考虑节点边际价格的热电联产机组主从博弈竞价策略

本文构建了以热电联产机组(combined heat and power unit,CHP)、电力市场和热力市场为参与者的主从博弈模型,并基于电力市场中节点边际电价(locational marginal electricity price,LMEP)的概念,提出了节点边际热价(locational marginal heat price,LMHP)的概念.在节点边际电价的求解中,采用了支路潮流(branch power flow,BPF)模型,考虑了配电网中的网络损耗从而可以得到更精确的计算结果.在节点边际热价的求解中,考虑了管道热损耗,并基于管道损耗方程分析了节点边际热价的分布规律.在此基础上,采用变步长迭代寻优算法求解热电联产机组、电力市场、热力市场各自最优出力和最优报价策略.最后,通过一个6节点电网–4节点热网的算例对所构建的主从博弈模型及热电联产机组的竞价策略进行了验证.     

Carbon emission impact on the operation of virtual power plant with combined heat and power system

A virtual power plant (VPP) can realize the aggregation of distributed generation in a certain region, and represent distributed generation to participate in the power market of the main grid. With the expansion of VPPs and ever-growing heat demand of consumers, managing the effect of fluctuations in the amount of available renewable resources on the operation of VPPs and maintaining an economical supply of electric power and heat energy to users have been important issues. This paper proposes the allocation of an electric boiler to realize wind power directly converted for supplying heat, which can not only overcome the limitation of heat output from a combined heat and power (CHP) unit, but also reduce carbon emissions from a VPP. After the electric boiler is considered in the VPP operation model of the combined heat and power system, a multi-objective model is built, which includes the costs of carbon emissions, total operation of the VPP and the electricity traded between the VPP and the main grid. The model is solved by the CPLEX package using the fuzzy membership function in Matlab, and a case study is presented. The power output of each unit in the case study is analyzed under four scenarios. The results show that after carbon emission is taken into account, the output of low carbon units is significantly increased, and the allocation of an electric boiler can facilitate the maximum absorption of renewable energy, which also reduces carbon emissions from the VPP.     

Optimal Operation of Distributed Generations Considering Demand Response in a Microgrid Using GWO Algorithm

The widespread penetration of distributed energy sources and the use of load response programs, especially in a microgrid, have caused many power system issues, such as control and operation of these networks, to be affected. The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid. In this paper, the optimum operation of distributed generation resources and heat and power storage in a microgrid, was performed based on real-time pricing through the proposed gray wolf optimization (GWO) algorithm to reduce the energy supply cost with the microgrid. Distributed generation resources such as solar panels, diesel generators with battery storage, and boiler thermal resources with thermal storage were used in the studied microgrid. Also, a combined heat and power (CHP) unit was used to produce thermal and electrical energy simultaneously. In the simulations, in addition to the gray wolf algorithm, some optimization algorithms have also been used. Then the results of 20 runs for each algorithm confirmed the high accuracy of the proposed GWO algorithm. The results of the simulations indicated that the CHP energy resources must be managed to have a minimum cost of energy supply in the microgrid, considering the demand response program.     

Recurrent neural network for combined economic and emission dispatch

Recently, the combined economic and emission dispatch (CEED) problem, which aims to simultaneously decrease fuel cost and reduce environmental emissions of power systems, has been a widespread concern. To improve the utilization efficiency of primary energy, combined heat and power (CHP) units are likely to play an important role in the future. The goal of this study is to propose an approach to solve the CEED problems in a CHP system which consists of eight power generators (PGs), two CHP units and one heat only unit. Owing to the existence of power loss in power transmission line and the non-convex feasible region of CHP units, the proposed problem is a nonlinear, multi-constraints, non-convex multi-objectives (MO) optimization problem. To deal with it, a recurrent neural network (RNN) combined with a novel technique is developed. It means that the feasible region is separated into two convex regions by using two binary variables to search for different regions. In the frame of the neurodynamic optimization, existence and convergence of the dynamic model are analyzed. It shows that the convergence solution obtained by RNN is the optimal solution of CEED problem. Numerical simulation results show that the proposed algorithm can generate solutions efficiently.     

综合能源热力潮流节点标幺值模型及算法实现

潮流计算是综合能源能量管理的基础,已有的综合能源潮流计算模型,采用电力网络节点模型与热力网络回路模型组合,实时潮流计算过程中,要在网络拓扑形成节点之后,搜索供热网络回路,形成多个独立的最小热力回路,在最小回路模型的基础上,做牛顿法潮流计算;为了方便与电网潮流的节点模型组合,提高综合能源潮流计算的算法效率和收敛性能,我们采用热力网络潮流节点标幺值模型,用热力节点的供水温度、回水温度、供水压力、回水压力作为热力网络状态量,用回水、供水节点净注入流量为零、回水、供水节点节点的注入能量为零作为基础模型,采用变尺度算法解热力潮流非线性方程组,只计算一次雅可比矩阵并求逆,通过递推来实现潮流计算,克服了牛顿法需要多次求导求逆的缺点,避免了搜索实时网络的最小回路,方便与电力网络节点模型联合求解,更适合大规模热-电联合系统中的潮流计算。     

