Analysis and decomposition of active and reactive power spot price in deregulated electricity markets

Electricity markets have suffered important modifications in recent decades in many countries, in which a competition framework has been established with the aim of improving market efficiency and reducing energy prices. However, this new paradigm does not assure optimal solutions, as new constraints can be introduced in optimization processes that can affect the resulting prices. An example of this situation is the establishment of power purchase agreements between producers and consumers. A wide literature can be found regarding electricity markets. Some of this literature refers to the theory of spot prices and its application to them. This paper deals with the obtaining, decomposition and deduction of behavior rules of spot prices, and their influence on established contractual relationships in a deregulated market environment which allows power purchase agreements between consumers and producers. It is performed by a deterministic modeling of the complete generation-grid system. The influence of the existence of this kind of agreements on both total costs and spot prices is discussed.     

Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.     

Multi-elite guide hybrid differential evolution with simulated annealing technique for dynamic economic emission dispatch

This paper proposes an improved multi-objective differential evolutionary algorithm named multi-objective hybrid differential evolution with simulated annealing technique (MOHDE-SAT) to solve dynamic economic emission dispatch (DEED) problem. The proposed MOHDE-SAT integrates the orthogonal initialization method into the differential evolution, which enlarges the population diversity at the beginning of population evolution. In addition, modified mutation operator and archive retention mechanisms are used to control convergence rate, and simulated annealing technique and entropy diversity method are utilized to adaptively monitor the population diversity as the evolution proceeds, which can properly avoid the premature convergence problem. Furthermore, the MOHDE-SAT is applied on the thermal system with a heuristic constraint handling method, and obtains more desirable results in comparison to those alternatives established recently. The obtained results also reveal that the proposed MOHDE-SAT can provide a viable way for solving DEED problems.     

Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

我国两部制电价制度对天然气发电企业盈利能力的影响

上海、浙江和江苏等地陆续出台了两部制电价制度,以期解决天然气发电(以下简称气电)企业成本高、经营困难等问题。为了研究该电价制度对气电企业盈利能力的影响,在对比分析上述三地电价政策和实施效果的基础上,基于不同类型机组的三大经营指标(项目财务内部收益率、经济净现值、动态投资回收期),采用项目经济性分析模型探究了不同类型燃气电厂的经济性。研究结果表明:①现行两部制电价与单一制电价相比,电价水平小幅度下降,给企业经营带来了一定的冲击,但从长远看,则有利于形成可持续的发展机制;②两部制电价是各地政府经过充分调研和测算后根据该区具体情况制定的,在该政策下多数企业处于盈亏平衡点附近,综合条件优、管理水平高的企业能取得一定的盈利,反之则亏损;③当电量电价一定且大于盈亏平衡点时,企业效益随年利用小时数的增加而提升,反之则随年利用小时数的增加而降低。结论认为:①两部制电价能起到促进企业管理和技术水平提升,引导和鼓励电力投资的作用,符合我国电力体制改革的方向;②政策制定时应针对不同时期建成的项目加以区别对待,实现上网电价、天然气价格和供热蒸气价格的"三个联动";③应建立大数据平台,实行气网、电网联合调度;④发电企业应创新管理,降低电厂建设及维护成本,提升机组效率,降低气耗。     

SCADA系统在城市燃气供应中的应用

介绍了三级结构的SCADA系统各级站的硬件配置及功能，此SCADA系统适用于三级管理体制的城市燃气供应系统。     

基于需求响应调度容量上报策略博弈的电网多代理系统调度模式

负荷能够作为系统备用资源,通过需求响应平衡间歇性能源带来的系统功率波动。但是,由于调度工作量巨大,电网难以直接调度庞大且分散的负荷资源。因而提出基于多代理系统的负荷调度策略,建立了计及负荷违约的代理需求响应可调度容量上报博弈模型,同时构建了基于信任度的电网调度容量和调度量分配模型。代理根据自身负荷特点,向电网上报可调度容量,电网公司根据代理上报容量和信任度进行调度容量分配,并在实时调度时分配调度量,实现各个代理调度容量以及调度量的合理分配和电网调度费用低、代理收益高的目标。结果表明,该模型能够在计及负荷违约的条件下有效实现负荷需求响应调度容量和调度量的合理分配。     

基于改进形态滤波器和弧长差分序列的微电网电能质量扰动定位与识别

针对强噪声背景下微电网电能信号扰动定位和识别困难的问题,提出一种基于改进形态滤波器和弧长差分序列的扰动定位与识别方法。首先,将交替混合形态滤波器中的膨胀和腐蚀函数改进为均值膨胀和均值腐蚀函数,再对电能扰动信号进行滤波。然后,在分析扰动波形变化规律和三个典型扰动算例的基础上,定义并计算滤波后扰动信号的弧长差分序列。最后,利用弧长差分序列定位准确扰动时间,从弧长差分序列和滤波后信号中提取幅值特征和波峰特征,输入到已定义识别规则的扰动识别器,实现扰动识别。仿真试验和实际微电网数据试验结果表明,该方法能够精确定位和识别混入不同强度噪声的5种单一扰动和3种复合扰动,适用于实际微电网电能信号扰动的定位与识别。     

考虑污染物排放约束的传统电厂与虚拟电厂间环境经济调度模型

为有效实现分布式能源(distributed energy resource,DER)单元参与电力系统能源市场,深度挖掘负荷侧灵活供能潜力,首先建立虚拟电厂(virtual power plant,VPP)作为管理运行分布式能源的代理模型,并基于组件特性分析对虚拟电厂的外特性进行了量化;然后基于当前电力行业面临的经济环境热点问题,建立了考虑污染物排放约束的传统电厂(conventional power plant,CPP)和虚拟电厂间的环境经济调度(environmental economic dispatch,EED)二阶约束二阶规划(quadratically constraint quadratic programming,QCQP)模型;接着介绍了CPLEX优化引擎和YALMIP软件包的功能,并采用建模与求解解耦的方式来求解模型;最后对改进10机系统进行仿真计算,验证了所提模型的有效性和正确性。     

考虑需求响应的风电消纳模糊

随着智能电网的快速发展,将需求响应(demand response,DR)融入调度过程以协调风电和火电机组出力是目前的研究热点.首先利用需求响应对负荷曲线的优化作用及其对系统备用容量的等效作用,制定了分时电价和可中断负荷的容量成本;其次针对风电出力的不确定性和随机性,采用可信性测度理论对其进行模糊表示;然后将风电出力不确定性引入到旋转备用模糊约束中,给出了基于模糊机会约束规划(fuzzy chance constrained programming,FCCP)并考虑需求响应的经济调度模型;最后由改进引力搜索算法求解所给模型.算例分析表明所提模型能够有效应对风电出力不确定性,降低系统运行的总成本.