计及激励型需求响应的热电互联虚拟电厂优化调度

目前，对多能量虚拟电厂在多种不确定性条件下的优化调度问题研究存在不足。针对这些不确定性问题，提出计及激励型需求响应的热电互联虚拟电厂优化调度模型。首先，针对分布式能源发电的不确定性，根据不同时刻风速、光照强度相关性，利用Student-T Copula函数得到风光发电场景；其次，综合考虑电热相关约束，建立以虚拟电厂效益最大为目标函数的优化调度模型；然后，采用改进型多元宇宙算法对所提出的模型进行优化求解；最后，通过算例仿真，验证所提出的优化调度模型能够平缓负荷曲线，减少环境污染，提高虚拟电厂整体经济效益。     

基于分时电价的含风-光-气-储虚拟电厂经济调度

构建基于分时电价的含风-光-气-储虚拟电厂经济调度模型,调度模型以虚拟电厂的效益最大为目标函数,并采用罚函数法将约束条件引入到目标函数中,采用新兴启发式的布谷鸟搜索算法对模型进行求解,得到虚拟电厂各设备出力。将风电和光伏出力的不确定性表示为一个具有零均值、呈正态分布的预测误差,并分析正态分布系数对误差和虚拟电厂的影响。对比分析分时电价、储能设备等对虚拟电厂的影响,仿真结果验证所提模型及算法的有效性,为虚拟电厂的经济调度提供新的方法和途径。     

基于自律分散控制的多区域虚拟电厂优化调度策略

鉴于分布式能源的日益增长给电力系统的安全稳定运行带来了一定的挑战,即基于自律分散控制研究了多区域虚拟电厂的优化调度问题。基于自律分散控制系统及一致性算法的基本概念搭建多区域虚拟电厂的结构模型,并建立多区域虚拟电厂自律分散控制策略;在此基础上,以最大化虚拟电厂自身收益为目标建立日前优化调度模型,并采用功率调节成本作为一致性变量建立多区域虚拟电厂日内优化调度模型;最后,通过算例验证了模型及策略的有效性。     

考虑风光不确定性的分布式能源集成虚拟电厂收益-风险均衡模型

文章将风电场、光伏发电、小水电站等分布式能源聚合为虚拟电厂,并考虑价格型需求响应负荷及激励型需求响应负荷,以运营收益最大化为目标,综合考虑负荷供需平衡约束、机组运行约束以及旋转备用约束等,构建虚拟电厂常规调度优化模型,利用条件风险价值法(CVaR)和鲁棒随机优化理论构造虚拟电厂风险规避优化模型。最后,以独立微电网作为实例对象,验证了模型能够在最大化经济效益的同时,最大化利用清洁能源,合理控制运营风险,实现虚拟电厂最优化运营。     

电厂SO2排放对上海世博园区的影响分析

燃煤电厂烟囱排放是上海大气中SO2的主要来源之一，因此在分析上海大气中SO2浓度时必须考虑电厂的影响。作为计算大气扩散的经典模型，高斯扩散模型一直被人们广泛地利用。利用高斯扩散模型分析了上海各大电厂对世博园区SO2浓度分布的影响，可为上海世博园区的环保工作提供参考。     

计及厂用电不平衡状态感知与碳减排的多能源储能优化配置模型

为解决燃气电厂内厂用电不平衡引起的资源浪费、碳排放量高等问题,实现多种负荷与储能设备之间的协调运行,提出了一种计及厂用电不平衡状态感知与碳减排的多能源储能优化配置模型。首先,对厂内多种负荷用能需求的不确定性进行分析,在此基础上建立燃气电厂的厂用电不平衡状态感知模型;然后,以多能源储能系统综合成本最小、碳排放量最小、天然气利用效率最大为目标,构建了燃气电厂多能源储能优化配置模型,并进行求解;最后,通过算例仿真验证提出的多能源储能优化配置模型能够减少天然气资源浪费,提高燃气电厂的经济性和碳减排能力。     

浅谈智能电厂规划建设

近年来，电厂智能化建设进入新的阶段。为了使大家初步了解智能电厂，通过梳理智能电厂的概念、体系架构，对智能电厂的建设思路提出建议，并对一体化信息平台进行介绍。从纵向层级、横向全生命周期和全生产流程三条主线进行分析，指出智能电厂不仅由智能化的设备组成，同时还需要与IT技术、信息化管理工具、先进算法和管理理念相结合。智能电厂建设是一项复杂的系统工程，必须以科学和务实的态度对待，并结合企业的内外部环境，有计划、有步骤、有目标地进行科学决策，分阶段实施，使企业的经营目标、管理思想能真正落地，从而能够提高生产效率，降低企业综合成本，提升企业市场应变能力。     

