基于物理合同的梯级水电厂日前交易电量优化分配

提出物理合同模式下梯级水电厂日前交易电量优化的数学模型,目标函数是梯级总收入最大化,采用逐步优化算法,能够同时进行合同电量和竞价电量的优化分配,为梯级水电厂联合报价和电量申报提供参考。实例应用表明了方法的可行性。     

Stochastic multiobjective self-scheduling of a power producer in joint energy and reserves markets

This paper presents a stochastic multiobjective model for self-scheduling of a power producer which participates in the day-ahead joint energy and reserves markets. The objective of a power producer is to compromise the conflicting objectives of payoff maximization and gaseous emissions minimization when committing its generation of thermal units. The proposed schedule will be used by the power producers to decide on emission quota arbitrage opportunities and for strategic bidding to the energy and reserves market. The paper analyzes a scenario-based multiobjective model in which random distributions, such as price forecasting inaccuracies as well as forced outage of generating units are modeled as scenarios tree using a combined fuzzy c-mean/Monte-Carlo simulation (FCM/MCS) method. With the above procedure the stochastic multiobjective self-scheduling problem is converted into corresponding deterministic problems. Then a multiobjective mathematical programming (MMP) approach based on ?-constraint method is implemented for each deterministic scenario. Piecewise linearized fuel and emission cost functions are applied for computational efficiency and the model is formulated as a mixed-integer programming (MIP) problem. Numerical simulations for a power producer with 21 thermal units are discussed to demonstrate the performance of the proposed approach in increasing expected payoffs by adjusting the emission quota arbitrage opportunities.     

Risk-constrained self-scheduling of a fuel and emission constrained power producer using rolling window procedure

This work addresses a relevant methodology for self-scheduling of a price-taker fuel and emission constrained power producer in day-ahead correlated energy, spinning reserve and fuel markets to achieve a trade-off between the expected profit and the risk versus different risk levels based on Markowitz’s seminal work in the area of portfolio selection. Here, a set of uncertainties including price forecasting errors and available fuel uncertainty are considered. The latter uncertainty arises because of uncertainties in being called for reserve deployment in the spinning reserve market and availability of power plant. To tackle the price forecasting errors, variances of energy, spinning reserve and fuel prices along with their covariances which are due to markets correlation are taken into account using relevant historical data. In order to tackle available fuel uncertainty, a framework for self-scheduling referred to as rolling window is proposed. This risk-constrained self-scheduling framework is therefore formulated and solved as a mixed-integer non-linear programming problem. Furthermore, numerical results for a case study are discussed.     

Optimization based bidding strategies in the deregulated market

With the deregulation of electric power systems, market participants are facing an important task of bidding energy to an independent system operator (ISO). This paper presents a model and a method for optimization-based bidding and self-scheduling where a utility bids part of its energy and self-schedules the rest as in New England. The model considers ISO bid selections and uncertain bidding information of other market participants. With appropriately simplified bidding and ISO models, closed-form ISO solutions are first obtained. These solutions are then plugged into the utility's bidding and self-scheduling model which is solved by using Lagrangian relaxation. Testing results show that the method effectively solves the problem with reasonable amount of CPU time     

Unit commitment problem in deregulated environment

This paper addresses the self-scheduling problem of generation companies owning thermal power units considering bilateral contracts and day-ahead market. This approach allows precise modelling of variable costs, start-up costs and comprehensive system of constraints. The self-scheduling model is formulated as deterministic optimization problem in which expected profit is maximized by 0/1 mixed-integer linear programming technique. Solution is achieved using the homogeneous and self-dual interior point method for linear programming, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model for optimizing the thermal generation schedule is demonstrated through the case study with detailed discussion.     

Hydrothermal self-scheduling problem in a day-ahead electricity market

This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a day-ahead market. The hydrothermal model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modelling of non-convex variable cost functions and non-linear start-up cost functions of thermal units, non-concave power-discharge characteristics of hydro units, ramp rate limits of thermal units and minimum up and down time constraints for both hydro and thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the generation schedule is demonstrated through the case studies and their analysis.     

基于合作博弈的含清洁能源发电商参与现货市场竞价策略及收益分配

随着清洁能源发电技术的成熟及其建设成本的下降,含清洁能源发电商在参与电力市场时逐渐从补贴对象转变为自主竞价的市场主体。一方面,火电机组具有较好的调节能力,但在较低的预期能源价格期间,昂贵的生产成本可能导致其单独参加现货市场竞标时缺乏竞争力;另一方面,清洁能源出力和现货市场电价的不确定性导致发电商在参与电力市场竞争时需承担投标偏差造成的损失,收益大幅下降。采用风火联合竞价策略可以促使二者优势互补、共赢发展。首先,以含清洁能源发电商参与现货市场竞价利润最大为目标,建立考虑投标偏差惩罚的风火机组联合组成的含清洁能源发电商两阶段随机整数优化竞价模型,采用条件风险价值理论评估清洁能源和电价预测偏差风险,并得到最优竞价策略。对联合后获得的收益,利用合作博弈论中的核仁解给出火电机组与清洁能源机组间的收益分配方法。算例仿真验证,所提竞价策略有效提高了含清洁能源发电商的利润,降低了投标偏差惩罚对含清洁能源发电商收益的影响,增强了含清洁能源发电商在参与现货市场的主动性。     

