Robust bidding and offering strategies of electricity retailer under multi-tariff pricing

In this paper, an electricity retailer seeks to determine selling price for end-user consumers under fixed pricing (FP), time-of-use pricing (TOU) and real-time pricing (RTP). Furthermore, in order to provide power exchange between the retailer and the power market, bidding and offering curves should be prepared to bid and offer to the day-ahead market. Therefore, this paper proposes a robust optimization approach (ROA) to obtain optimal bidding and offering strategies for the retailer. To achieve this, ROA is used for uncertainty modeling of power market prices in which the minimum and maximum limits of prices are considered for uncertainty modeling. Lower and upper bounds of price is consecutively subdivided into sequentially nested subintervals which allows formulating robust mixed-integer linear programming (RMIP) problem. The proposed RMIP model helps retailer to select a robust decision in the presence of market price uncertainty. Furthermore, the bidding and offering curves of the retailer are obtained from sufficient data through solving these problems. Meanwhile, the uncertainty of customers demand and variable climate condition are modeled based on stochastic programming. To validate the proposed robust optimization model, three case studies are evaluated and the results are compared.     

Production price of hydrogen from grid connected electrolysis in a power market with high wind penetration.

In liberalized power markets, there are significant power price fluctuations due to independently varying changes in demand and supply, the latter being substantial in systems with high wind power penetration. In such systems, hydrogen production by grid connected electrolysis can be cost optimized by operating an electrolyzer part time. This paper presents a study on the minimization of the hydrogen production price and its dependence on estimated power price fluctuations. The calculation of power price fluctuations is based on a parameterization of existing data on wind power production, power consumption and power price evolution in the West Danish power market area. The price for hydrogen is derived as a function of the optimal electrolyzer operation hours per year for four different wind penetration scenarios. It is found to amount to 0.41–0.45 €/Nm³. The study further discusses the hydrogen price sensitivity towards investment costs and the contribution from non-wind power sources.     

关于在电力市场环境下建立和促进可再生能源发电价格体系的研究

本文介绍了在开放的竞争性电力市场环境下,制定和实施特殊的上网电价政策来促进可再生能源发电发展的国际经验,总结归纳了政策制定的基本原则、方法和典型的价格体系,对各类价格政策的实施效果以及对我国的适用性进行了分析。提出在竞争性电力市场环境下,采用特殊的价格政策和机制,可以起到鼓励可再生能源发电市场发展和带动技术进步、产业升级的效果。我国应吸取国外的成功经验,根据我国可再生能源电价政策的实施情况,对政策予以适时调整,完善价格政策体系。     

电价预测技术综述

电力工业从垄断走向市场,使得电价不再由政府确定,而是在市场机制下产生。电价波动会影响市场参与者的经济利益。对电力市场参与者而言,准确地预测电价具有非常重要的意义。该论文以电力系统短期边际价格为主要研究对象。首先分析了电价的变化特点、影响电价的主要因素,明确电价变化的规律性。然后介绍了一些现有因素分析的方法。并对当前电价预测方法按其工作原理进行分类总结,最后根据各类电价预测模型的特点尤其利用神经网络方法建立的预测模型进行了深入分析和总结。     

A bilevel model for electricity retailers' participation in a demand response market environment

Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility.     

过渡时期发电企业竞价模式研究

自2002年国家提出建立竞争性的电力市场的目标以来,多个采用不同竞价机制的区域电力市场试点已初步形成。但是由于我国的电力产业自身条件的特殊性和电价衍变过程的复杂性,决定了竞价机制改革必须在充分考虑历史遗留因素的条件下稳步推进。本文通过分析电价的衍变过程和电力市场化改革的区域试点工作,针对向市场化过渡的特殊时期所必须面临的问题,提出了一种新的发电企业竞价模式。该模式采用了新的两部制电价计算方法和电力市场运营模式,在有效解决电力产业的一些历史遗留问题的条件下,为不同技术类型、不同时期建设的发电机组提供了一个统一的竞争平台,同时为该模式提供了一些配套的政策建议。     