基于双层合作博弈的虚拟电厂滚动优化调度研究

为了应对当下高比例可再生能源和大规模电动汽车的接入给虚拟电厂双侧运行带来的挑战,提出了一种改进的Shapley值分配方法用于解决联盟收益分配问题。以虚拟电厂为中介,分别构建了以联盟收益最大化为目标的“需”侧用户-虚拟电厂联盟和“供”侧虚拟电厂-主动配电网联盟,再将双侧的合作博弈模型联系起来,构成基于双层合作博弈的虚拟电厂滚动优化调度模型。利用改进的Shapley值进行联盟收益再分配,从而达到用户、虚拟电厂和主动配电网三方主体收益的最大化,最后进行实验验证。结果表明：该模型使三方主体收益相较于未合作博弈和任一单层合作博弈分别提高了15.64%,6.95%和6.949%,提高了系统运行的经济性。     

数据驱动的燃煤电厂脱硫系统多目标优化

本文利用某燃煤电厂湿法烟气脱硫系统的数据对比随机森林、极致梯度提升、支持向量回归、深度神经网络、长短时记忆神经网络五种模型的预测效果,结果显示长短时记忆神经网络的效果优于其它四种模型。基于该模型结合多目标粒子群优化算法,进一步对脱硫系统相关参数开展多目标优化,优化结果验证了本文提出的数据驱动的脱硫系统多目标优化模型的有效性。     

电站锅炉全局优化智能配煤模型的建立及系统开发

建立了应用于电站锅炉的全局优化智能配煤模型.该模型在多目标优化数学模型的框架下,运用模糊数学方法构建目标函数和遗传算法(GA)寻优,利用神经网络实现混煤燃烧特性的预测.为提高GA的寻优性能,应用正交设计法和自适应罚函数对简单GA进行改进,建立了基于自适应罚函数的正交遗传算法优化配煤模型.在此基础上,开发了智能配煤系统并应用于某电厂优化配煤,提高了电厂配煤的自动化和智能化水平,具有较好的应用前景和示范作用.     

基于有偏t分布ARIVIAX模型的短期电价预测

基于正态分布假设的时间序列分析模型不能有效地处理电价的有偏厚尾性,在对电力市场现货电价的影响因素和波动规律综合分析的基础上,提出了一种基于有偏学生t分布ARMAX模型的短期电价预测方法。该方法可同时考虑电价分布的有偏厚尾性、多重周期性及其与负荷之间的非线性相关性。对PJM电力市场历史数据的算例研究表明,该方法计算量小,待估参数少。     

基于项目群的电网科技项目评价方法研究

随着电网投资精细化的发展,电网公司投资在兼顾可靠性的同时,更加注重投资效益及效果。对于科技项目投资而言,完善科技项目后评价阶段的价值评价体系和方法对于提高科技项目投资效益具有重大意义。文章分析科技项目的特点以及项目群的成果价值表现,构建指标计算方法,选择了基于分位数统计法确定的评价指标隶属度标准,对电网科技项目实施效果进行评价。     

基于电价波动率的现货电价风险度量研究

风险度量因子的选取是风险度量的核心工作之一,统计性质好的指标通常能降低建模复杂度,提高精度。根据电价序列的特征及电价风险度量模型的特点,提出以电价波动率替代电价作为风险度量因子,避开电价序列的非平稳性,建立GARCH-VaR模型用于现货电价风险度量,以北欧电力市场的电价风险度量为例,对模型的可行性和有效性进行检验,并将所提出的电价风险度量方法与电价波动率正态分布法、电价ARMA-GARCH模型度量的电价风险进行比较。结果表明,所提方法不仅能有效降低电价风险度量的模型复杂度,还可提高风险度量的准确性。     

Market and patent analysis of commercializing biohydrogen technology

In the face of world-wide energy price fluctuation, energy supply security, and the energy crisis, it becomes an urgent issue to search for alternative methods for energy generation and to close the gap between the supply and demand of global energy. The current method of energy supply in Taiwan is through a centralized electronic power system, which is generated by a few large electronic power plants. Hydrogen fuel cell (HFC) has a characteristic of de-centralized electronic power supply system, which provides electronic power more reliably, efficiently and economically. Based on the output of Taiwan’s sewage, sludge, kitchen waste and biohydrogen technology, the preliminary market for biohydrogen fuel cell (BHFC) is positioning itself toward the supply of public electronic power within the housing communities. Based on the patent analysis of BHFC, this study finds that Taiwan pays more attention to the front-end manufacturing of raw materials and emphasizes the development of biohydrogen technology, while America and Japan mainly pay more attentions to rear-end product application and emphasize the application of hydrogen and fuel cells by integrating industrial opinions. Based on the market analysis of BHFC, this study finds that the product attributes, consumers’ characteristics and external variables strongly influence consumer’s purchase intention of biohydrogen technology products.     

