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Solar Energy and Storage – Energy System Analysis on the use of energy storage coupled with solar technologies

机译：太阳能和储能–结合储能技术和太阳能技术的能源系统分析

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OverviewIn countries with higher solar radiation compared to Europe, e.g. countries in Middle East and North Africa (MENA), solartechnologies have become very competitive to other sources due to the falling costs. Some of these countries initiated nationalaction plans to install high shares of photovolataics (PV) in relatively short time period, which consequently leads tointegration challenges. Increasing share of renewable energy requires strategies to deal with highly fluctuating feed-in fromrenewables and subsequently novel operational strategies for the total system. Grid reinforcement and balancing of thefluctuating renewable resources are key topics.This paper analyses the role of solar technologies and their interaction with energy storage to flatten or shift the electricitygeneration by using a fundamental electricity system modelling (ENTIGRIS, www.entigris.org). The capacity expansion anddispatch model is used to analyse the role of energy storage (chemical or thermal) in combination with PV or concentratedsolar power (CSP). The analysis shows that battery prices have to be at the range of (50-100 $/kWh) to be considered as anoption for storage coupled with PV in an optimized least-cost system of about 30-35% shares of renewables. If energy storageis required in an energy system, CSP coupled with a thermal storage proves to be a cheaper solution in the energy mix. Theeconomic analysis also provides insight of the operation strategies of these energy storages.MethodsThe main objective of this study is to analyse the role of CSP and PV within an energy system with increasing renewableenergy shares. This is achieved by modelling and optimizing a least cost expansion plan of the energy system with the modelENTIGRIS. The optimization model is formulated as a linear problem. The solver compares different electricity generationand transmission technology options while minimizing the system costs of the required technology mix and infrastructure forthe electricity supply. The model optimizes the expansion and the unit-commitment in the overall power system byconsidering the grid constraints and geographical typology. The present hourly demand and long-term load projection has tobe met at all times. As the design of energy storage in capacity and volume is also optimized, their roles in the electricitysystem together with the solar technologies can therefore be analyzed. A sensitivity analysis is conducted using several batteryprices ranging from 500, 300, 200 to 100 and 50 $/kWh to test their economic feasibility. Furthermore, a sensitivity analysisis conducted with a variation of the weighted average cost of capital (WACC) to analyse the influence of governmentsubsidies and incentive programmes on CSP in order to make it more competitive againt concventional power plants.The applied version of the optimization model ENTIGRIS is amodification of the European version and covers the electricitysystem in detail [1, 2,3]. It optimizes the connection betweenthe existing conventional power plant systems with a highresolution of renewable energy generation. Figure 1 shows thegeneral input and output data of the optimization model whichoptimizes total cost for expansion planning and systemoperation over a specific time horizon (e.g. 20 years).In the model, cost and technology assumptions are includedwith relevance to the specific electricity system. Current andfuture cost assumptions are included based on current marketprices and learning curves to be able to estimate them to thefuture. Furthermore, all existing power plants are includedwith the installed capacity and geographical location in theenergy system.ResultsSolar technologies contribute a significant share in the optimal result in the long-term expansion of electricity system inregions with high radiation such as in MENA. They are competitive to all other generation