基于负荷侧响应的含储热热电联产的风电消纳模型

为了有效减少弃风,提高风电消纳能力,该文从负荷侧出发,通过峰谷分时电价策略引导用户的用电方式,达到削峰填谷,优化负荷曲线的目的。同时,在传统热电联产机组中应用大容量储热装置,通过对储热环节的控制,解耦“以热定电”约束,提高系统调节能力。以系统煤耗量最低为目标,构建包含储热的热电联产机组与风电联合出力优化调度模型。该模型考虑系统中的含储热热电联产机组运行成本,同时兼顾储热、负荷侧响应与热电平衡的相关约束等因素,采用基于模拟退火的粒子群算法对模型进行求解,并利用算例比较不同模式下的结果,验证了模型的有效性。     

Integration of wind power into the British system in 2020

This paper investigates the integration of renewable electricity into the UK system in 2020. The purpose is to find the optimal wind generation that can be integrated based on total cost of supply. Using EnergyPLAN model and the Department of Energy and Climate Change (DECC) energy projections as inputs, this paper simulates the total cost of electricity supply with various levels of wind generation considering two systems: a reference and an alternative system. The results show that 80 TWh of wind electricity is most preferable in both systems, saving up to 0.9% of total cost when compared to a conventional system without wind electricity production. The alternative system, with decentralized generation and active demand management, brings relatively more cost saving, and higher wind utilisation, compared to the reference case. The sensitivity analysis with alternative fuel and capital costs again confirms the superiority of the alternative over the reference system.     

Cost‐optimized allocation of wind power investments: a Nordic–German perspective

Using a linear cost minimization model with a 1 h time resolution, we investigated the influence of geographic allocation of wind power on large‐scale wind power investments, taking into account wind conditions, distance to load, and the nature of the power system in place (i.e. power generation and transmission capacities). We employed a hypothetical case in which a 20% wind power share of total electricity demand is applied to the Nordic–German power system. Free, i.e. geographically unrestricted, allocation of new wind power capacity is compared with a case in which national planning frameworks impose national limitations on wind power penetration levels. Given the cost assumptions made in the present work, the prospect of increasing the wind power capacity factor from 20 to 30% could motivate investments in transmission capacity from northern Scandinavia to continental Europe. The results obtained using the model show that the distribution of wind farms between regions with favorable wind conditions is dependent upon two factors: (i) the extent to which existing lines can be used to transmit the electricity that results from the new wind power and (ii) the correlation for wind power generation between the exporting region and the wind power generation already in place. In addition, the results indicate that there is little difference, i.e. just over 1%, in total yearly cost between the free allocation of new wind power and an allocation that complies with national planning frameworks. However, on a national level, there are significant differences with respect to investments in transmission and wind power capacities and the replacement of conventional power generation. Copyright © 2012 John Wiley & Sons, Ltd.     

计及绿色电力证书与碳交易制度的“源-荷”协调优化调度

基于低碳电力和智能电网的背景,考虑现有的风电消纳困境,该文以绿色电力证书为基础,结合碳排放权的交易制度,同时引入需求侧高载能企业负荷的响应模型,并将虚拟电厂经济效益作为优化目标函数,建立以绿证交易为基础,结合碳交易制度和高载能需求侧响应的“源-荷”双侧互补协调优化调度模型。最后将某省份区域电网代入到该文所构建模型之中进行仿真,并采用自适应免疫疫苗算法对模型进行求解,结果表明所建立的计及绿证交易与碳交易的模型有利于促进风电消耗,降低单位发电量的碳排放。     

计及住宅混合能源需求响应的含风电系统随机优化调度

建立基于需求响应的住宅混合能源系统优化运行模型.同时,采用负荷聚合方法来集中分散的住宅需求响应能力.在电网层面,建立计及需求响应与风电的日前随机优化调度模型.最后,分别对6节点系统和IEEE-118节点系统进行仿真.仿真结果表明,6节点系统的弃风量下降77.5％,IEEE-118节点系统的住宅能源成本、电力系统运行成本...     

