考虑多重不确定因素的可再生能源制氢场站最优运营策略研究

以可再生能源制氢场站这一新兴能源制造主体为对象,在电力市场环境下研究面对可再生能源出力和电力市场价格的多重不确定性因素时,可再生能源制氢场站最优运营策略模型,制氢场站的运营策略具体包括制氢场站中长期电量合同分解、电力现货市场购电量以及氢气生产计划。首先,建立了可再生能源制氢场站在电力市场环境下的运营框架,并以此为基础建立了可再生能源制氢场站确定性最优决策模型。其次,采用蒙特卡洛抽样和场景缩减方法,将风电出力的不确定性用具有代表性的典型场景进行刻画。接着,建立了基于信息间隙决策理论的计及现货价格不确定性的可再生能源制氢场站最优运营决策模型,该模型给出的决策能够保证可再生能源制氢场站的总成本不高于其最大所能接受的值。最后,通过算例仿真与对比证明了所提方法的有效性。     

水电厂年度合约电量的风险控制研究

针对电力市场环境下水电企业的合同电量确定及计划安排等问题,从水电厂商对预测径流和预测现货电价的风险态度出发,提出以风险价值(VaR)为风险量测方法,构建了考虑径流和电价的不确定性控制风险模型,并基于水电厂商风险控制目标确定年度合约电量.     

可再生能源绿证价格季节性测算方法研究

  目的  在市场化交易模式消纳可再生能源发电的发展趋势下,“市场电价+绿证收入”将成为未来可再生能源发电企业的主要经营模式。以可再生能源发电参与现货电能量市场为研究大背景,对可再生能源绿色电力证书的价格进行研究。  方法  基于现货电能量市场的优化出清模型,应用可再生能源全生命周期成本测算理论,以满足可再生能源发电企业的内部收益为目的,建立了绿证-电能量市场耦合的优化模型,并结合可再生能源季节性出力特性,提出了可再生能源绿证价格季节性曲线及其波动区间的仿真和测算方法。  结果  不同类型的可再生能源绿证价格不同,不同类型的可再生能源绿证价格的气候相关性亦不相同。  结论  绿证价格的科学合理测算不仅可以帮助可再生能源发电企业进行收益评估和制定更为准确的投资决策,还为电力市场主体与交易中心提供相关决策支持。     

电力现货背景下的可再生能源配额制、绿色电力证书及碳交易等机制改进设计

随着电力现货8个试点省份开展连续试运行结算,电力现货模式初具雏形。现货市场能够实现资源优化配置,促进新能源消纳。可再生能源消纳保障机制、绿色电力证书、碳市场机制与电力现货将一直共存。现行机制下,绿色电力证书与补贴捆绑,相对价格较高,市场反应冷淡;可再生能源消纳保障机制与绿色电力证书存在双重计量的问题。本文从可再生能源保量保价的角度出发,提出了新的市场机制设计方案及建议。绿色电力证书制度纳入平价项目,存量项目与补贴解绑;可再生能源消纳保障机制与电力现货市场结合开展,确保消纳指标完成。建议放开可再生能源直接参与市场,绿电交易实现多方共赢。可再生能源企业与用户进行双边绿电直接交易,建议以绿色能源企业为先行试点。最后,建立了可再生能源为中心的机制体系,并展示了体系内部相互关系,为下一步市场机制改进、促进可再生能源健康发展提供了思路。     

考虑源荷不确定性的分时电价动态修正机制研究

针对新型电力系统中可再生能源出力及负荷需求的不确定性造成源荷协调困难,导致难以制定合理的分时电价的问题,该文提出一种考虑源荷不确定性的分时电价动态修正机制。首先,根据可再生能源出力的波动性以及不确定性,建立新能源并网功率与并网电量偏差量化模型;其次,根据需求侧负荷的变化特征,结合可再生能源出力不确定性,通过多种不确定性因素影响条件的误差计算方法,建立电价概率密度模型。然后,根据负荷上报的用电量以及预报电价,建立考虑源荷不确定性的电力市场分时电价动态修正与优化模型,并采用粒子群算法进行模型求解。最后,通过实际运行数据仿真验证该文所提方法的有效性。     