基于SQP法的电厂日前合约市场报价策略研究

在电力市场环境下,发电企业为了追求经济效益的最大化,必须在优化机组负荷分配的基础上掌握企业运行成本,并在电力市场上报出具有竞争力的上网电价。针对日前市场的特殊性,并建立了机组经济性曲线拟合的数学模型和基于序列二次规划法(SQP法)的机组负荷优化分配模型,指出了完全成本加成法的报价方法。用算例验证了一个发电企业在4个时段日前市场负荷的耗量成本。     

适合国情的两部制电力市场研究

从电力生产特点分析入手,论述了建立两部制电力市场的必要性;阐述了电力市场出清价由两部制成本形成;基于发电可靠性分析,提出了两部制电力市场价格的模型及实现方式;最后,通过一个实例模拟,验证了两部制电力市场的可行性。     

甘肃敦煌10MW光伏并网发电特许权示范项目存在问题分析

2009年3月启动的甘肃敦煌10MW光伏并网发电特许权示范项目招标,标志着我国在大型荒漠光伏电站应用方面取得了重大进展。国家能源局组织开展的第一轮太阳能光伏发电特许权招标活动非常及时,对启动国内太阳能光伏市场产生了积极的影响,确定的电价1.09元/(kW.h)基本合理。然而,项目在实施过程中也却遇到了一系列的问题,如因供货不及时影响了项目进展,增大了建设成本;配套电网建设滞后;电力外送和消纳问题越来越突出,将成为大规模发展光伏电站的主要制约因素;税制改革挫伤了地方政府的积极性等。为保证国内光伏市场的健康发展,建议应将增值税中央收入部分按一定比例返还地方,采取补贴或者转移支付等手段维护地方政府开发太阳能项目的积极性;继续开展招标试点,摸清国内太阳能产业和市场的发展走向,完善太阳能光伏发电价格形成机制;吸取风电特许权项目的经验教训,改进招标规则,在电价的核准上谨慎行事;统筹考虑风电、太阳能等可再生能源资源开发与外送通道和消纳市场问题;慎重对待为解决太阳能等可再生能源发电电力消纳问题而引进高耗能项目。     

发电侧电力市场辅助定价研究

以传统的潮流约束和年度利润目标作为约束条件建立定价模型。对一个实际电厂的数据进行模拟计算，结果表明：用该模型计算出的电价能够满足电厂的经济目标要求，为报价提供了有益的参考。     

基于区块链的内部模拟市场建设研究与应用

当前电网企业的经营面临着严格的成本监管与市场化竞争,为了提高企业的经济效益并激发基层单位经营活力,电网公司有必要构建内部模拟市场来将市场供需、价格和竞争机制引入企业内部。区块链里存储的数据被加密并带有数字签名,难以篡改,可以依托Hyperledger Fabric平台,构建联盟区块链的内部模拟市场交易系统。文章提出了将业务数据上链存证,实现分布式共享,设计“专家共识法”实现多方参与定价定量,并采用智能合约实现各类业务交易的点对点结算。对系统的交易处理性能进行的实验测试结果表明,基于联盟区块链Fabric平台的内部模拟交易系统,当结算智能合约个数为100时,执行时间平均为0.47 s,具有较高的运行效率。     

对我国电力市场的初探

阐述了我国建立电力市场为目的,介绍了我国电力市场的基本框架内容,并就这个框架里的内容作了深入的研究和分析,以利于我国将来的电力市场的发展和完善。     

电力市场中热电联产机组两部制电价机制的研究

通过比较热电联产机组与常规火电机组的优势劣势,分析了国内外电力市场中热电联产机组的扶持政策和运营情况,提出了热电联产机组参与电力市场的两部制电价机制设计方法,给出了热电联产机组两部制电价中可用容量、可用小时数、容量电价、电量电价等参数的计算方法,形成了一套科学合理的价格形成机制,使其与常规火电机组可以参与同一电力市场竞价上网。     