基于合作博弈模型的新能源参与电力交易的调控策略

我国“十四五”规划提出建设以新能源为主体的新型电力系统,这为我国能源结构优化和低碳建设提供助力,同时也对新能源的消纳和电力供需稳定提出了新的要求。文中立足于现阶段新能源参与电力市场的基本情况,通过构建供给侧火电与新能源多能互补的合作联盟以及供需双侧可调负荷与新能源的源荷互动合作联盟,通过信息互补、潮流互济等多种形式,实现有效的新能源消纳量提升和电力合作联盟的电力市场效益提升。并通过仿真案例证明了所提模型在促进新能源消纳、减少电力市场偏差和提升合作联盟效益等多个方面存在显著成效。     

不完全信息下基于深度双Q网络的发电商三段式竞价策略

不完全信息的电力市场环境下发电商仅知道自身相关的信息,而其他市场参与者的报价和市场环境都可能会影响市场出清结果,进而影响发电商的收益,因此其报价决策应当考虑多维的市场信息。基于深度强化学习算法,提出多智能体的DDQN（double deep Q-network）算法模拟日前现货市场中发电商三段式竞价策略的过程。首先,定义发电商模型中马尔可夫决策过程的要素和动作价值函数;然后,建立发电商深度双Q网络的框架,并引入经验池和动态ε-greedy算法进行神经网络的训练,该决策模型可以根据市场的出清电价和负荷水平等多维连续状态做出报价;最后,通过算例比较了发电商采用DDQN和传统Q-learning两种算法获得的收益差别,说明DDQN算法可以根据发电商面临的复杂市场环境做出正确的决策而Q-learning算法在环境复杂时决策能力较差,并在不同状态量选取、网络泛化能力、更大规模算例适应性等方面分析了发电商采用DDQN算法进行市场策略生成的有效性和优越性。     

Binary fireworks algorithm for profit based unit commitment (PBUC) problem

The deregulation of electricity markets has transformed the unit commitment and economic dispatch problem in power systems from cost minimization approach to profit maximization approach in which generation company (GENCO)/independent power producer (IPP) would schedule the available generators to maximize the profit for the forecasted prices in day ahead market (DAM). The PBUC is a highly complex optimization problem with equal, in equal and bound constraints which allocates scheduling of thermal generators in energy and reserve markets with no obligation to load and reserve satisfaction. The quality of the solution is important in deciding the commitment status and there by affecting profit incurred by GENCO/IPPs. This paper proposes a binary coded fireworks algorithm through mimicking spectacular display of glorious fireworks explosion in sky. In deregulated market GENCO/IPP has the freedom to schedule its generators in one or more market(s) based on the profit. The proposed algorithm is tested on thermal unit system for different participation scenarios namely with and without reserve market participation. Results demonstrate the superiority of the proposed algorithm in solving PBUC compared to some existing benchmark algorithms in terms of profit and number of iterations.     

Monopsony behavior in the power generation market

As the sole sellers of power to customers and buyers of wholesale power, vertically integrated electric utilities operate as both monopolies and monopsonies. Regulators account for the negative effects of monopolistic behavior, but little attention is given to the impact of monopsony. As the sole (or dominant) buyer of power in a particular market, the vertically integrated utility can constrain the market, shift risks to sellers, and force generation prices below a long-term market rate. A less competitive market enhances the utility’s opportunity to invest its own capital in generation, even at above-market prices, and even to the point of costly over-procurement.     

Acumentrics,Sumitomo form SOFC joint venture

Massachusetts-based Acumentrics, a leading solid oxide fuel cell developer, is forming Acumentrics Japan Co as a joint venture with Sumitomo Corporation, one of Japan’s largest integrated trading companies. The new company will market and sell Acumentrics’ proprietary tubular SOFC (T-SOFC) power systems throughout Japan. The venture marks the successful conclusion of a year-long market and fuel cell technology study.This is a short news story only. Visit www.re-focus.net for the latest renewable energy industry news.     

区域电网竞价策略研究

根据区域电网的特点,研究售电公司、电网公司和用电客户之间的电量交易。考虑到交易过程中的供需差异等因素,建立了基于输电费用优化的非合作博弈售电策略模型。以区域电网为例,分析各利益主体在非合作博弈模型下的纳什均衡售电策略。算例分析结果表明,非合作博弈售电策略模型不仅可为售电公司提供竞价参考、平衡可再生能源和传统火电之间的利益,同时也可降低区域电能供需不平衡概率,保障电力市场安全运行。     