Inefficient and opaque price formation in the Japan Electric Power Exchange

This study examines whether the spot prices in the Japan Electric Power Exchange are efficiently formed from April 3, 2006, to March 31, 2012, using the conventional and rank-based variance-ratio tests. The results seem to reject the efficient market hypothesis in the market. Moreover, by applying Granger-causality tests, this paper investigates whether the power price is determined from the information of primary energy and exchange markets that directly affect the cost of power generation. The results indicate no Granger-causality from the prices of oil and gas and the exchange rate to the price of electricity. Finally, this paper discusses the factors that lead to inefficient and mysterious price formation.     

可再生能源绿证价格季节性测算方法研究

  目的  在市场化交易模式消纳可再生能源发电的发展趋势下,“市场电价+绿证收入”将成为未来可再生能源发电企业的主要经营模式。以可再生能源发电参与现货电能量市场为研究大背景,对可再生能源绿色电力证书的价格进行研究。  方法  基于现货电能量市场的优化出清模型,应用可再生能源全生命周期成本测算理论,以满足可再生能源发电企业的内部收益为目的,建立了绿证-电能量市场耦合的优化模型,并结合可再生能源季节性出力特性,提出了可再生能源绿证价格季节性曲线及其波动区间的仿真和测算方法。  结果  不同类型的可再生能源绿证价格不同,不同类型的可再生能源绿证价格的气候相关性亦不相同。  结论  绿证价格的科学合理测算不仅可以帮助可再生能源发电企业进行收益评估和制定更为准确的投资决策,还为电力市场主体与交易中心提供相关决策支持。     

Is the Merchant Power Producer a broken model?

Deregulated energy markets were founded on the Merchant Power Producer, a stand-alone generator that sold its production to the spot and short-term forward markets, underpinned by long-dated project finance. The initial enthusiasm that existed for investment in existing and new merchant power plant capacity shortly after power system deregulation has progressively dissipated, following an excess entry result. In this article, we demonstrate why this has become a global trend. Using debt-sizing parameters typically used by project banks, we model a benchmark plant, then re-simulate its performance using live energy market price data and find that such financings are no longer feasible in the absence of long-term Power Purchase Agreements.     

Electric power grid interconnections in Northeast Asia: A quantitative analysis of opportunities and challenges

Power grid interconnection has gained attention in Northeast Asia (NEA) as a means to build an economically efficient power system and to effectively utilize renewable energy, such as wind and solar resources in the Gobi Desert and hydro resources in Eastern Russia.In order to quantify the potential economic and environmental benefits from connecting power grids and developing renewables in NEA, we build an NEA-wide multi-region power system model using linear programming techniques. Our analysis considers power system characteristics, such as the seasonal and daily electric load curves of the various NEA economies.Compared to a “no grid extension” scenario, increased access to renewables contributes significantly to emissions reductions and fuel cost savings. However, the results imply modest benefits in lowering total cost because of the large initial investments needed in developing the renewables and the transmission lines. These limited total cost savings are likely to pose an implementation challenge for NEA grid interconnections. Our results also suggest that grid interconnections become more economically attractive in higher fuel price or lower initial cost situations. The relevant planning organizations should carefully consider the initial cost and future fuel price trends when considering how to interconnect power girds in an economical manner.     

基于多周期GARCH-M模型的短期电价预测

电价的分布特性是电力市场风险管理和电力金融产品定价的重要依据。建立了一个采用虚拟变量和正弦函数来刻画现货电价序列多周期性特征的GARCH-M模型。该模型易于定阶、待估参数少,可同时处理电价序列的趋势变化、多周期、异方差及其与负荷之间的非线性相关性,具有一定的实用价值。对PJM电力市场历史数据的分析表明,电价分布的异方差和负荷的平方对电价均值具有显著的影响,电价序列具有周、半月、月、季、半年等多重周期和明显的波动集聚性。     

Managing volumetric risk of long-term power purchase agreements

A negative dependence between wind power production and electricity spot price exists. This is an important fact to consider for risk management of long-term power purchase agreements (PPAs). In this study we investigate this dependence by constructing a joint model using constant as well as time-varying copulas. We propose to use score-driven models as marginal model for the spot price of electricity as these are more robust to extreme events compared to ARMA–GARCH models. We apply the new model to pricing and risk management of PPAs and benchmark it against the ARMA–GARCH specification. Our comparison shows that the score-driven model results in a statistically significant improvement of predicting the Value-at-Risk (VaR), which is of high importance for risk management of long-term PPAs. Further, comparing constant and time–varying copulas we find that all time-varying copulas are significantly better than their constant counterparts at predicting the VaR, hence time–varying copulas should be used in risk management of PPAs.