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

The North Atlantic Oscillation (NAO) is a large-scale atmospheric circulation pattern driving climate variability in north-western Europe. As the deployment of wind-powered generation expands on electricity networks across Europe, the impacts of the NAO on the electricity system will be amplified. This study assesses the impact of the NAO, via wind-power generation, on the electricity market considering thermal generation costs, wholesale electricity prices and wind generation subsidies. A Monte Carlo approach is used to model NAO phases and generate hourly wind speed time-series data, electricity demand and fuel input data. A least-cost unit commitment and economic dispatch model is used to simulate an island electricity system, modelled on the all-island Irish electricity system. The impact of the NAO obviously depends on the level of wind capacity within an electricity system. Our results indicate that on average a switch from negative to positive NAO phase can reduce thermal generation costs by up to 8%, reduce wholesale electricity prices by as much as €1.5/MWh, and increase wind power generators' revenue by 12%.     

世界风力发电现状与前景预测

全球可再生能源发电装机容量中风电占有压倒性优势,今后可望成为欧洲、亚洲、北美的主要电力来源.2011年中国以62GW的累计装机容量蝉联世界第一,按照我国“十二五”规划目标,预计到2015年风电装机容量将达到1×108kW,年发电量1900×108kW·h.GWEC和Greenpeace预测,今后20年风力发电将成为世界主力电源,2030年装机容量有可能达到23×108kW,可供应世界电力需求的22％.欧美正大力开发海上风电产业.欧洲是世界海上风电发展的先驱和产业中心,欧洲企业不仅拥有自己的核心技术,而且还向世界各地输出技术,今后欧洲海上风力发电将急速增长.美国采取与英国、德国等欧洲厂家相同的战略,大力发展海上风力发电.我国海上风电产业刚刚起步,预计2015年海上风电装机500×104kW.日本学者大岛教授推算了不同电源的发电成本:包括政府财政补贴,运行年限30年的核电站发电成本为12.06日元/(kW·h);按标准设备利用率,风力发电成本11.30日元/(kW·h),与核电相比已经有竞争力.假设风况好时设备利用率达到35％,发电成本为7.95日元/(kW·h),比核电低得多.     

Optimizing hybrid offshore wind farms for cost-competitive hydrogen production in Germany

Nearly 96% of the world's current hydrogen production comes from fossil-fuel-based sources, contributing to global greenhouse gas emissions. Hydrogen is often discussed as a critical lever in decarbonizing future power systems. Producing hydrogen using unsold offshore wind electricity may offer a low-carbon production pathway and emerging business model. This study investigates whether participating in an ancillary service market is cost competitive for offshore wind-based hydrogen production. It also determines the optimal size of a hydrogen electrolyser relative to an offshore wind farm. Two flexibility strategies for offshore wind farms are developed in this study: an optimal bidding strategy into ancillary service markets for offshore wind farms that build hydrogen production facilities and optimal sizing of Power-to-Hydrogen (PtH) facilities at wind farms. Using empirical European power market and wind generation data, the study finds that offshore-wind based hydrogen must participate in ancillary service markets to generate net positive revenues at current levels of wind generation to become cost competitive in Germany. The estimated carbon abatement cost of “green” hydrogen ranges between 187 EUR/tonCO₂e and 265 EUR/tonCO₂e. Allowing hydrogen producers to receive similar subsidies as offshore wind farms that produce only electricity could facilitate further cost reduction. Utilizing excess and intermittent offshore wind highlights one possible pathway that could achieve increasing returns on greenhouse gas emission reductions due to technological learning in hydrogen production, even under conditions where low power prices make offshore wind less competitive in the European electricity market.     

