illustrates how power system well-being is improved by interconnection with other power systems. The concepts contained in the paper are illustrated by application to two radially interconnected IEEE-RTS     

Operating reserve assessment in interconnected generating systems

It is shown that the two risks concept can be used to determine the spinning reserve requirements of a multiarea interconnected system configuration. This is a probabilistic technique which takes into account the system parameters which directly or indirectly influence the system reliability. It is concluded that the use of a single system risk and an interconnected system risk provide valuable insight into the benefits of interconnection. These concepts are illustrated by application to two radially interconnected power systems     

Reliability computations for interconnected generating systems vialarge deviation approximation

The use of the large-deviation approximation is discussed for computing the reliability of two generating systems having correlated loads and interconnected by a transmission tie-line of a given capacity. The necessary formulas are derived and applied to a prototype two-area system model. Numerical results show that the proposed approximation is quite accurate. Information is provided on the speed of the algorithm     

Unit commitment solution methodology using genetic algorithm

Solution methodology of unit commitment (UC) using genetic algorithms (GA) is presented. Problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start up cost and spinning reserve, which is defined as minimization of the total objective function while satisfying the associated constraints. Problem specific operators are proposed for the satisfaction of time dependent constraints. Problem formulation, representation and the simulation results for a 10 generator-scheduling problem are presented     

考虑频率与区间联络线功率安全约束的两区互联电力系统机组组合

随着电源结构与电网形态的转变,互联电力系统频率时空分布特征日益显著,区域频率差异与区间联络线功率振荡增大,基于统一频率假设的频率安全约束机组组合方法不再适用。针对考虑频率时空分布特征的两区互联电力系统安全约束机组组合,推导区域频率与区间联络线功率闭式解,并基于闭式解的两项划分,推得区域频率最低点、最大变化率、准稳态值以及区间联络线功率振荡峰值、准稳态值等一系列解析安全量化指标。基于所得指标,构建考虑区域频率与区间联络线功率安全约束的机组组合模型。并根据调度模式与指标特点,提出兼顾区域能力保障与区间能力协调的两级两阶段迭代求解算法。结果表明,所得指标可准确描述两区互联电力系统的安全特征,所提模型和算法可有效保障两区互联电力系统机组组合方案的运行安全。     

改进的拉格朗日松弛法求解机组组合问题

提出了一种求解机组组合问题的改进拉格朗日松弛算法.与现有此类方法相比,此算法进行了以下三个方面改进:基于启发式排序法得到较优的拉格朗日乘子初值;改进了动态规划求解单机问题时的累计费用以获得更优的机组启停决策;采用自适应性次梯度法结合集结投影次梯度法的联合优化策略加快算法收敛速度.10机到100机的6个算例表明,自适应性次梯度法和集结投影次梯度法的联合优化策略更易跳出其单一策略时的振荡现象,从而加快收敛.     

Stabilizing interconnected power systems using static phase shifters

This paper presents a digital simulation study of proposed thyristor controlled static phase shifter applications in steady state stability enhancement of interconnected power systems. Incorporation of a detailed linearized model of a static phase shifter into the dynamics of the interconnected power system facilitates the investigation of different control strategies for static phase shifters to damp the electromechanical and torsional oscillations.     

Unit commitment using Lagrangian relaxation and particle swarm optimization

Unit commitment (UC) is a NP-hard nonlinear mixed-integer optimization problem. This paper proposes ELRPSO, an algorithm to solve the UC problem using Lagrangian relaxation (LR) and particle swarm optimization (PSO). ELRPSO employs a state-of-the-art powerful PSO variant called comprehensive learning PSO to find a feasible near-optimal UC schedule. Each particle represents Lagrangian multipliers. The PSO uses a low level LR procedure, a reserve repairing heuristic, a unit decommitment heuristic, and an economic dispatch heuristic to obtain a feasible UC schedule for each particle. The reserve repairing heuristic addresses the spinning reserve and minimum up/down time constraints simultaneously. Moreover, the reserve repairing and unit decommitment heuristics consider committing/decommitting a unit for a consecutive period of hours at a time in order to reduce the total startup cost. Each particle is initialized using the Lagrangian multipliers obtained from a LR that iteratively updates the multipliers through an adaptive subgradient heuristic, because the multipliers obtained from the LR tend to be close to the optimal multipliers and have a high potential to lead to a feasible near-optimal UC schedule. Numerical results on test thermal power systems of 10, 20, 40, 60, 80, and 100 units demonstrate that ELRPSO is able to find a low-cost UC schedule in a short time and is robust in performance.     

Unit commitment of main transformers for electrified mass rapid transit systems

This paper proposes the transformer planning for an electrified mass rapid transit (MRT) system so that the overall cost of main transformers is minimized over the life cycle. The unit commitment is applied to derive the optimal transformer capacity to meet the annual peak demand and provide reserve for service reliability. The motion equation of train sets is used to derive the dynamic power consumption and travel distance as each time snapshot. The Simulink package is applied to solve the power demand of each train set by the simulation of VVVF inverters and induction motors. The DC/AC load flow analysis is performed to find the annual power loading of traction substations (TSS) and whole Taipei MRT network. The transformer loss, investment, and service reliability are used to define the equivalent cost of all feasible states for each dynamic programming (DP) stage. According to the computer simulation, very significant cost saving is obtained by the proposed methodology for transformer capacity planning of an MRT network.     