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。     

基于改进引力搜索算法的电力市场环境下可再生能源竞标消纳优化

为解决新能源参与电力市场竞标、促进新能源消纳的问题,文章提出了基于改进引力搜索算法的电力市场环境下可再生能源竞标消纳优化模型。建立了风电、光伏机组出力模型,确定了风电光伏不确定出力场景削减。针对可再生能源竞标消纳模型建立了出清电价模型,确定了交易双方利润模型,并针对交易过程中的不确定概率进行了分析。提出了采用改进引力搜索算法联合模式搜索算法对出清电价模型进行求解。最后通过仿真分析,说明了所提方法的有效性。     

考虑收益风险的梯级水电站群中长期合约电量最优组合模型

针对梯级水电站群参与不同时间尺度的合约电量交易时天然来水和交易电价的不确定性因素导致不同市场份额难以确定、水资源利用不充分及不同时间尺度电量分配不合理导致收益存在较大风险问题，提出了考虑收益风险的梯级水电站群中长期合约电量最优组合模型，该模型采用给定置信度下整个梯级发电收益风险最小为目标，其求解首先由多年来水数据生成随机月尺度来水过程，然后根据梯级水电站占市场比重不同模拟出三种电价函数，采用逐步优化和逐次逼近混合算法对电站出力和合约电量组合循环迭代求解。最后以西南地区某流域梯级水电站为例进行验证。结果表明，所提出的优化调度模型能够合理制定年度和月度双边合约电量申报策略，有效降低收益风险，为梯级水电站群参与不同时间尺度的双边交易市场提供可靠依据。     

全钒液流电池储能在配电网中优化配置策略

再生能源的大量接入对配电网造成许多不利影响,应用全钒液流电池（VRB）储能技术可有效促进可再生能源消纳,减少可再生能源并网造成的不利影响。分析了VRB储能的充放电特性,并在此基础上建立了电池模型,充分考虑配电网中风电、光伏发电、负荷需求的不确定性和VRB储能电池的经济性,提出了一种VRB储能优化配置策略,利用遗传算法进行求解,在IEEE33节点电网模型中进行仿真分析,验证了这种策略可有效提高可再生能源消纳,减少大电网中传统燃料能源输入电量。     

基于Vine-Copula和拟蒙特卡罗法的可再生能源电力现货市场风险度量模型

可再生能源参与电力现货市场政策制定前,需度量可再生能源的市场风险。在可再生能源未深度参与电力现货背景下,直接采用传统方法对历史数据进行风险度量不可行。文章结合可再生能源有效出力和在险模型(Value at Risk,VaR)设计了可再生能源风险度量指标,通过风险场景匹配市场和机组出力数据。针对目前国内电力现货市场数据量少的问题,结合市场主体在电力现货市场中所能获得的数据进行市场因子筛选,通过Vine-Copula函数考虑多个市场因子间的相关性;改进了传统蒙特卡罗法收敛慢的缺陷,采用拟蒙特卡罗模拟法生成市场因子数据,根据拟合的映射关系生成电价水平数据。最后,文章基于南方(以广东起步)电力现货市场结算试运行的数据和海上风电与光伏的仿真出力,对所提出的模型进行算例分析,结果显示拟蒙特卡罗法收敛性更高,能满足模型中所有风险场景高频计算风险的需求。     

Long-term cross-border electricity trading model under the background of Global Energy Interconnection

