The Spillover Effect between Futures and Spot Price of Agricultural Products:A Case Study of Soybean Products of China

Taking soybean products as an example and using the daily price data of 2007-2015,this paper established the error correction model and BEKK-GARCH model,and made an empirical study on the spillover effect of futures and spot price of agricultural products of China. According to this study,there were mean spillover effect and two-way volatility spillover effect in futures and spot price of soybean,soybean oil,and soybean meal; soybean futures prices significantly guided the spot price; in the price linkage between the types,the price relationship between the soybean meal and soybean was closer than between the soybean oil and soybean.

Investigation on Active and Reactive Combined Spot Price Integrated with Wind Farm

An active and reactive combined spot price model and the corresponding algorithm are introduced in this paper based on the theory of optimal power flow. Different from the traditional economic dispatch in the field of spot price, the objective function is to minimize generation costs based on pricing reactive power. Then considering the characteristics of wind turbines, processing methods of wind farms in optimal power flow is discussed. Finally, the feasibility of the model and the algorithm is verified through the simulation results of IEEE 30 system.

An Application of Decision Trees Algorithm to Project Hourly Electricity Spot Price as Support for Decision Making on Electricity Trading in Brazil

Estimating the price of a financial asset or any tradable product is a complex task that depends on the availability of a reasonable amount of data samples. In the Brazilian electricity market environment, where spot prices are centrally calculated by computational models, the projection of hourly energy prices at the spot market is essential for decision-making, and with the particularities of this sector, this task becomes even more complex due to the stochastic behavior of some variables, such as the inflow to hydroelectric power plants and the correlation between variables that affect electricity generation, traditional statistical techniques of time series forecasting present an additional complexity when one tries to project scenarios of spot prices on different time horizons. To address these complexities of traditional forecasting methods, this study presents a new approach based on Machine Learning methodology applied to the electricity spot prices forecasting process. The model’s Learning Base is obtained from public information provided by the Brazilian official computational models: NEWAVE, DECOMP, and DESSEM. The application of the methodology to real cases, using back-testing with actual information from the Brazilian electricity sector demonstrates that the research is promising, as the adherence of the projections with the realized values is significant.

The Empirical Analysis of the Dynamic Prices Relationship between Cotton Spot Market and Futures Market in Xinjiang

The thesis analyzes the causal relationship between the cotton spot,and the tendency and impact of prices of futures markets in Xinjiang by using ADF test,co-integration analysis,Granger causality test and other econometric methods in order to discuss the interacted relationship between futures market prices of cotton and spot market prices since the futures of cotton in Xinjiang go public.The results of empirical analysis show that the spot market prices of cotton and the futures market prices in Xinjiang fluctuate prominently in the short run and tend to counterpoise in the long run;the futures market of cotton plays the role of leading the spot market prices of cotton in Xinjiang,while the spot market prices of cotton in Xinjiang impacts little on the futures market prices.The corresponding countermeasures are put forward.The government should continuously perfect the construction of the futures market of cotton in Xinjiang,so as to exert the function of price discovery and the function of hedging,and promote the development of cotton industry in Xinjiang.

Nonlinearities between oil spot and futures markets： Evidence from intraday data

This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market, both in their means and in their conditional volatilities, to investigate whether the association is linear or not. The novelty of this work is based on intraday data from both markets. The empirical findings indicate the presence of nonlinearities both in means and conditional volatilities. Moreover, non-linear causality estimations both in means and in volatilities reveal the presence of bi-directional causality, a fact that provides additional support to the hypothesis that both markets are driven by the same information sets.

Theory summary on price discovery function of futures market

Price discovery is the basic function of futures market, and whether the futures market has the function of price discovery is an important research field for scholars both at home and abroad. This paper classifies the test methods and models on a basis of previous research, and introduces the applicable premise of research methods and models as well as the major research achievements of scholars at home and abroad, and also reviews the shortcomings of test methods and models.

The interactions between Chinese local corn and WTI crude oil prices:an empirical analysis

This paper investigates the relationship between China’s fuel ethanol promotion plan and food security based on the interactions between the crude oil market, the fuel ethanol market and the grain market. Based on the US West Texas Intermediate(WTI) crude oil spot price and Chinese corn prices from January 2008 to May 2018, this paper applies Granger causality testing and a generalized impulse response function to explore the relationship between world crude oil prices and Chinese corn prices. The results show that crude oil prices are not the Granger cause of China’s corn prices, but changes in world crude oil prices will have a long-term positive impact on Chinese corn prices. Therefore, the Chinese government should pay attention to changes in crude oil prices when promoting fuel ethanol. Considering the conduction e ect between fuel ethanol and the food market, the government should also take some measures to ensure food security.

