基于双层规划的拥挤定价模型及算法

城市道路拥挤定价具有双层特性,上层为城市交通管理部门,下层为道路使用者．本文假设用户出行成本仅与出行时间相关,应用双层规划模型建立拥挤定价模型,并讨论双层规划模型的遗传算法．研究表明,双层规划模型能有效解决复杂的拥挤定价问题,遗传算法收敛较快,容易实现计算精度要求．     

高科技项目投资的实物期权定价模型

为了准确地评价高科技项目投资价值,在分析实物期权定价理论的基础上,结合高科技项目投资的特点,把二项式模型与B-S模型结合起来,建立了高科技项目投资价值评价的实物期权定价模型．通过该模型可以捕捉到镶嵌在高科技项目中的管理柔性价值和战略期权价值,进而对这些期权进行定量分析．该方法能提高高科技投资项目管理的实践水平和理论水平,进而提高决策质量．     

Prediction and assessment of demand response potential with coupon incentives in highly renewable power systems

Demand Response (DR) provides both operational and financial benefits to a variety of stakeholders in the power system. For example, in the deregulated market operated by the Electric Reliability Council of Texas (ERCOT), load serving entities (LSEs) usually purchase electricity from the wholesale market (either in day-ahead or real-time market) and sign fixed retail price contracts with their end-consumers. Therefore, incentivizing end-consumers’ load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market. As the first-of-its-kind implementation of Coupon Incentive-based Demand Response (CIDR), the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements, individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets, as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts. A number of methodologies are developed for this special type of DR program including price/baseline prediction, individualized target setting and a lottery mechanism. This paper summarizes the methodologies, design, critical findings, as well as the potential generalization of such an experiment. Comparison of the EnergyCoupon with a conventional Time-of-Use (TOU) price-based DR program is also conducted. Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries, the effective cost for demand response providers in EnergyCoupon can be substantially reduced, while achieving a similar level of demand reduction as conventional DR programs.     

Real-Time Differential Pricing Scheme for Active Consumers with Electric Vehicles

Electric vehicles (EVs) are becoming increasingly popular because of their low operating costs. However, the anticipated increase in EV usage presents opportunities as well as challenges for utilities. This paper models EV charging behavior of active consumers who strategize their EV charging schedule to minimize the charging cost. The electric utility employs a temporal and spatially varying real-time pricing scheme that minimizes peak-to-average load ratio by influencing charging behavior of multiple active consumers. These active consumers decide their optimal charging strategy based on real-time electricity prices in order to minimize their EV charging cost. A model predictive control (MPC)-based optimal pricing scheme for electric utility and optimal charging strategy for active consumers is proposed. Effects of the proposed approach on load profile is verified using simulations.     

社会福利均衡的实时电价多层互动模型

为提升智能电网需求侧管理的实时电价所提升的社会福利普及到电力系统每位参与者,给出了一种更为关注收益均衡的建模方法。根据现有的电力系统运行机制,将发电厂、电网公司和用户纳入其中,以电网公司收益提升为目标,建立实时电价多层互动模型,并与现有的社会总福利最大化模型进行了比较分析。仿真结果表明,互动模型较之社会总福利最大化模型,更好地平衡了各参与者间的收益,并且电网公司的收益具有显著提升,各时段用电负荷也呈现减少趋势,进一步说明了互动模型的有效性。     

An adaptive supervised wide-area backupprotection scheme for transmission linesprotection

Background: The increasing penetration of a massive number of plug-in electric vehicles (PEVs) and distributed generators (DGs) into current power distribution networks imposes obvious challenges on power distribution network operation. Methods: This paper presents an optimal temporal-spatial scheduling strategy of PEV charging demand in the presence of DGs. The solution is designed to ensure the reliable and secure operation of the active power distribution networks, the randomness introduced by PEVs and DGs can be managed through the appropriate scheduling of the PEV charging demand, as the PEVs can be considered as mobile energy storage units. Results: As a result, the charging demands of PEVs are optimally scheduled temporally and spatially, which can improve the DG utilization efficiency as well as reduce the charging cost under real-time pricing (RTP). Conclusions: The proposed scheduling strategy is evaluated through a series of simulations and the numerical results demonstrate the effectiveness and the benefits of the proposed solution.     