Environmental problems caused by traditional power production and the unbalanced distribution of energy resources and demand limit the development of sustainable societies. A feasible method to optimize the resource allocation has been proposed, and it involves cross-border and cross-regional electricity transactions. However, the uncertainty of renewable energy and the specific features of the cross-border electricity market are key issues which need to be considered in the trading mechanism design. Based on this, this paper sets up a long-term cross-border electricity trading model considering the uncertainty of renewable energy. First, annual transactions are matched according to the declared data of bidders with consideration of cross-border interconnection development benefits, potential benefit risks, and transmission costs. Second, for annual contract decomposition, the model uses the minimum generation cost function with a penalty item for power shortages to allocate electricity to each month. Additionally, the scenario reduction algorithm is combined with the unit commitment to construct a stochastic generation plan. Finally, a case study of the numerical results for the multinational electricity market in northeast Asia is used to show that the proposed trading model is feasible for cross-border electricity trading with high penetration of renewable energy.     

现货市场新能源参与方式及其对市场出清价格的影响分析

在我国新一轮电力市场改革背景下,电力现货市场建设进程进一步加快.随着新能源装机的快速增长,将会对电力现货市场竞价交易带来很大影响.基于我国试点运行的现货交易机制,对现行几种新能源参与市场模式进行了分析并提出了适用于新能源快速发展阶段的市场参与机制.建立了包含新能源参与的省级日前市场机组组合模型和实时市场安全经济调度模型...     

Front Cover

The objectives of the Australian national electricity market are that it should be competitive, offer customers a choice of generators and retailers, and provide open access to the interconnected transmission and distribution network. It should not present barriers to entry, more or less favorable treatment of new entrants, bias towards a particular energy source or favoritism towards, or impediments to, intra- as opposed to inter-state trade. The core objective of the market rules, set out in the National Electricity Law and regulations and the Code, is to provide a light-handed and market-oriented regime of regulation that in turn allows the market to achieve its objectives. This article discusses the governance of the market, network planning and regulation, spot and contract markets, and supply reliability and security. To properly function the market relies on a deep and active contract market alongside the spot market and a close and dynamic relationship between spot and contract prices.     

Impact of industrial virtual power plant on renewable energy integration

An industrial park is one of the typical energy consumption schemes in power systems owing to the heavy industrial loads and their abilities to respond to electricity price changes. Therefore, energy integration in the industrial sector is significant. Accordingly, the concept of industrial virtual power plant (IVPP) has been proposed to deal with such problems. This study demonstrates an IVPP model to manage resources in an eco-industrial park, including energy storage systems, demand response (DR) resources, and distributed energies. In addition, fuzzy theory is used to change the deterministic system constraints to fuzzy parameters, considering the uncertainty of renewable energy, and fuzzy chance constraints are then set based on the credibility theory. By maximizing the daily benefits of the IVPP owners in day-ahead markets, DR and energy storage systems can be scheduled economically. Therefore, the energy between the grid and IVPP can flow in both directions: the surplus renewable electricity of IVPP can be sold in the market; when the electricity generated inside IVPP is not enough for its use, IVPP can also purchase power through the market. Case studies based on three wind-level scenarios demonstrate the efficient synergies between IVPP resources. The validation results indicate that IVPP can optimize the supply and demand resources in industrial parks, thereby decarbonizing the power systems.     

Economic assessment of virtual power plants in the German energy market — A scenario-based and model-supported analysis

