Analytical Framework for Market-oriented DSR Flexibility Integration and Management

Integration and management of the flexibility of Demand Side Resources (DSR) in today’s energy systems plays a significant role in building up a sustainable society. However, the challenges of understanding, predicating and handling the uncertainties associated this subject to a great extent hamper its development. In this paper, an analytical framework based on a multi-portfolio setup in presence of a deregulated power market is proposed to address such challenges by adopting the thinking in modern portfolio theory (MPT). A Numerical example that targets on analyzing the risk and return for various flexibility pricing strategies are presented to illustrate some features of the framework.

Market based framework for multiple AUVs cooperation

A“Market” based framework for multiple AUVs team is introduced in this paper.It is a distributed meta-level task allocation framwork. The formulation and the basic concepts of the “Market” such as “goods” and “price” are discussed first, then the basic algorithm of the “auction”. The loosely coupled v-MDTSP tasks are considered as an example of the task allocation mission. A multiple AUV team controller and a detailed algorithm are developed for such applications. The simulation results show that the controller has the advantages such as robustness and low complexity and it can achieve better optimization results than the classical central controller (such as GA) in some tasks. And the comparison of two different local solvers also implies that we should get the reasonable task allocation even not using the high quality algorithm, which can considerably decrease the cooperation computation.

Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive data.Data security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing mechanisms.In this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary market.Moreover,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and users.Specifically,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic bidding.The incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading scenario.With temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation strategies.Furthermore,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

Auction mechanism design of the Chinese national carbon market for carbon neutralization

The carbon market auction mechanism is an important policy tool for carbon pricing and a key mechanism that supports carbon emission neutralization,especially for China.A few systematic studies exist on China’s carbon market auction mechanism.This article focuses on the five auction mechanisms in Chinese pilot emission trading schemes(ETS),reviews the structures and bidding situation of the five-pilot auction mechanism,extracts the similarities,and analyzes their different features,such as auction mode,bidding scale,participants,pricing mode,auction frequency,and so on.This study conducts an in-depth analysis of the carbon allowance auction mechanism in the Guangdong pilot ETS of China,including its development and the evolution of the key elements,its operational effects,and related disputes.Finally,this study puts forward the trend forecast and suggestions for the Chinese allowance auction mechanism,such as the time window of launching national allowance auctions,the most likely auction mode,carbon pricing,and bidding revenue management.Carbon pricing by auction is the most powerful policy tool for addressing carbon emissions reduction and implementing the Glasgow Climate Pact.

A Few Notes on Auctions:The Boom in the Asymmetric Art Auction Market

The art market,following the example of financial markets,is divided into a primary market,where works are traded directly from artists,and a secondary market that is mainly the auction market.COVID-19 and galloping inflation have influenced the creation of a bull market in artwork.The high incomes of some buyers and inflation have influenced the emergence of the so-called“glittery”art market.Works by neglected artists have“very much taken on a life of their own”:fantasy art,works by young poster artists,casting“nightmares”-have been selling well for more than a year.People terrified of inflation are putting their money“in works of art”.The auction market dominates the primary market because anonymity makes it easier to enter the art market.The gallery market does not guarantee this anonymity.Very often,the auction market for works of art is used for money laundering.The purpose of this paper is to show that auction mechanisms are a good tool for the efficient allocation of goods and money in an era of galloping inflation,including non-standard objects such as works of art.These mechanisms,due to the information asymmetry,often lead to the generation of all kinds of pathologies and the increasing incidence of the phenomenon known as the winner’s curse.

Chinese “Red” Oil Paintings Sold Well in Auction Market

Chinese"red"art,which refer to artworks depicting revolutionary subjects,have seen excellent performance in the auction market since the beginning of this year.In particular,the celebration of the60th anniversary of the People’s Republic of China gave a new push to its price rise.