Modelling of the whole process of a university campus CHP power plant and dynamic performance study

Combined heat and power (CHP) refers to a process/system designed to utilize the waste or residual heat from a power generation process. Thus, a CHP plant can produce both electricity and heat. The nature of such a combination makes the process more complex than any single power generation process or boiler heating system. The paper focuses on modelling study and analysis of energy efficiency of the University of Warwick micro-CHP power plant. In this CHP modelling study, a gas turbine module is built to provide driving power and methane is used as fuel gas. Heat recovery system and auxiliary boiler modules are developed for thermal power generation. All the sub-systems are validated by comparing the simulation results with the operating data collected from the CHP plant. The dynamic performance of the key CHP process outputs is studied with respect to the variation of the input syngas stream, including electricity generation, thermal power output and water output temperature. Simplified controllers are also applied to the gas engineheat recovery subsystem and auxiliary boiler. Simulation results with/without feedback control are both analyzed. The study has highlighted the key factors which influence the plant performance and suggested the strategy for potential energy efficiency improvement.     

通用蒸汽动力系统的综合与模拟

为解决实际化工生产中各生产单元、工艺过程对不同品级蒸汽的需求,本文把不同的蒸汽动力循环过程归纳综合成一种通用的过程,并使过程模型化。基于这种通用的数学模型,开发了可以模拟计算蒸汽动力循环过程的计算机软件。通过实例表明通过该软件程序可以计算系统各单元的蒸汽和水的热力学性质、流量及换热单元的热负荷,为过程动力、热能、工艺蒸汽等的分配提供参考数据,对实际生产具有重要的指导意义。     

New optimization method based on energy management in microgrids based on energy storage systems and combined heat and power

Microgrids can be assumed as a solution model for green energy sources, energy storage systems, and combined heat and power (CHP) systems. In this work, the cost and emission minimization based on a demand response (DR) program is considered an optimization problem. To solve the mentioned problem a new multiobjective optimization algorithm (improved particle swarm optimization) is proposed based on a fuzzy mechanism to select the optimal value. The microgrid system includes two CHP units, fuel cell and battery systems, and the heat buffer tank. In this problem, two different feasible operating regions have been assumed in CHPs. Accordingly, to decrease the operational cost, time-of-use, and real-time pricing DR programs have been simulated, and the impacts of the mentioned models are evaluated overload profiles. The effectiveness of proposed models has been applied on different cases studies by different scenarios. The proposed model solved the DR program, time of use-DR and real-time pricing-DR problems. The proposed model could reduce the cost about 10%.     

Simulation of maximum power in the wearable thermoelectric generator with a small thermopile

Miniature thermopiles that could be fabricated by using modern thin- and thick-film technologies are discussed as a power supply to wearable devices. The maximum power that can be produced by a thermopile of a medium-to-small size was simulated in case of typical thermal properties of humans and their living environment. The local thermal resistances of human being required for the simulation were obtained experimentally. The designs of wearable thermoelectric generators are discussed. The general design optimization of wearable thermoelectric energy harvester with a miniature thermopile was performed in case of near-maximum power generated per unit volume of thermoelectric generator. The obtained performance characteristics allow prediction of the application area for wearable energy harvesters of human body heat and the perspectives of their market success.     

Simplifying discovered process models in a controlled manner

Process models discovered from a process log using process mining tend to be complex and have problems balancing between overfitting and underfitting. An overfitting model allows for too little behavior as it just permits the traces in the log and no other trace. An underfitting model allows for too much behavior as it permits traces that are significantly different from the behavior seen in the log. This paper presents a post-processing approach to simplify discovered process models while controlling the balance between overfitting and underfitting. The discovered process model, expressed in terms of a Petri net, is unfolded into a branching process using the event log. Subsequently, the resulting branching process is folded into a simpler process model capturing the desired behavior.     

电力需求侧管理与错峰用电分析浅谈

结合当前国内用电形势和供电企业具体的业务特点,以及电网建设的发展趋势,阐述电力需求管理与用户行为引导的关系,以及供电企业如何进行客户用电行为分析,制定和优化电力需求侧错峰用电方案,实现错峰用电的精细化管理。通过已知历史和未知预测等各种复杂环境进行分析,根据供电企业的业务错峰方案所需的条件及流程,构建错峰用电方案的算法模型,并以此为基础设计出有效支撑供电企业业务开展的电力需求侧错峰分析报告以辅助企业决策提供支持。     

一种多输入多输出系统模型辨识方法及其应用

目前的辨识方法一般需要在系统输入端加入激励信号，而且多输入多输出系统的在线辨识仍很困难。本文提出一种基于牛顿迭代法的多输入、多输出对象模型迭代辨识方法，模型参数更新的依据是使模型预测输出与全部采样时刻的对象实际输出之间的均方差递减，直到收敛。这种基于全局数据迭代的辨识方法可进行闭环辨识，无需外加激励信号，适用于多输入多输出对象的在线辨识。对一个两输入、两输出对象模型的仿真研究和某电厂300MW机组负荷被控对象的计算结果表明，辨识效果令人满意。     

基于风电消纳的热电系统储热模型仿真

为了有效解决电热联合系统弃风严重、煤耗量较高的问题,基于风电消纳的热电系统储热模型.融合不同的系统组建电热联合系统,以热电联产机组最小煤耗及最低成本为目标,通过风电消纳需求提升系统中用户需求的灵活性,同时挖掘用户的需求响应侧潜力,组建基于风电消纳的电热联合系统储热模型.采用粒子群算法对电热联合系统储热模型进行求解,得到...     