The energy transition (“Energiewende”) in Germany will result in a substantial transformation of the energy supply system. Virtual power plants are expected to be important components of the new intelligent energy infrastructure. They aggregate beside different types of distributed generation units also active consumers and storage technologies in order to integrate these in a profit-maximising, system-stabilising, and sustainable way. The assessment of the economic performance of virtual power plants requires a scenario-based and model-supported analysis. In this relation, future energy market conditions are simulated using the scenario methodology. Starting from the year 2015, three scenarios have been identified that illustrate alternative energy developments in Germany by 2030. Based on these scenarios, the additional revenues potential of the modeled virtual power plant is identified when compared to an independent and non-market-oriented operation mode of distributed energy resources. According to the model results, revenues of the VPP can increase by 11% up to 30% in the analyzed scenarios in 2030 due to the market-oriented operation mode. Nevertheless, the amount and composition vary depending on technology-specific subsidies, temporary nature of power demand and price structures in the energy market. Fluctuating renewable energies are expected to benefit from the market-oriented operation mode in the virtual power plant, especially through the EEG direct marketing. The selective and regulated shutdown of renewable energies in times of negative electricity prices may lead to further cost savings. The utilization of temporary price fluctuations in the spot market and the demand-oriented provision of control power offer high additional revenue potential for flexible controllable technologies such as battery storage, biomethane as well as combined heat and power units. Finally, the determination of the long-term profitability of a virtual power plant still requires a full-scale cost–benefit analysis. For this holistic approach, the model results provide a reliable scientific basis.     

How does Germany's green energy policy affect electricity market volatility? An application of conditional autoregressive range models

Based on a dynamic model for the high/low range of electricity prices, this article analyses the effects of Germany's green energy policy on the volatility of the electricity market. Using European Energy Exchange data from 2000 to 2015, we find rather high volatility in the years 2000–2009 but also that the weekly price range has significantly declined in the period following the year 2009. This period is characterised by active regulation under the Energy Industry Law (EnWG), the EU Emissions Trading Directive (ETD) and the Renewable Energy Law (EEG). In contrast to the preceding period, price jumps are smaller and less frequent (especially for day-time hours), implying that current policy measures are effective in promoting renewable energies while simultaneously upholding electricity market stability. This is because the regulations strive towards a more and more flexible and market-oriented structure which allows better integration of renewable energies and supports an efficient alignment of renewable electricity supply with demand.     

A real options evaluation model for the diffusion prospects of new renewable power generation technologies

This study presents a policy planning model that integrates learning curve information on renewable power generation technologies into a dynamic programming formulation featuring real options analysis. The model recursively evaluates a set of investment alternatives on a year-by-year basis, thereby taking into account that the flexibility to delay an irreversible investment expenditure can profoundly affect the diffusion prospects of renewable power generation technologies. Price uncertainty is introduced through stochastic processes for the average wholesale price of electricity and for input fuel prices. Demand for electricity is assumed to be increasingly price-sensitive, as the electricity market deregulation proceeds, reflecting new options of consumers to react to electricity price changes (such as time-of-use pricing, unbundled electricity services, and choice of supplier). The empirical analysis is based on data for the Turkish electricity supply industry. Apart from general implications for policy-making, it provides some interesting insights about the impact of uncertainty and technical change on the diffusion of various emerging renewable energy technologies.     

考虑可再生能源消纳与灵活性需求的电力市场优化决策研究

可再生能源配额制与电力市场改革同步推进,电力系统灵活性需求急剧增加.为促进可再生能源的消纳,提高电力系统的灵活性,本文提出了一种电力市场双层优化决策模型.先是考虑风光负荷之间的相关性,建立了灵活性需求的概率模型;进而建立多市场主体下考虑省间-省内可再生能源和常规能源交易的双层优化模型;最后利用KKT条件和拉格朗日对偶理...     

Support schemes for renewable electricity in the European Union: Producer strategies and competition

Current discussion about how to reform European support schemes for renewable electricity neglects certain risks of market power in wholesale electricity markets. In a stylized Cournot model of interacting spot and forward electricity markets, I analyze how different price-based support schemes affect producer strategies and, ultimately, competition in the wholesale market. I compare the strategic behavior of renewable and conventional producers in terms of electricity production and forward market sales in the presence of two different price-based support schemes: feed-in tariffs and feed-in premiums. I show that the feed-in premium, which is the European Commission's current scheme of choice, may enhance market power and favor conventional electricity production. It may also reduce the likelihood of achieving the political objective to increase production from renewable energy sources.