新时代中国供销合作社综合改革研究:变迁逻辑与共时场域

当前,以为农服务为宗旨的供销社面临重新定位和再发展问题。文本立足“新时代供销社何去何从”主题,基于注意力变迁视角及制度分析与发展(IAD)框架的整合,在系统梳理供销社演化脉络和变迁逻辑的基础上,分析现阶段供销社的综合改革场域。研究认为:鉴于不同时期国家对乡村建设中供销社的角色呼唤有其时态语境,新时代的供销社应遵循注意力变迁逻辑并由此呈现渐变性特征。从长期看,供销社要把握历时演化的内在逻辑,释放作为“四不像”组织的灵活性,服务党和国家战略;从短期看,要以治理注意力为导向,从国家层面与供销系统两大角度探索改革方向与举措,助力供销社综合改革有效服务乡村振兴战略。

信息素养教育的价值表达与营销框架构建——基于ROST CM6和Nvivo12的质性文本分析

国内高校在构建可推广的普适化、情境化和嵌入实践的信息素养教育模式方面做了诸多努力,但接受信息素养教育的大学生占比还不够普及,信息素养教育在高校尚未被机构内用户广泛接受并持续发展。《高等教育信息素养框架》为开展数智时代高校信息素养教育营销推广提供了制度借鉴,文章运用文本分析工具ROST CM6和Nvivo12对《框架》文本进行质性分析,从社会价值、知识价值、审美价值等8个维度深入挖掘《框架》蕴含的信息素养教育的价值内涵,从价值行动、价值目标、价值功能三个维度构建了信息素养教育的价值营销框架。

全国统一电力市场环境下的电力辅助服务市场体系设计

全国统一电力市场体系设计及建设重点围绕电能品种展开,辅助服务作为保障电力系统安全的重要品种,也需适应主能量市场、从全国辅助服务市场体系角度开展顶层设计。文中分析了中国区域及省级辅助服务市场机制的总体情况。在全国统一电力市场的基本框架下,基于对电能量市场基本发展形态的分析,从市场层级维度、市场品种维度、市场周期维度出发,梳理层级之间、品种之间的衔接关系,提出适应不同市场发展阶段的全国辅助服务市场整体框架及建设发展路径。

基于互动视角的数字营销研究:整合框架与未来展望

人工智能、区块链、大数据、云计算等颠覆性信息技术对市场营销带来了前所未有的影响,数字营销逐渐成为学术界与实践界关注的前沿焦点。然而,在研究文献数量急剧增长的同时,相关研究主题却依然十分零散。本研究基于ADO框架,从互动视角对693篇相关文献进行了系统梳理,开发了以“互动前因—互动过程—互动结果”为主线的数字营销整合框架,进一步深入剖析了现有研究在人工智能悖论、个性化-隐私悖论、数字技术对于顾客行为影响、数字营销绩效度量方式、数字营销互动理论模型等方面存在的主要问题,并识别出未来的重点研究方向,以期对数字营销相关理论研究和实践探索提供有益参考。

基于日前预测与日内运行储能动作偏差量的多园区分布式储能云服务交易机制设计

目前云储能的商业模式及市场机制尚不成熟,用户参与云储能服务的方式较为单一。同时,分布式储能多用于用户侧与可再生能源协同运行以平抑其出力的波动性,其不确定性导致的日前预测与日内运行(DAF-IDO)存在偏差。为此,提出了基于DAF-IDO储能动作偏差量的多园区分布式储能云服务交易机制,将运行与交易相结合,在解决DAF-IDO偏差的同时,为分布式储能用户参与云储能服务提供全新的市场途径。提出了DAF-IDO储能动作偏差量的确定方法,使得各园区运营商能够对园区储能供需量进行定量计算;制定了基于组合拍卖的园区间分布式储能云服务交易机制,并在云储能价格机制中加入谷时段补偿机制,在兼顾各方经济性的同时提升了用户参与云服务的积极性及自主性。通过算例仿真验证了所提机制的可行性和合理性。

Electricity-Heat-Based Integrated Demand Response Considering Double Auction Energy Market with Multi-Energy Storage for Interconnected Areas

With development of integrated energy systems and energy markets,transactive energy has received increasing attention from society and academia,and realization of energy distribution and integrated demand response through market transactions has become a current research hotspot.Research on optimized operation of a distributed energy station as a regional energy supply center is of great significance for improving flexibility and reliability of the system.Based on retail-side energy trading market,this study first establishes a framework of combined electric and heating energy markets and analyses a double auction market mechanism model of interconnected distributed energy stations.This study establishes a mechanism model of energy market participants,and establishes the electric heating combined market-clearing model to maximize global surplus considering multi-energy storage.Finally,in the case study,a typical user energy consumption scenario in winter is selected,showing market-clearing results and demand response effects on a typical day.Impact of transmission line constraints,energy supply equipment capacity,and other factors on clearing results and global surplus are compared and analyzed,verifying the effects of the proposed method on improving global surplus,enhancing interests of market participants and realizing coordination and optimal allocation of both supply and demand resources through energy complementarity between regions.