A comparison of variation management strategies for wind power integration in different electricity system contexts

Variation management strategies improve the capability of the electricity system to meet variations both in the electricity demand and in the generation that relies on variable energy sources. In this work, we introduce a new, functionality‐based, categorization of variation management strategies: shifting (eg, batteries), absorbing (eg, power‐to‐gas), and complementing (dispatchable generation, including reservoir hydropower) strategies. A dispatch model with European coverage (EU‐27 plus Norway and Switzerland) is applied to compare the benefits of shifting and absorbing strategies on wind integration in regions with different amounts of complementing strategies in place. The benefits are measured in terms of the wind value factor, wind owner revenue, and average short‐term generation cost. The results of the modeling show that the reduction in average short‐term generation cost and the increase in revenue earned by the wind owner from shifting strategies, such as the use of batteries, are more substantial at low wind shares than at high wind shares. The opposite situation is found for absorbing strategies, such as power‐to‐gas, which are found to be more efficient at reducing the average generation cost and increasing profit for the wind owner as the wind share increases. In regions that have access to complementing strategies in the form of reservoir hydropower, variation management has a weak ability to reduce the average short‐term generation cost, although it can increase significantly the revenue accrued by the wind power owner.     

How does market power affect the impact of large scale wind investment in 'energy only' wholesale electricity markets?

In the short run, it is well known that increasing wind penetration is likely to reduce spot market electricity prices due to the merit order effect. The long run effect is less clear because there will be a change in new capacity investment in response to the wind penetration. In this paper we examine the interaction between capacity investment, wind penetration and market power by first using a least-cost generation expansion model to simulate capacity investment with increasing amounts of wind generation, and then using a computer agent-based model to predict electricity prices in the presence of market power. We find the degree to which firms are able to exercise market power depends critically on the ratio of capacity to peak demand. For our preferred long run generation scenario we show market power increases for some periods as wind penetration increases however the merit order counteracts this with the results that prices overall remain flat. Returns to peakers increase significantly as wind penetration increases. The market power in turn leads to inefficient dispatch which is exacerbated with large amounts of wind generation.     

Energy‐cost‐aware flow shop scheduling considering intermittent renewables,energy storage,and real‐time electricity pricing

The industrial sector is one of the major energy consumers that contribute to global climate change. Demand response programs and on‐site renewable energy provide great opportunities for the industrial sector to both go green and lower production costs. In this paper, a 2‐stage stochastic flow shop scheduling problem is proposed to minimize the total electricity purchase cost. The energy demand of the designed manufacturing system is met by on‐site renewables, energy storage, as well as the supply from the power grid. The volatile price, such as day‐ahead and real‐time pricing, applies to the portion supplied by the power grid. The first stage of the formulated model determines optimal job schedules and minimizes day‐ahead purchase commitment cost that considers forecasted renewable generation. The volatility of the real‐time electricity price and the variability of renewable generation are considered in the second stage of the model to compensate for errors of the forecasted renewable supply; the model will also minimize the total cost of real‐time electricity supplied by the real‐time pricing market and maximize the total profit of renewable fed into the grid. Case study results show that cost savings because of on‐site renewables are significant. Seasonal cost saving differences are also observed. The cost saving in summer is higher than that in winter with solar and wind supply in the system. Although the battery system also contributes to the cost saving, its effect is not as significant as the renewables.     

Identification of reservation capacity in critical peak pricing electricity demand response program for sustainable manufacturing systems

Electricity demand response is considered an effective approach to balance the electricity demand and supply with existing infrastructure of generation, transmission, and distribution. A majority of existing literature on the electricity demand response has mainly centered on the commercial and residential building sectors while the application for the industrial sector is largely neglected. This paper presents a methodology for the application of a typical demand response program, Critical Peak Pricing (CPP) program, for the manufacturing enterprises. The configuration of the reservation capacity (in kilowatt, kW) in the CPP program, which plays a critical role in the cost of the final bill charge, will be identified by optimal production scheduling for the typical manufacturing systems with multiple machines and buffers. Mixed Integer Nonlinear Programming formulation is used to establish the mathematical model with the objective to minimize the electricity bill cost as well as the potential penalty cost due to the non‐fulfillment of the target production. An approximate technique is introduced to find a near optimal solution, and a numerical case study is used to illustrate the effectiveness of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

Distributed generation integrated with thermal unit commitment considering demand response for energy storage optimization of smart grid