Unit commitment literature synopsis

Several optimization techniques have been applied to the solution of the thermal unit commitment problem. They range from heuristics such as complete enumeration to the more sophisticated ones such as Augmented LaGrangian. The heuristics have even reappeared as expert systems. The problem to solve is the optimal scheduling of generating units over a short-term horizon, typically 168 hours. This paper is an overview of the literature in the unit commitment field over the past twenty five years     

Unit commitment using load forecasting based on artificial neural networks

This paper consists of two parts. While the first part shows the application of artificial neural networks to load forecasting using new input-output models, the second part utilizes the results from the first part in unit commitment. Based on the forecasts provided, unit commitment schedules are obtained for both hourly and daily load variations. Issues related to both problems are discussed along with an illustration of the two-step method using data obtained from a local utility. While a generation schedule such as this is not only invaluable to power system planners and operators, it is shown that this two-step process paves the way for an artificial intelligence (AI) type of method for the unit commitment problem based on the same inputs as the load forecasting method. For the chosen inputs, the simulations here show an average error of 4.3% and 3.1% in the case of the daily (twenty-four hours ahead) and hourly (one hour ahead) load forecast, respectively.     

Unit commitment problem in deregulated environment

This paper addresses the self-scheduling problem of generation companies owning thermal power units considering bilateral contracts and day-ahead market. This approach allows precise modelling of variable costs, start-up costs and comprehensive system of constraints. The self-scheduling model is formulated as deterministic optimization problem in which expected profit is maximized by 0/1 mixed-integer linear programming technique. Solution is achieved using the homogeneous and self-dual interior point method for linear programming, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model for optimizing the thermal generation schedule is demonstrated through the case study with detailed discussion.     

Unit commitment with ramp multipliers

This paper presents a new decomposition method, based on the Lagrangian relaxation technique, for solving the unit commitment problem with ramp rate constraints. By introducing an additional vector of multipliers to represent the cost of “system ramping demand”, this method can handle the coupling constraints between time periods while still keeping the simplicity of the original decomposition method. A new algorithm for updating multipliers is also proposed. Similar to the bundle algorithm, this algorithm maintains the previous iteration history to approximate the dual envelope. Unlike the bundle algorithm, this new algorithm generates an update step along the subgradient direction without any quadratic programming (QP) code. The new algorithm combines the bundle algorithm's smooth approach to the dual optimum with the sub-gradient method's fast update     

考虑电动汽车入网技术的电力系统机组组合研究

为了提高电动汽车入网技术（V2G）的电力系统机组组合实用性和经济性,提出一种考虑可入网电动汽车（PEV）的数量变化和电池电荷状态变化的机组组合算法。利用电池电荷状态与充放电电量之间的关系,结合预估的不同时段入网PEV数量,确定每天入网PEV的净充电总需求量。构建考虑电动汽车入网技术的电力系统机组组合模型,以发电成本为目标函数,加入电池电荷状态的罚函数,求解电力系统机组的出力计划和入网PEV的充放电控制计划。分析了不同情景下充放电最优控制和机组组合结果,对比了不同PEV充电模式对电力系统机组组合结果的影响。算例分析结果表明,该方法可以有效的节省机组成本,实现电动汽车的连续调度,证明了该方法的正确性和有效性。     

Unit commitment risk with sequential rescheduling

Rescheduling decisions in power system operation are often made to commit additional generating capacity to meet the system obligation of load plus spinning reserve. These are based on the observation of some events (e.g. unit forced outage) which lead to possible capacity deficiency. A new concept is presented of unit commitment risk analysis which explicitly models the stochastic sequence of events associated with rescheduling decisions. This concept is compared with that of the PJM method via a simple example. Based on the concept of rescheduling, a stochastic model is proposed for risk analysis, and this model is illustrated via simulation results     

基于分布鲁棒机会约束的机组组合模型

可再生能源的大量渗透使得传统的机组组合的解决方法不可行,文中主要对含有不确定变量约束的机组组合模型进行研究.将含不确定变量的功率平衡约束松弛为不等式约束,并将该不等式约束与旋转备用约束以及传输极限约束均转化为基于矩信息模糊集的分布鲁棒机会约束模型,采用双边模型处理传输极限约束以提高可靠性;为了使模型便于求解,双边模型采...     

Unit commitment taking into account reactive power

In this paper, the Voltage Magnitude Constrained OPF (VMC‐OPF) algorithm to determine the reactive power injection from compensating equipment to load bus is developed. By introducing the proposed VMC‐OPF to the real power related Unit Commitment (UC) [1], a novel daily UC method taking into account the reactive power to secure bus voltage magnitude is presented. The Transmission Access Charge (TAC) and Ancillary Services Charge (ASC) are included in the objective function for considering costs of using transmission network and supplying reactive power to maintain the voltage. Using the proposed UC, the difference between two schedules based on benefit maximization and cost minimization is also discussed. To ascertain the effectiveness of the proposed UC method, we demonstrate various simulation results for a model power system of IEEE‐118 bus system. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(3): 17–26, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20590     

Unit commitment with primary frequency regulation constraints

The unit commitment problem with tertiary reserve requirements has been broadly studied. Such reserves, when needed, are centrally deployed with relatively slow time constants of the order of minutes. In contrast, the scheduling of units offering primary frequency regulation reserve deployable in a decentralized manner within seconds of a contingency has received relatively little attention. In this paper, we formulate and solve a multiperiod unit commitment that simultaneously accounts for both primary and tertiary reserve constraints. What makes this scheduling problem particularly challenging is the characteristic that primary frequency regulation reserves have a common single degree of freedom, namely, the system frequency deviation.