基于校准窗口集成与耦合市场特征的可解释双层日前电价预测

随着电力市场之间耦合程度不断加深,只局限于单个市场内部的传统特征集不足以支撑高精度预测的需求。而且模型预测性能对校准窗口的选择敏感,而传统电价预测仅使用一个固定时间长度的数据集,同时预测模型的“黑盒”结构导致预测结果在工程应用中可信度偏低。针对上述问题,该文提出一种考虑校准窗口集成与耦合市场特征的可解释双层日前电价预测框架。内层框架为基于改进自适应噪声完备集合经验模态分解(improved complete ensemble empirical mode decomposition,ICEEMDAN)的择优预测,首先分解原始电价序列,然后应用Lasso估计回归(lassoestimated autoregressive,LEAR)、长期和短期时间序列网络(long-term and short-term time-series networks,LSTNet)、卷积神经网络-长短记忆神经网络(convolutionalneuralnetworks-longshort termmemory,CNN-LSTM)、移动平均(autoregressive integrated moving average,ARIMA)和核极限学习机(kernel extreme learning machines,KELM)模型预测子序列并选择最优预测算法。外层框架为基于贝叶斯模型平均(bayes modelaveraging,BMA)的校准窗口集成预测,针对每个不同校准窗口长度数据集下的预测分配权重并集成得到预测电价。最后,通过可解释方法沙普利加性解释模型(shapley additiveexplanations,SHAP)分析耦合市场特征如何影响预测电价。该文通过北欧电力市场数据集的算例分析证明了所提算法的优越性和校准窗口集成方案的有效性。

视频营销研究的整合框架与未来展望

数字经济时代,视频营销在数字营销领域中的地位日益凸显。借助CiteSpace分析软件,基于“前因—作用机制—结果”(ADO)框架和“理论—情境—方法”(TCCM)框架,对既有视频营销相关研究进行梳理,构建了一个涵盖视频营销前因后效、作用机制、理论视角、研究方法和适用场景的整合研究框架。在此基础上,从消费者“接受—拒绝”困境仍未化解、对顾客绩效的影响研究尚显不足、定制化视频营销的研究相对缺乏、视频影响者的营销能力难以量化、理论和方法的发展相对滞后五个方面揭示了既有视频营销研究存在的主要问题。基于上述研究现状归纳和问题反思,结合对企业当下管理实践的思考,从五个方面提炼出视频营销未来的重点研究问题和可能的研究方向,以期推动中国视频营销领域的理论发展和实践应用。

基于碳绿证市场机制的多区域电力系统低碳调度模型

传统能源资源的有限性和供应安全问题促使人们转向能源互联和低碳电力的研究方向。综合能源系统(IES)逐渐成为实现能源协调和节能减排的关键手段。为了管理碳排放和促进可持续能源的利用,文章提出了一种基于碳绿色证书联合市场的多区域综合能源系统调度模型。监管部门对碳排放量进行分配调整,可分别在碳交易系统和绿证市场系统两个渠道进行交换。评估了在IES中引入碳绿色证书市场机制的可行性,并提出了绿色证书联合市场框架。采用组合双拍卖(CDA)机制进行竞价,确定绿色证书的最佳价格,建立了供热网络和天然气网络的优化模型,并将其与IES的约束相结合,确保系统的稳定运行。该模型分析了碳交易系统、绿证市场系统以及天然气价格的变化对系统运行成本的影响。仿真实验结果表明,该模型能够显著提高IES效益并降低碳排放。

基于数据挖掘的多场景互联电力运行指标体系研究

根据国内外先进电力市场的建设经验,一个高水平运作的电力市场离不开市场数据体系建设的强力支持。电力市场的数据是相互交织、相互影响且不断迭代的,因此其数据互联场景复杂而又交叉。文中从交易中心的服务视角出发,对其进行基于数据挖掘的多场景互联的电力市场运行状态评价指标体系的设计。调研分析了电力交易中心相关方指标需求,基于服务的视角,确定电力市场指标体系设计的四个主要目标为达成目标,提出电力市场指标体系的5点设计原则,根据已经细化的数据指标体系建立包括能源经济、电力系统运行、电力交易、电力市场管理、交易中心管理五大类指标的整体框架。此外,文中提出加入调控云资源管控,在紧急时间里可以得到自动化支撑,满足规范。文中研究建立电力市场的数据指标体系,可服务于电力市场建设。