This paper deals with an optimal battery energy storage capacity for the smart grid operation. Distributed renewable generator and conventional thermal generator are considered as the power generation sources for the smart grid. Usually, a battery energy storage system (BESS) is used to satisfy the transmission constraints but installation cost of battery energy storage is very high. Sometimes, it is not possible to install a large capacity of the BESS. On the other hand, the competition of the electricity market has been increased due to the deregulation and liberalization of the power market. Therefore, the power companies are required to reduce the generation cost in order to maximize the profit. In this paper, a thermal units commitment program considers the demand response system to satisfy the transmission constraints. The BESS capacity can be reduced by the demand response system. The electric vehicle (EV) and heat pump (HP) in the smart house are considered as the controllable loads of the demand side. The effectiveness of the proposed method is validated by extensive simulation results which ensure the reduction of BESS capacity and power generation cost, and satisfy the transmission constraints.     

A spatial and temporal correlation analysis of aggregate wind power in an ideally interconnected Europe

Studies have shown that a large geographic spread of installed capacity can reduce wind power variability and smooth production. This could be achieved by using electricity interconnections and storage systems. However, interconnections and storage are not totally flexible, so it is essential to understand the wind power correlation in order to address power system constraints in systems with large and growing wind power penetrations. In this study, the spatial and temporal correlation of wind power generation across several European Union countries was examined to understand how wind ‘travels’ across Europe. Three years of historical hourly wind power generation data from 10 countries were analysed. The results of the analysis were then compared with two other studies focused on the Nordic region and the USA. The findings show that similar general correlation characteristics do exist between European country pairs. This is of particular importance when planning and operating interconnector flows, storage optimization and cross‐border power trading. Copyright © 2017 The Authors Wind Energy Published by John Wiley & Sons Ltd     

Exploring the impact on cost and electricity production of high penetration levels of intermittent electricity in OECD Europe and the USA,results for wind energy

In this study we explore for the USA and OECD Europe (OECD Europe includes the countries that participate in the Organisation of Economic Cooperation and Development, among which Western Europe, USA and Japan) dynamic changes in electricity production, cost and CO₂ emissions when intermittent electricity sources are used with increasing penetration levels. The methodology developed can be applied for both solar photovoltaic (PV) and wind energy. Here the focus of the results is on penetration of wind electricity in the electricity system as simulated in a long-term model experiment in which the electricity demand is kept constant over time. All important parameter are included in a sensitivity analysis. With increasing penetration levels the cost reduction of wind electricity caused by upscaling and technological learning is counteracted by the cost increase due to (1) the need for additional back-up capacity, (2) the need to generate wind electricity at less favourable sites, and (3) discarded wind electricity because of supply–demand mismatch. This occurs after about 20% wind electricity production as percentage of current electricity production. At this level about 500 (OECD Europe) and 750 (USA) TWh yr⁻¹ wind electricity is absorbed in the system with the electricity demand of the year 2000. Wind electricity is found to be discarded when the production is about 55 (USA) to 10 times (OECD Europe) the present electricity produced from wind power. Beyond 30% of present electricity production, cost increases most significantly because of discarded wind electricity, excluding storage. In both regions the use of wind electricity would mainly avoid use of natural gas. The CO₂ emissions abatement costs range from 14 (OECD Europe) to 33 (USA) $ per ton CO₂ differ in both regions due to a faster wind electricity cost increase in OECD Europe.     

Green hydrogen for heating and its impact on the power system

With a relatively high energy density, hydrogen is attracting increasing attention in research, commercial and political spheres, specifically as a fuel for residential heating, which is proving to be a difficult sector to decarbonise in some circumstances. Hydrogen production is dependent on the power system so any scale use of hydrogen for residential heating will impact various aspects of the power system, including electricity prices and renewable generation curtailment (i.e. wind, solar). Using a linearised optimal power flow model and the power infrastructure on the island of Ireland this paper examines least cost optimal investment in electrolysers in the presence of Ireland's 70% renewable electricity target by 2030. The introduction of electrolysers in the power system leads to an increase in emissions from power generation, which is inconsistent with some definitions of green hydrogen. Electricity prices are marginally higher with electrolysers whereas the optimal location of electrolysers is driven by a combination of residential heating demand and potential surplus power supplies at electricity nodes.     