Comparative Analysis of Discovery Function of Cotton Future Price among Different Regions——A Case Study of Xinjiang

Through comparative analysis, We research the relationship between cotton future price and cotton spot price in different regions, in order to formulate corresponding strategies in different regions under the new situation. We use ADF unit root test, E-G two-step cointegration test, Granger causality test, and other research methods in Eviews 5.0 statistical software, to empirically study the relationship between the cotton future price and cotton spot price in Xinjiang, the relationship between the cotton future price and cotton spot price in China. The results show that there is a long-term relationship between the cotton future price and cotton spot price in Xinjiang, between the cotton future price and cotton spot price in China; the cotton future price plays unidirectional role in guiding cotton spot price in Xinjiang and cotton spot price in China. The discovery function of cotton future price plays much greater role in the cotton market of China than in the cotton market of Xinjiang.

电碳耦合对煤电机组现货市场结算电价影响分析模型

煤电行业二氧化碳排放量占比最多,首先被纳入了全国性碳市场,而碳排放成本又对煤电现货市场结算电价造成一定程度的影响。基于此,构建了现货市场下不考虑碳排放成本的煤电机组竞价调度模型,并进行了模拟分析;继而构建了考虑碳排放成本的煤电机组竞价模型;再以广东省为例,模拟了煤电机组在“有无风光出力”“不同碳市场”情景下煤电机组现货市场报价及出清情况的变化。结果显示,随着碳市场的逐步完善,碳价和配额总量进一步收紧,煤电机组报价逐渐升高,现货市场结算电价也随之提高,夏季有风有光情景下轻度、中度、重度碳市场的平均出清电价分别为0.1607元/(kW·h)、0.1863元/(kW·h)、0.2461元/(kW·h),较未引入碳市场时分别增加了0.18%、16.14%、53.41%。

不同市场环境下贵州省抽水蓄能电站的电价形成机制研究

在梳理我国抽水蓄能电站电价政策演变历程的基础上,针对贵州省电力市场的发展方向,制定了针对贵州省乌江流域抽水蓄能电站在不同电力市场环境下的电价形成机制,分别对现货市场形成前后电力市场环境下的电量电价和容量电价进行测算。结果表明,在不完善的电力市场环境下电站上网电价为0.351 5元/(kW·h),抽水电价为0.263 6元/(kW·h),站点容量电价为668.50~771.70元/(kW·a);在较完善的电力市场环境下峰谷电价差为0.331~0.504元/(kW·h),站点容量电价为586.17~689.37元/(kW·a),可认为现阶段未形成现货市场的情况下严格执行两部制电价是合理有效的,未来形成现货市场后将由市场竞争生成电价。

基于深度强化学习的电力市场量价组合竞价策略

目前国内电力市场普遍采用“优先消纳、保障收购”的市场机制应对新能源消纳需求,因此传统能源将面对具有高不确定性的净负荷市场情形进行竞争,并通过策略报价使自身收益最大化。然而,现有策略报价的相关研究仅考虑了发电商报价而不报量、且忽略了竞争对手博弈主动性,导致难以反映策略发电商真实的市场竞价行为。对此,提出了一种基于深度强化学习的电力市场量价组合竞价策略分析方法。首先,针对现有策略竞价研究仅报价不报量的缺陷,研究了考虑量价组合申报的发电商双层双线性竞价模型。然后,为了考虑竞争对手行为的不确定性,构建了基于K-Medoids聚类方法与深度神经网络的发电商典型报价与净负荷间的概率映射,旨在为策略发电商提供贴近真实市场的竞价环境。最后,为高效求解策略报价的双层双线性模型,探讨了考虑不完全信息博弈与净负荷不确定性的深度确定性策略梯度强化学习方法。算例研究结果验证了所提量价组合申报模型的有效性以及所提方法应对电力市场净负荷和对手行为变化的鲁棒性,并能够提高发电商的竞价收益。

基于藤Copula理论的海上风电建模及电力市场运行分析

海上风电因具有更高的发电利用小时数,将成为中国实现“碳中和·碳达峰”的重要技术选项。随着海上风电装机容量的不断提升,其出力的间歇性、波动性将对电力系统的安全稳定和电力市场的经济运行造成显著影响。为刻画不同站点间风速的相关性,基于藤Copula理论对海上风电的出力进行建模,并利用C藤Copula函数构建多风电场出力的联合分布模型。在此基础上,提出基于共识聚类的电力市场典型阻塞场景构建方法,并采用简化的中国广东省电网架构数据开展算例仿真计算,对大规模海上风电并网前后电力系统的发电结构、碳排放量、市场电价等关键指标的变化进行实证分析。

新能源入市风险下计及影响层的现货限价自适模型

在现货市场起步阶段,普遍采用扁平化限价标准以防范极端价格风险,而随着新型电力系统建设提速推动新能源规模化入市,现货价格受间歇性出力的影响面愈加扩大,新能源入市风险增加,限价设计须进一步考虑常规机组收益、新能源装机比例以及负荷需求量等。因此,综合考虑与现货价格有强联动的影响因素,选取主要因子构成限价影响层,并在改进传统价格管制模型的基础上引入影响因子及系列模型的自适系数,提出新能源入市风险下计及多因子影响层的现货市场限价自适模型,仿真结果表明:模型能够实现不同需求场景下对现货价格的动态跟踪以保障系统安全稳定。