GPU-based model predictive control for continuous casting spray cooling control system using particle swarm optimization

Model predictive control (MPC) for spray cooling control system requires a repeated online solution of an optimization problem that includes partial differential equations (PDEs). To simulate the future temperature behavior of steel billets, 3D dynamic heat transfer model is used. The special solution domain of PDEs has led to large computation cost, which is the main challenge in the real-time practical application of spray cooling control system. Meanwhile, the heat transfer coefficients need to be identified using the measured surface temperature. This work presents a two-level parallel solution method implemented on a Graphics processing unit (GPU) for MPC of spray cooling control systems and a weighted least squares modified conjugate gradient method (WLS–MCG) for identification of heat transfer coefficients. Two-level parallel solution method consists of parallel-based heat transfer model and stream parallel particle swarm optimization (PSO). PSO is used to solve the optimization problem. WLS–MCG consists of the weighted least squares (WLS) and modified conjugate gradient method (MCG). The experimental results show that the two-level parallel solution method has good computational performance and achieves satisfactory control performance.     

风险规避下不同权力结构闭环供应链决策研究

将制造商风险规避行为特征考虑到不同权力结构闭环供应链博弈模型中,利用均值-方差理论探讨风险规避行为和权力结构对闭环供应链决策的影响。研究表明：随着制造商风险规避程度的提高,各权力结构下的批发价、绿色度、零售价和产品性价比逐渐降低;市场中领导者的先动优势总会使其制定出更加有利于自身的决策。对于制造商而言,在零售商主导和无权力结构的市场中,适度的规避风险有助于其效用的提高,而在自身主导的市场中,风险规避行为反而对其不利;当消费者对产品绿色品质的追求较低时,处于无权力结构的市场最有利,否则处于零售商主导的市场会更有利,然而无论消费者处于何种权力结构的市场,制造商风险规避行为都会对其产生负面影响。     

Statistical process control based fault detection of CHP units

This paper describes a fault diagnosis method that provides early detection of fouling of the heat recovery system of combined heat and power units. Early detection of fouling build-up is difficult from basic data analysis methods due to limited instrumentation, and a unit can operate for many months with a reduced heat transfer rate before an unplanned shut down. This novel application of statistical process control (SPC) using an estimate of the coolant flow rate, provides advanced warning of fouling build-up and allows significantly increased energy recovery and reduced financial losses from unplanned unit shut down and incorrect fault identification.     

交流励磁双馈发电机模型的建立与控制

众所周知,采用交流励磁双馈发电机的变速恒频风力发电系统具有许多优点,例如最大限度的捕捉风能,允许原动机在一定范围内变速运行,可灵活调节系统的有功和无功功率,起到功率因数补偿的作用。为了能比较清楚地研究变速恒频双馈风电系统的工作特性,需要建立一套能合理反映交流励磁双馈发电机运行特性、且适合应用于变速恒频风电机组性能研究的数学模型。     

交流励磁双馈发电机模型的建立与控制

众所周知,采用交流励磁双馈发电机的变速恒频风力发电系统具有许多优点,例如最大限度的捕捉风能,允许原动机在一定范围内变速运行,可灵活调节系统的有功和无功功率,起到功率因数补偿的作用。为了能比较清楚地研究变速恒频双馈风电系统的工作特性,需要建立一套能合理反映交流励磁双馈发电机运行特性、且适合应用于变速恒频风电机组性能研究的数学模型。     

Model checking, testing and verification working together

We present a symbolic model checking approach that allows verifying a unit of code, e.g., a single procedure or a collection of procedures that interact with each other. We allow temporal specifications that assert over both the program counters and the program variables. We decompose the verification into two parts: (1) a search that is based on the temporal behavior of the program counters, and (2) the formulation and refutation of a path condition, which inherits conditions constraining the program variables from the temporal specification. This verification approach is modular, as we do not require that all the involved procedures are provided. Furthermore, we do not request that the code is based on a finite domain. The presented approach can also be used for automating the generation of test cases for unit testing.A preliminary version of the paper, with the title Unit Checking: Symbolic Model Checking for a Unit of Code appears in the Lecture Notes in Computer Science volume 2772, Verification– Theory and Practice, celebrating Zohar Manna’s 64th birthdayThis research was partially supported by US Army Research Office Grant number DAAAD19-01-1-0473This research was partially supported by Subcontract UTA03-031 to The University of Warwick under University of Texas at Austin’s prime National Science Foundation Grant #CCR-0205483Received February 2004Revised September 2004 and April 2005Accepted April 2005 by M. Leuschel and D. J. Cooke