Representation of variable renewable energy sources in TIMER,an aggregated energy system simulation model

The power system is expected to play an important role in climate change mitigation. Variable renewable energy (VRE) sources, such as wind and solar power, are currently showing rapid growth rates in power systems worldwide, and could also be important in future mitigation strategies. It is therefore important that the electricity sector and the integration of VRE are correctly represented in energy models. This paper presents an improved methodology for representing the electricity sector in the long-term energy simulation model TIMER using a heuristic approach to find cost optimal paths given system requirements and scenario assumptions. Regional residual load duration curves have been included to simulate curtailments, storage use, backup requirements and system load factor decline as the VRE share increases. The results show that for the USA and Western Europe at lower VRE penetration levels, backup costs form the major VRE cost markup. When solar power supplies more than 30% of the electricity demand, the costs of storage and energy curtailments become increasingly important. Storage and curtailments have less influence on wind power cost markups in these regions, as wind power supply is better correlated with electricity demand. Mitigation scenarios show an increasing VRE share in the electricity mix implying also increasing contribution of VRE for peak and mid load capacity. In the current scenarios, this can be achieved by at the same time installing less capital intensive gas fired power plants. Sensitivity analysis showed that greenhouse gas emissions from the electricity sector in the updated model are particularly sensitive to the availability of carbon capture and storage (CCS) and nuclear power and the costs of VRE.     

Determining optimal electricity technology mix with high level of wind power penetration

Notwithstanding its variability and limited controllability, wind power is expected to contribute strongly to electricity generation from renewable energy sources in the coming decades. Treating wind power as non-dispatchable by subtracting its output from the original load profile, results in a net load profile, which must be covered by conventional power generation. The screening curve methodology is a first approximation to find the optimal generation technology mix, based on relative cost levels. However, increased variability of the net load profile, due to wind power generation, strongly influences system operation. Therefore a static linear programming investment model is developed to determine the optimal technology mix. This alternative methodology shows a reduced capacity of inflexible generation after including operational constraints to properly account for net load variability. In order to illustrate this methodology, an example is set up, showing the sensitivity with respect to ramp rates of conventional generation, transmission interconnection and energy storage. The comparison of those different sources of system flexibility suggests that energy storage facilities better facilitate the integration of wind power generation.     

Wind hybrid electrical supply system: behaviour simulation and sizing optimization

Using a global approach, a wind hybrid system operation is simulated and the evolution of several parameters is analysed, such as the wasted energy, the fuel consumption and the role of the wind turbine subsystem in the global production. This analysis shows that all the energies which take part in the system operation are more dependent on the wind turbine size than on the battery storage capacity. A storage of 2 or 3 days is sufficient, because an increase in storage beyond these values does not have a notable impact on the performance of the wind hybrid system. Finally, a cost study is performed to determine the optimal configuration of the system conducive to the lowest cost of electricity production. Copyright © 2001 John Wiley & Sons, Ltd.     

Design for renewable energy systems with application to rural areas in Japan

This study uses optimization modeling to study efficient ways to integrate renewable energy systems to provide electricity and heat in rural Japan. The model provides minimum cost system configuration and operation taking into account hour-by-hour energy availability and demand. Grid electricity is available to rural areas of Japan, but it is relatively expensive. Local renewable energy generation can be economic while using grid electricity to compensate for the intermittency of the renewable generation. In the model, renewable electricity can be provided by a combination of wind, photovoltaic, and biomass. Heat can be provided by petroleum, LPG, and geothermal heat pumps (GHPs). We find that due to the relatively high cost of grid electricity, there is significant penetration of wind generation. In turn, the penetration of wind creates economic conditions that encourage GHP penetration. The integrated renewable system reduces the annual cost of the entire system by 31%, and reduces the carbon emissions by 50%.