电力零售核心业务架构与购售电决策

随着电力工业改革的不断发展和智能电网的兴起,现代电力系统正逐步演变为更加复杂的信息物理融合系统。未来电力系统中将同时融合可再生能源、分布式发电设备、储能设备、智能表计、需求响应等新技术与新机制。在电力零售市场环境下,这些新技术与新机制给零售公司带来了严峻挑战,需要发展新的决策机制与方法。随着中国新一轮电力市场化改革的逐步深化,多个区域的电力零售市场也正在逐步建立和运营。为了给国内构建完整的竞争性电力零售市场提供有益的参考,并帮助相关研究学者和技术人员更好地了解电力零售市场的研究现状,文中首先介绍了一些主要国家的电力零售市场情况,然后以澳大利亚和芬兰为例,详细说明了电力零售公司的组织结构和购售电业务流程。接着,比较系统地综述了近年来国内外电力零售决策方面的研究进展,包括零售负荷预测、零售公司购电策略、零售定价策略、零售风险管理等。最后,讨论了电力零售研究领域的一些关键问题和未来可能的发展方向。     

计及可靠性的跨地区交易统一输电定价模型

结合中国跨地区输电交易、电力体制及价格政策环境,构造了输电系统可靠性影响的评估指标,建立了计及可靠性的跨地区交易统一输电定价模型。该模型包括二层结构:一是深入分析输电成本,提出了长期边际输电可靠性成本的计算方法,基于电网使用程度和长期边际输电可靠性成本,构建了计及可靠性的用户输电定价模型;二是综合考虑输电线路的投资及可靠性贡献,建立了电网运营商输电收益分配模型,构造并引入了过度投资惩罚基金的经济激励模型。该模型采用统一定价机制,克服了多级叠加和点费率定价不能清晰反映跨区域交易对电网的使用份额的不足,定价公平,结算简单透明;可靠性分量的引入能够为市场成员提供输电阻塞的经济信号,有效引导输电投资和使用。IEEE 57节点算例验证了其有效性与合理性。     

PPP模式下地下综合管廊入廊定价激励机制研究

地下综合管廊建设难以推广的主要原因在于前期需要巨大的建设投资和后期需要较高的运营成本。在分析PPP模式相关理论和地下综合管廊相关知识的基础上,提出了适合于我国地下综合管廊建设的PPP融资模式,即基于URM(使用者付费模式)的建设期补偿模式和运营期补偿模式,予以解决前期投资需求问题。继而选取了运营期补偿模式作为研究基础,运用委托-代理理论作为理论支撑,设计了一种激励相容的入廊定价机制,予以解决运营收费问题。该机制的实现,不但可以维护管线单位和消费大众的利益,还可以在满足投资方利润的基础上激励投资方真实申报成本,降低管廊运营成本,减轻政府财政负担。     

城市地下综合管廊定价模型及实证研究

在分析我国已建成的部分城市地下综合管廊没有充分发挥预期效果的原因的基础上,为了吸引投资和促进综合管廊的发展,笔者首先针对已有定价模型的不足,根据“谁受益,谁付费”的原则,通过专家调查和文献分析,确定了管线横截面积、管线年度经营收益、节约的管线建设成本、节约的管线维护成本和管理难度5个分摊因素。进而根据入廊费和年运营维护费确定各因素的重要程度,区分入廊费用分摊因子和年运营维护费用分摊因子,构建了一个更公平合理的定价模型。最后通过实证分析,得出各入廊管线单位负担费用均低于传统直埋方式产生费用的结论,且费用分摊更为合理,说明模型的实用性较强,对我国城市地下综合管廊的建设和发展有一定的参考价值。