考虑电热多种负荷综合需求响应的园区微网综合能源系统优化运行

区域综合能源系统是解决社会能源利用效率低以及可再生清洁能源难以消纳问题的有效途径之一。基于电力负荷与热力负荷在综合能源管理中具有相似的可调度价值,提出了一种考虑电热多种负荷综合需求响应的园区微网综合能源系统优化模型。首先,在电力负荷价格型需求响应的基础上,分析了热力负荷具有传输延迟、供热舒适度模糊性等固有特点,可作为柔性负荷参与到优化调度中,即热力需求响应;其次建立了包含风电、光伏、燃气轮机、余热锅炉、储能设备、燃气锅炉、以及电热负荷构成的热电联供型园区微网模型,以系统综合运行成本最小为目标函数。算例仿真结果表明,综合需求响应的应用提高了园区微网热电生产的灵活性,考虑电热力多负荷综合需求响应比单一考虑需求响应可有效地减少弃风、弃光,降低需求侧用户的总能源消耗成本以及系统的运行成本,提高能源利用效率,实现系统环保经济运行。     

考虑可转移负荷的售电公司负荷组合优化

在电力市场环境下,售电公司根据用户的负荷特性,进行用户负荷的组合优化可以降低售电公司的购电成本,从而提升售电公司效益。针对售电公司如何根据电力负荷的互补性、多样性整合优化用户资源的问题,从降低购电成本,提高售电公司效益角度,首先分析了负荷率对购电成本的影响,接着基于用户综合负荷特性,构建售电公司初步负荷组合优化模型,再进一步考虑了用户可转移负荷,对用户的组合负荷特性进行优化,最大化售电公司售电利益,最后根据某市2019年工业用户群组负荷数据,对提出的模型进行仿真分析,并对研究实施的软件功能架构进行了设计。     

考虑可再生能源消纳的火电机组市场力评估

随着可再生能源并网比例的不断提升,实现其全额消纳会对火电机组的市场机会产生越来越大的冲击。针对这一现象,提出了火电机组综合市场力评估方法。考虑可再生能源发电并网下火电机组备用作用的强化,对传统市场力指标——Lerner指数进行修正,建立了反映火电机组在电量市场与备用市场综合市场力的改进Lerner指标;同时计及风电出力的不确定性,采用正态分布与拉普拉斯分布的联合概率密度函数更好地反映风电预测误差的尖峰厚尾特性,完善了备用需求的表达;以电量完全竞争作为假设前提,采用电量—备用联合优化模型模拟电力市场交易,进而完成对火电机组综合市场力的准确度量。以10机系统为例进行仿真计算,验证了改进指标的有效性并分析风电渗透率、风电预测精度等因素变化对火电机组综合市场力的影响。     

电力市场环境下抽水蓄能电站的运营模式与效益分析

简要分析了在电力市场环境下抽水蓄能电站的收益模型,论述了我国抽水蓄能电站的投资体制和经营管理模式,讨论了在不同经营管理模式下抽水蓄能电站的收益特点和经营风险。在此基础上,分析了两种适合我国电力市场化改革初级阶段的抽水蓄能电站的经营管理模式,即由电网公司和拥有大型火电机组的发电公司联合租赁抽水蓄能电站的模式,以及抽水蓄能电站和拥有大型火电机组的发电公司联合运营的模式,描述了评估抽水蓄能电站对电网公司和这类发电公司的贡献模型,以用于适当确定和分配租赁费。     

Stochastic operational scheduling of distributed energy resources in a large scale virtual power plant

Virtual Power Plant (VPP) is introduced as a tool for the integration of distributed generations, energy storages and participation of consumers in demand response programs. In this paper, a probabilistic model using a modified scenario-based decision making method for optimal day ahead scheduling of electrical and thermal energy resources in a VPP is proposed. In the proposed model, energy and reserve is simultaneously scheduled and the presence of energy storage devices and demand response resources are also investigated. Moreover, the market prices, electrical demand and intermittent renewable power generation are considered as uncertain parameters in the model. A modified scenario-based decision making method is developed in order to model the uncertainties in VPP’s scheduling problem. The results demonstrated that the optimal scheduling of VPP’s resources by the proposed method leads VPP to make optimal decisions in the energy/reserve market and to play a dual role as a demand/generation unit from the perspective of the upstream network in some time periods.     

热电厂负荷分配模型与算法

负荷分配是发电企业节能减排的重要措施。热电厂中存在热、电两种品质不等价又相互关联的能量类型,其负荷优化分配问题较普通凝汽式电厂复杂得多,是一个高维、非凸、离散的非线性规划问题。综述热电厂负荷优化分配的数学模型,对求解此问题的各种优化算法进行详细分析比较,提出进一步研究的方向。     

含大规模储热的光热电站—风电联合系统多日自调度方法

含储热的光热电站具有良好的可调度性,其可调度能力与实时光照功率和储热装置内存储的能量有关。当光热电站与风电组成联合系统发电时,光热电站可以削减风电的不确定性,但由于风、光功率情况在不同调度日间具有波动性,因此联合系统需要的光热电站的可调度能力和光热电站的实际可调度能力每天均不相同。文中建立了基于场景方法的光热电站与风电联合系统的多日随机调度模型。该模型充分考虑多日风、光功率预测的不确定性,进行联合系统日前自调度。最后,通过算例分析,讨论了不同预测时间尺度、储能参数取值对自调度结果的影响。