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.

Supply chain decisions and coordination in the presence of an imperfect spot market

This study considers a supply chain consisting of a commodity supplier and a final product manufacturer with uncertain demand.In addition to purchasing from the supplier through a forward contract,the manufacturer can adjust their inventory by trading the commodity in an online spot market after observing the actual demand.However,the spot market is imperfect in that transactions cannot be certainly realized and come with additional transaction costs.Furthermore,the spot price is volatile such that overly relying on the spot market is unwise.To investigate how the spot market affects the decisions and coordination in a supply chain,we develop a game-theoretical model incorporating spot trading.We derive the optimal ordering decision in a centralized supply chain,as well as the supplier's and manufacturer's equilibrium pricing and ordering decisions in a decentralized supply chain.The impact of the imperfect spot market on the optimal decisions and profits is analyzed.This study also demonstrates how the supply chain can be coordinated in the presence of an imperfect spot market.Finally,a numerical analysis is performed to examine the analytical results.Our results indicate that the spot market can generally improve the performance of the centralized supply chain and benefit the manufacturer in the decentralized one.However,it can be detrimental to the supplier.The supply chain can be coordinated by a revenue-sharing contract,and both parties'profits can be improved.Our findings suggest that the manufacturer could take advantage of the spot market,and the supplier should attempt to integrate or coordinate the supply chain to share the benefits of spot trading.

OPTIMAL POLICY WITH A TOTAL ORDER QUANTITY COMMITMENT CONTRACT IN THE PRESENCE OF A SPOT MARKET

In this paper, the optimal policy is considered when the buyer faces two supply sources： one is the contract supplier from which the buyer orders over a specific contract period （say, a year） at a pre-agreed price, and the other is the spot market. However, when ordering from the contract supplier, the buyer must fulfill a pre-determined total order quantity, or the so-called definite total order quantity commitment, over the whole contract period. In other words, the commitment secures the buyer a fixed price but obliges him/her a total order quantity over the contract period. Although the spot market gives the buyer more flexibility in terms of order quantities, its prices are volatile. Such a combination of contract and spot procurements is often observed in practice. Within the contract period, there are multiple sub-periods, during each of which the buyer reviews the inventory, issues an individual order, and uses the on-hand inventory to meet the random demand. Thus, in each （ordering） period, the buyer will weigh between the current known spot price （by procuring from the spot market） and a lower future price （by waiting while consuming the remaining commitment）. An optimal dual ordering policy is characterized for each period, depending on the on-hand inventory level, the spot price, and the remaining commitment quantity. The optimal policy in each period is also shown to be independent of the contract price. Through a numerical study, the inventory cost is demonstrated to be （1） insensitive to the contract price when the total commitment quantity is lower than the total expected demand over the contract period and （2） non-increasing in the variability of spot prices.

Value assessment of hydrogen-based electrical energy storage in view of electricity spot market

Hydrogen as an energy carrier represents one of the most promising carbon-free energy solutions.The ongoing development of power-to-gas(Pt G)technologies that supports large-scale utilization of hydrogen is therefore expected to support hydrogen economy with a final breakthrough.In this paper,the economic performance of a MW-sized hydrogen system,i.e.a composition of water electrolysis,hydrogen storage,and fuel cell combined heat and power plant(FCCHP),is assessed as an example of hydrogen-based bidirectional electrical energy storage(EES).The analysis is conducted in view of the Danish electricity spot market that has high price volatility due to its high share of wind power.An economic dispatch model is developed as a mixed-integer programming(MIP)problem to support the estimation of variable cost of such a system taking into account a good granularity of the technical details.Based on a projected technology improvement by 2020,sensitivity analysis is conducted to illustrate how much the hydrogen-based EES is sensitive to variations of the hydrogen price and the capacity of hydrogen storage.

Selective Learning for Strategic Bidding in Uniform Pricing Electricity Spot Market

In an electricity market,power producers’profits are determined by the market price instead of the regulated price.Therefore,the producers should be cautious in strategic bidding,for which prediction-based approaches are widely used and have been proved effective for many areas.However,in a uniform pricing market,the market environment is so complicated,which is primarily due to the complexity of the participants’interaction,that even the strategies based on machine learning algorithms,which are generally considered as outstanding nonlinear prediction methods,may sometimes lead to unsatisfactory results.Therefore,a selective learning scheme for strategic bidding is proposed to ensure greater effectiveness.The proposed scheme is based on an ensemble technique,where several machine learning algorithms serve as the underlying algorithms to predict the price and generate a bidding recommendation.As the clearing iteration progresses,the most fitting ones will be chosen to dominate the bidding strategy.Considering the characteristics of the electricity market,the prediction method used in the selective learning scheme is modified to achieve higher accuracy.Simulation studies are presented to demonstrate the effectiveness of the proposed scheme,which leads to more reasonable bidding behaviors and higher profits.