水电主导现货市场优化出清研究

针对传统以购电经济性为唯一目标的市场出清中梯级水电一边缺水一边弃水的水-电不匹配问题,本研究结合梯级水电运行特性,提出一种水力、电力、价格3因素耦合的出清方法。首先,梳理了梯级水电出清后缺水和弃水两种水-电不匹配的工况,提出用水-电耦合度指标来度量水量与电量匹配的程度,并给出了水-电耦合度的计算方法。其次,建立了适用于水电主导电力市场的水力、电力和价格耦合出清模型,设计了购电成本最小化和水-电耦合度最大化两个目标函数。为了提高模型求解效率,提出模型结构分层、搜索空间缩减和计算时段合并的模型求解综合降维策略,并基于价格排序-粒子群耦合优化算法实现模型求解。最后,以四川省串并混联开发的“3梯8站”组成的虚拟市场进行日前模拟出清。结果表明:与传统以经济性为唯一目标的出清模型相比,水-电-价耦合出清模型的购电费用不变,但水-电耦合度提高了1.57%,证明水-电耦合度最大化目标的加入不会增加购电成本,但对减少出力不足、提升出清结果的可执行率和降低弃水都有显著成效;所提求解策略降低了模型复杂度,提高了求解效率,为解决梯级水电现货市场出清中水-电-价的不耦合问题提供了新思路。

现货市场中实现保供目标的容量补偿定价方法

为解决电力现货市场环境下的电力系统装机充裕度不足的问题,提出一种实现电力系统保供目标的容量补偿定价方法。首先,根据保供要求的电力系统可靠性标准,构建基于内部收益率评估的机组投资、退役决策模型;其次,通过“机组电能市场收入评估、机组容量补偿收入评估、投资退役决策”的迭代,确定目标年份市场中分类型机组的预期装机;然后,计算目标年份的可靠性指标,根据可靠性指标与标准的偏差调整容量补偿价格,使得发电充裕度能够满足目标年份系统的可靠性标准。算例结果表明,所提定价方法能够在保证电力系统可靠性的基础上,降低电力用户的综合购电成本。

电力现货市场阻塞费用结算机制分析

节点边际电价价格机制下,试点省份阻塞费用结算机制存在差异,需进行系统的分析。为此,首先从问题的本质出发,梳理了阻塞相关术语的内涵;然后,基于统一的内涵,对比分析了典型现货试点省份阻塞费用结算机制关键异同点;最后,对用户统一结算点电价计算、中长期合约阻塞费收取、阻塞盈余分摊等问题进行分析,提出了相关建议。

省间电力现货交易优化设计与定价机制

在“碳达峰·碳中和”的目标驱动下,受新能源地理分布与随机性影响,以跨区域交易为媒介的区域间电能与灵活性互济重要性凸显。目前,中国正处于构建全国统一电力市场体系的关键阶段,需要有效的市场机制来管理省间电力现货交易。基于上述背景,设计了一种不依赖于跨区域投标者的省间电力现货交易方法。首先,提出了基于报价区的市场出清模型,采用分区边际定价的方法计算每个报价区的结算价格;然后,基于等效双边配对方法,按潮流贡献计算得到各区域间交易所需承担的输电费用;最后,采用算例验证了所提方法的有效性。与已有方法相比,所提方法在不依赖于跨区域投标者的前提下完成了跨区跨省电力交易,充分利用了输电线路容量,且市场出清过程中保护了各区域内部网架信息隐私。

现货电价条件下火力发电厂辅机优化调度技术应用

基于次日现货电价曲线波动情况,兼顾机组运行需要、辅机制备原料能力和仓储容量等多种因素,开发火力发电厂辅机优化调度专用软件,提前1 d对可错时运行辅机的启停计划进行自动规划。理论分析和软件功能测试结果表明:对部分辅机设备优化调度后,既可以提高火力发电厂的售电收益,又有利于在用电低谷时段消纳部分电能,提高电网运行的稳定性,具有良好的经济效益和社会效益。

电力现货市场下山东电化学储能电站净收益分析

总结山东电力现货市场下电化学储能电站的相关政策。通过分析储能电站的各项收益、费用,得出电化学储能电站净收益的计算公式。通过分析电站净收益与上网电量、度电价差、综合效率、采用“两充两放”运行策略的关系,研究典型工况下临界点度电价差。通过山东某在运100 MW/200 MW·h电化学储能电站案例分析验证了净收益计算公式的有效性。研究结果可以为优化电站运行策略、提高电站收益水平提供参考。