technologies, if world marketprices of oil and natural gas are included in the analysis. This leads to strong increase of generation capacities on therenewable side. However, the model includes reserve margins and coverage of transmission grid which provides indepthresults on specific power system how they can react on the conventional side on the high feed-in of renewables in the system.Based on the result, CSP with thermal energy storage is the more cost effective solution of a solar technology and energystorage compared to PV plus battery, as the former is preferred to be expanded by the model in all cases. The sensitivityanalysis shows that batteries become economic feasible at prices lowers than 100$/kWh (if no other markets such as ancillaryservices, reserve or grid stability are requested and the focus is on energy shifting from day to night). A break-even levelizedcost of electricity (LCOE) of 7.8 ct/kWhel is observed for CSP with a WACC of 4% and CCGT at a fuel price of 8 $ perMillion BTU. A considerably lower LCOE of CSP is achieved by lowering the WACC further. This however would require astrong incentive programme in favour of CSP which could be achived by tax cuts or lower interest rates.Figure 2 illustrates the impact of CSP and PV operations on the overall system. In this system, only a CSP is constructed witha 8h thermal storage. No batteries in addition to the PV system was built by the model. The CSP and PV feed-in during theday leads to a high flexibility capacity in the form of CCGT, as these power plants have to decrease their output during theday. CSP and thermal storage have their highest output share in the evening when PV is not producing.ConclusionsEnergy storage with solar technologies are an upcoming solution in energy systems. Electricity systems with CSP and PVgenerators will use increasing share of energy storage when renewable share are further increased. However, thermal energystorage is economic feasible already in the next years as integration cost in a CSP plant is lower compared to chemical energystorages such as battery stacks. However, battery storage might also play a role on ancillary services and other supportiveoperation in an electricity system.
机译：概述 与欧洲相比，太阳辐射较高的国家/地区中东和北非（MENA）国家，太阳能 由于成本下降，技术已变得比其他来源更具竞争力。其中一些国家发起了国家 行动计划在相对较短的时间内安装大量光伏产品，从而导致 整合挑战。可再生能源份额的增加需要采取策略来应对来自能源市场的大幅波动 可再生能源，以及随后整个系统的新颖运营策略。电网加固与平衡 波动的可再生资源是关键主题。 本文分析了太阳能技术的作用及其与能量存储的相互作用，以使电力变平或转移 通过使用基本电力系统建模来发电（ENTIGRIS，www.entigris.org）。产能扩张和 调度模型用于分析与PV或集中式光伏结合的储能（化学或热能）的作用 太阳能（CSP）。分析显示，电池价格必须在（50-100 $ / kWh）的范围内，才能视为 在约30-35％的可再生能源份额的优化的最低成本系统中，结合光伏的存储选项。如果储能 在能源系统中是必需的，事实证明，CSP与蓄热装置相结合是一种较便宜的能源组合解决方案。这 经济分析还可以洞悉这些储能的运行策略。 方法 这项研究的主要目的是分析随着可再生能源的增加，CSP和PV在能源系统中的作用。 能源股。这是通过使用该模型对能源系统的最低成本扩展计划进行建模和优化来实现的 ENTIGRIS。优化模型被表述为线性问题。求解器比较不同的发电量 和传输技术选择，同时将所需技术组合和基础架构的系统成本降至最低 电力供应。该模型通过以下方式优化了整个电力系统中的扩展和机组组合： 考虑网格约束和地理类型。当前的每小时需求和长期负荷预测必须 随时都能见面。由于还优化了容量和容量的储能设计，因此它们在电力中的作用 因此，可以将太阳能系统与太阳能技术一起进行分析。使用几节电池进行灵敏度分析 价格从500、300、200到100和50美元/千瓦时不等，以测试其经济可行性。此外，敏感性分析 进行加权平均资本成本（WACC）的变化以分析政府的影响 对CSP的补贴和激励计划，以使其具有更大的竞争力。 优化模型ENTIGRIS的应用版本是 欧洲版的修改并涵盖了电力 系统详细[1，2,3]。它优化了之间的连接 现有的常规电厂系统具有很高的 分辨率的可再生能源发电。图1显示了 优化模型的一般输入和输出数据 优化扩展计划和系统的总成本 在特定时间范围（例如20年）内运行。 在模型中，包括了成本和技术假设 与特定的电力系统有关。当前和 根据当前市场包括未来成本假设 价格和学习曲线，以便能够将其估算为 未来。此外，包括所有现有发电厂 的装机容量和地理位置 能源系统。 结果 太阳能技术在电力系统长期扩展的最佳结果中占有重要份额。 辐射较高的区域，例如中东和北非地区。如果具有国际市场，它们将与所有其他发电技术竞争 分析中包括石油和天然气的价格。这导致了发电能力的大幅提高。 可再生的一面。但是，该模型包括备用余量和输电网的覆盖范围，从而提供了更深入的信息 结果表明，在特定的电力系统中，它们如何在传统方面对系统中可再生能源的大量馈入产生反应。 根据结果​​，具有热能存储功能的CSP是太阳能技术和能源的更具成本效益的解决方案 与PV加电池相比，它的存储空间更大，因为在所有情况下，该模型都更倾向于扩展前者。灵敏度 分析显示，电池价格低于100 $ / kWh（如果没有其他市场，例如辅助市场），则在经济上可行 服务，要求储备或电网稳定，重点是从白天到夜晚的能量转移）。收支平衡 电费（LCOE）为7.8 ct / kWhel，CSP的WACC为4％，CCGT的燃料价格为每$ 8 $ 百万英热单位。通过进一步降低WACC，可以大大降低CSP的LCOE。但是，这将需要 可以通过减税或降低利率来实现有利于CSP的强有力的激励计划。 图2说明了CSP和PV操作对整个系统的影响。在此系统中，仅使用 一个8小时的储热库。该模型未制造除PV系统以外的任何电池。 CSP和PV馈电期间 一天导致了CCGT形式的高灵活性能力，因为这些发电厂不得不在发电过程中减少其发电量。 天。在不生产PV的傍晚，CSP和蓄热装置的产量份额最高。 结论 太阳能技术的储能是能源系统中即将出现的解决方案。具有CSP和PV的电力系统 当可再生能源份额进一步增加时，发电商将使用越来越多的能源存储。但是，热能 由于CSP工厂的整合成本比化学能源更低，因此在未来几年内存储已经在经济上可行 电池堆之类的存储设备。但是，电池存储也可能对辅助服务和其他支持服务起一定作用。 在电力系统中运行。

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