边际电价预测的三时点模型

从供求决定价格、价格引导供求两个角度出发，分析了电力市场系统供给、需求与电价的关系，建立了边际电价的三时点预到模型。运用该模型对西部某电网次日96点现货电价进行预到，取得了较好的预测效果。     

Day-ahead price forecasting of electricity markets by a new feature selection algorithm and cascaded neural network technique

With the introduction of restructuring into the electric power industry, the price of electricity has become the focus of all activities in the power market. Electricity price forecast is key information for electricity market managers and participants. However, electricity price is a complex signal due to its non-linear, non-stationary, and time variant behavior. In spite of performed research in this area, more accurate and robust price forecast methods are still required. In this paper, a new forecast strategy is proposed for day-ahead price forecasting of electricity markets. Our forecast strategy is composed of a new two stage feature selection technique and cascaded neural networks. The proposed feature selection technique comprises modified Relief algorithm for the first stage and correlation analysis for the second stage. The modified Relief algorithm selects candidate inputs with maximum relevancy with the target variable. Then among the selected candidates, the correlation analysis eliminates redundant inputs. Selected features by the two stage feature selection technique are used for the forecast engine, which is composed of 24 consecutive forecasters. Each of these 24 forecasters is a neural network allocated to predict the price of 1 h of the next day. The whole proposed forecast strategy is examined on the Spanish and Australia’s National Electricity Markets Management Company (NEMMCO) and compared with some of the most recent price forecast methods.     

Optimal investment strategies in decentralized renewable power generation under uncertainty

This paper presents a method for evaluating investments in decentralized renewable power generation under price un certainty. The analysis is applicable for a client with an electricity load and a renewable resource that can be utilized for power generation. The investor has a deferrable opportunity to invest in one local power generating unit, with the objective to maximize the profits from the opportunity. Renewable electricity generation can serve local load when generation and load coincide in time, and surplus power can be exported to the grid. The problem is to find the price intervals and the capacity of the generator at which to invest. Results from a case with wind power generation for an office building suggests it is optimal to wait for higher prices than the net present value break-even price under price uncertainty, and that capacity choice can depend on the current market price and the price volatility. With low price volatility there can be more than one investment price interval for different units with intermediate waiting regions between them. High price volatility increases the value of the investment opportunity, and therefore makes it more attractive to postpone investment until larger units are profitable.     

考虑电价风险的水电站长期优化调度及风险评估

研究了电价的不确定性给电力市场环境下水电站长期优化调度带来的风险,建立了基于VaR的期望—风险效用函数模型。借鉴于金融学中的VaR风险度量方法计量并评估风险,运用进化规划算法求解模型,并给出算例对模型进行了验证,分析说明如何应用风险评估方法进行风险度量和评估。     

An approach to locational marginal price based zonal congestion management in deregulated electricity market

Congestion of transmission line is a vital issue and its management pose a technical challenge in power system deregulation. Congestion occurs in deregulated electricity market when transmission capacity is not sufficient to simultaneously accommodate all constraints of power transmission through a line. Therefore, to manage congestion, a locational marginal price (LMP) based zonal congestion management approach in a deregulated electricity market has been proposed in this paper. As LMP is an economic indicator and its difference between two buses across a transmission line provides the measure of the degree of congestion, therefore, it is efficiently and reliably used in deregulated electricity market for congestion management. This paper utilizes the difference of LMP across a transmission line to categorize various congestion zones in the system. After the identification of congestion zones, distributed generation is optimally placed in most congestion sensitive zones using LMP difference in order to manage congestion. The performance of the proposed methodology has been tested on the IEEE 14-bus system and IEEE 57-bus system.     

省级电力公司电力市场研究

参照国外发达国家电力市场的运行经验，结合中国国情，提出了省级力公司电力市场的建立原则及运行原理。     

当前煤炭价格存在问题及解决思路

文章详细剖析了我国煤炭价格存在的主要问题,明确国内电煤价格改革应逐步向市场化方向迈进,由供需双方按市场机制进行确定。在目前情况下,应坚持放开煤炭价格的市场化改革方向,坚持由供需双方协商定价的基本原则,真正落实煤炭供需企业协商定价自主权。