卡-梅框架下数据财产权益保护规则分类分级配置研究

在社会、经济数字化转型的关键时期,建立高效的数据要素市场是数字经济持续快速发展的重要基础和基本前提,也是多学科交融的时代课题。数据的财产权益保护制度是数据要素市场的基础制度,目前相关的理论探讨可谓百家争鸣,与法律规定和裁判观点共同构成了一张“规则清单”。卡-梅框架提供了一种以经济效率为标准的规则选择方法,与建设高效的数据要素市场这一政策目标相契合。在此框架下,从事前效率和事后效率两个视角分别对个人数据、企业数据和公共数据的财产权益保护规则进行比较和选择,发现对于个人数据和企业数据而言,提供事后救济的责任规则相比赋予绝对化财产权的财产规则更具效率;而对于公共数据而言,两者各有优势。基于此,进一步对个人数据保护提出了构建“三层构造”保护模式的立法建议和建立数据匿名化制度的构想,对企业数据保护提出了构建非绝对性财产权利的方向指引,对公共数据提出了建立三类规则相互配合的分类分级开放格局的建议。

多智能物资运送小车协同控制的任务分配

针对进一步提升物资运送智能车的使用效率及多智能体协作任务分配不合理问题,提出一种基于区域划分拍卖算法的多车协同控制的任务分配策略。首先,对已知环境根据任务的密集程度进行区域划分,实现全局环境的任务处理。其次,按任务类型划分不同的处理方式,即局部任务通过使用优化的拍卖算法处理任务,进而提高多车协同的使用效率;全局跨区域任务使用二层框架完成点对点任务处理。最后,在全局已知的环境下进一步仿真算法,对比打击类型无人机的任务分配算法。结果表明,该算法的性能对智能车使用效率更高、任务的承载能力更强、任务分配策略更合理,在对多车协同控制解决任务分配的问题上能高效实施,简化复杂的任务分配过程。

数字经济时代微观经济理论的探索与思考

为了厘清数字经济时代传统微观经济学理论的适用性问题,揭示微观经济学理论革新的方向和实践中的应用,旨在构建一个更加符合数字经济特点的微观经济学理论框架。采用文献分析、理论分析和案例研究相结合的方法,着重将微观经济学理论框架中的供求定理、消费者行为、生产者决策、市场结构和外部性理论五大部分,置于数字经济时代背景下进行深入剖析。研究发现,数字经济时代的供求定理需要考虑基于大数据、人工智能的供给特征和消费者需求逻辑,以及平台企业的网络外部性和规模经济效应;消费者行为呈现出优化、升级、多样化和个性化的特征,以及非占有式的分享消费逻辑,并且可能产生选择过载;生产者决策需要运用人工智能技术来匹配产供销大数据,实现数据智能化,提高生产效率和创新能力;市场结构呈现出分层式垄断竞争的特点,需要采取新的监管政策和治理机制,维护市场秩序和社会福利;外部性理论需要分析数字经济带来的正外部性和负外部性,处理信息问题和产权问题,注重维护数据隐私和网络安全。研究表明,数字经济对微观经济学提出了一系列新挑战,要求理论和实践的创新与调整,通过更新理论框架、引入新的分析方法,微观经济学能够更好地理解和适应数字经济的发展,为理解数字经济时代的经济学变革提供了一定的参考和启示。

基于逻辑框架法的供销系统“保供促销”项目后评价——以漳州市东山县城关供销社海产品批发市场为例

逻辑框架法(Logical Framework Approach,LFA)作为在工程管理专业领域常用的定性分析方法,其在项目评价中具有极其重要的地位。在项目评价中,通过使用逻辑框架法这一重要工具,可以对项目进行全方位和全过程分析。供销系统“保供促销”项目是指全省供销合作社系统为保障农产品、农业生产资料等供应链稳定畅通和开拓农村市场、促进消费而投入资金的项目,对其进行评价研究的重要意义在于衡量对投入专项资金的项目是否起到“保供促销”的效用。本文通过项目实例,演示逻辑框架法在“保供促销”项目评价上的应用,分析项目的投入、产出、具体目的与宏观目标之间的关系,为提高项目效益和管理水平提供借鉴。