面向电力现货市场的独立储能经济性分析与容量补偿机制探索

新型储能技术的快速进步为提升电力系统灵活性提供了更多技术选择,也为构建竞争性灵活资源市场提供了条件。国外部分独立系统运营商为适应储能物理特性,在能量市场、辅助服务市场、容量市场、输电资产方面做了机制探索;国内一系列电力体制改革文件强调探索容量补偿机制以鼓励新型储能投资建设,但国家层面尚未出台针对新型储能的容量补偿政策。结合主流新型储能技术经济参数与国内典型地区现货市场价格曲线,测算了现货市场环境下各类新型储能经济性差异与未来趋势,并基于国内外容量补偿机制经验与研究成果,研究不同容量补偿机制情景下容量电价对提升新型储能经济性的作用。研究发现,以锂电池为代表的新型储能已开始显现相对于抽水蓄能的经济性,赋予新型储能独立市场地位,鼓励其参与电力现货市场,有助于降低新能源发电系统消纳成本。然而,目前新型储能参与电力现货市场仍面临阻碍,为此在容量补偿、现货与辅助服务市场建设等方面给出了政策建议。

考虑碳交易的电力现货市场出清多阶段优化模型研究

近年来,随着我国电力现货市场和碳市场的逐步完善,如何更好地实现电力现货市场和碳市场深度耦合,推进电碳市场向竞争市场发展已经成为一个新的研究重点。该文提出了一个考虑碳交易的电力现货市场出清多阶段优化模型,并对该模型下的电力现货市场均衡问题进行了分析。在模型的第一阶段,建立了市场机组碳配额分配模型;在第二阶段引入阶梯碳交易机制,结合各机组的碳配额,建立考虑电能量成本最小和阶梯碳交易成本最小的电力现货市场出清模型;在第三阶段,结合前两个阶段确定的各机组碳配额和中标信息,建立以电能量成本最小为目标的电价追踪模型和机组碳成本计算模型。最后将该文模型在改进的PJM5节点系统(Pennsylvania-New Jersey-Maryland 5-bus power grid)上实现,并从出清结果和市场均衡结果两个方面验证了模型的有效性。结果表明,该文所提模型能够实现市场出清经济目标与低碳目标之间的平衡,能够在不增加电碳耦合总成本的基础上实现最大的碳减排量,同时通过增强发电机组参与市场竞争的主观能动性,降低了用户侧用电成本。

适应新型电力系统的电力互替品市场——(二)商品形态及形成机理

当前的电力现货市场基础理论是在新能源占比极低情况下提出的,其所依据的“分时交易”假设无法适应新型电力系统新能源占比日渐趋高、调节需求日益增加的新情况。为此,文中舍弃“分时交易”的基本假设,将功率曲线作为有机整体进行交易,探讨商品形态及形成机理。首先,分析对比“分时交易”与系列论文提出的“整体交易”中商品的形态,揭示“分时交易”中电力商品在各时段同质的假设在实际中不能成立的根本原因。其次,从市场组织者角度出发,探讨电力互替品的性质与形成过程,指出电力除具备生产使用价值外,还具有平衡价值,并定义互替电量、调节电量分别对这两种价值进行表征与量化。进而,从市场主体角度出发,以电力互替品的形成成本最小为目标,提出市场主体自主优化形成电力互替品的方法。进一步指出,各主体还可互补聚合形成电力互替品,适应海量分散的新型市场主体进入市场。最后,算例从量、质、价三个方面展示电力互替品的形成过程,分析了影响电力互替品形成成本的关键因素。电力互替品的形成过程,正是市场主体从计划式的“被动提供灵活性”变为市场化的“主动提供灵活性”的过程,也正是系统调节能力的挖掘提升过程。

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

电力现货市场交易运营的未来重大需求与关键技术

中国正在全面开展电力现货市场建设,现货试点地区结合当前市场规则及电力系统现状构建了较为完善的现货市场运营支撑体系,支撑了当前电力现货市场有效运行。随着新能源占比逐步提升的新型电力系统构建及“双碳”目标国家战略的实施,现有的运营技术支撑体系将无法适应未来市场发展需要。文中在总结中国电力现货市场技术实践的基础上,分析了电力现货市场特征发生的变化及面临的技术挑战,探讨了未来在多元主体建模接入、市场出清算法、市场风险分析、可信交易环境、市场仿真等方面的关键技术,部分技术已经取得初步应用。

现货市场环境下考虑条件风险价值的风电场最优售电模型

随着我国电力市场的逐步开放,风电产业进入市场成为必然的发展趋势,风电场的售电决策和风险评估是其适应市场的关键。为根据风电场在现货市场环境中对风险和收益的不同偏好,提出相应的售电决策,使得收益最大化和风险最小化。提出了一种考虑条件风险价值的风电场最优售电双层优化模型。将风电场在现货市场中的报量和报价分别作为模型上下层的优化目标进行求解,考虑了预测偏差对售电计划的影响,并以偏差惩罚的形式并入目标函数,同时运用条件风险价值法来控制风电场出力的不确定性,得到风电场不同风险偏好下的报量报价曲线以及综合效用。最后,以某地区工程实际数据为例,利用所提模型就不同的风险系数和偏差价格系数对风电场在日前市场中的报量和报价进行了仿真,验证了所提模型的有效性与合理性。

溢出风险约束下省间省内两级电力现货市场协同出清方法

新能源的快速发展对电力市场机制提出了新的要求。为促进新能源消纳与保障电力供应,中国建立了省间和省内两级电力现货市场。然而,随着省间市场交易规模和占比的提升,各省电力供应间联系更为紧密,加剧了省内市场间的风险传递。首先,基于当前省间省内两级现货市场衔接机制分析了各省现货市场间的风险传递特征,进而引入溢出风险价值的概念以量化评估省间省内两级市场下的风险传递;其次,为抑制省间省内两级市场下的风险传递,基于两阶段随机优化理论,构建了溢出风险约束下的省间省内两级现货市场协同出清模型;进一步,考虑因各市场运营机构不同而带来的隐私保护需求,建立了基于交替方向乘子法(ADMM)的省间省内两级现货市场协同出清模型求解方法;最后,通过算例分析验证了所提出的市场出清模型与方法在抑制省间省内两级市场协同下风险传递中的有效作用。

考虑碳交易下虚拟电厂参与现货市场竞价和调度策略

以虚拟电厂参与电力现货市场竞争的博弈过程为研究对象,求解以虚拟电厂总收益最大为目标的虚拟电厂参与现货市场的最优购、售电策略;并在日前市场成交电量的基础上,设计以偏差考核成本最小为目标的虚拟电厂参加实时市场的优化调度策略。最后通过算例验证了售电公司采用虚拟电厂聚合方式能够通过对分布式能源调度控制来增加在购售电决策时的灵活性,从而提高自身运营收益,为售电公司组合资源提供了技术支撑。

考虑风电出力和电价不确定性的水风联合现货市场竞价策略

以风电为代表的新能源参与现货市场已是大势所趋,但出力不确定性导致其市场竞争力较弱,而电价的不确定性又进一步增大了其承担的收益风险。联合具有灵活调节能力的水电是有效的解决途径,而制定符合决策者风险意愿的竞价策略则是其中亟须解决的关键问题。为此,从价格接受者角度提出了水电联合风电参与现货市场的竞价模型。模型中采用笛卡尔积组合后的典型场景集描述风电出力、市场电价等多种不确定性,采用条件风险价值衡量不确定性导致的市场风险,并以风险因子作为决策者风险偏好纳入决策过程。通过引入0/1整数变量,将模型中的非线性函数转换为混合整数线性规划模型予以求解。以中国西南某省梯级水电站和风电场为背景,验证了模型的有效性,并进一步分析了风险偏好对竞价决策的影响。

备用与现货电能量市场模型衔接机制研究

现货电能量市场与备用市场在市场组织与出清模型上衔接紧密,为研究不同的衔接机制对总发电成本、能量备用市场价格等市场绩效指标的影响,建立日前电能量备用联合出清模型,并依据出清次序和机组组合阶段目标函数成本项这2个划分标准来建立4种顺次出清模型。基于IEEE 118节点系统开展仿真,研究分析不同衔接机制下的有关电力市场绩效指标及形成差异的原因,并通过改变系统参数与边界条件,研究不同衔接机制下市场出清的可行域。结果表明,联合出清模式的总发电成本、市场电价等绩效指标更优,可以更好地调用系统灵活资源,同时还具有最大的出清可行区间。能量优先出清同时在机组组合综合考虑备用成本的顺次模式,在总发电成本、市场电价等绩效指标以及出清可行域上仅次于联合出清模式。最后基于仿真及理论分析结果给出了在备用市场建设初期,宜采用“先能量后备用,能量出清结果作为备用市场出清边界条件,机组组合考虑备用成本”的顺次出清模式,以及长期转向联合模式的建设方案。

基于多种交易方式的省间省内现货市场双层出清模型

新能源比例不断提升,省间消纳需求不断增加,构建满足全局资源优化运行的省间市场是促进市场效率提升的关键。文中基于多种块交易及小时交易的时间耦合关系,建立了省间省内两级现货市场出清模型。首先,构建了包含普通小时交易、灵活小时交易、常规块交易、可移动式块交易和扩展链接式块交易多种交易方式的混合整数线性规划模型。其次,为解决省间市场主体较多、块交易时间耦合复杂带来的出清难度大的问题,提出了基于省内出清结果的参与省间市场主体的筛选机制,进一步实现基于各省筛选出主体的省间市场出清,通过融合省间、省内出清结果形成最终中标结果。最后,通过多区域互联的IEEE RTS-96系统算例验证该模型的合理性及其作用效果。结果表明,相较于各省单独出清,省间省内两级市场出清提升了整体社会福利。所提方法在提高求解效率的同时,尽量逼近省间整体出清的全局最优解,实现了社会福利最大化。

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。

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。