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Optimizing storage capacity in 100 % renewable electricity supply: A GIS-based approach for Italy 在100%可再生电力供应中优化存储容量：意大利基于gis的方法

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-05-01 Epub Date: 2025-02-03 DOI: 10.1016/j.segy.2025.100177

Vittoria Battaglia , Aseed Ur Rehman , Laura Vanoli

The sustainability of energy systems relies on the integration of renewable local sources. This study aimed to optimize Italy's electricity supply by leveraging a hybrid PV-wind energy system, employing advanced optimization techniques. The primary goal was pinpointing the minimum storage capacity necessary for Italy's power grid in a scenario completely reliant on PV and wind energy. To achieve this, the potential of both PV and wind energy was evaluated through a GIS-based analysis, while dynamic simulation was used to estimate power generation across regions. The Mixed-integer linear programming algorithm underwent a three-step process: computing the hourly residual load for diverse PV and wind capacity combinations, determining the hourly storage requirements and ultimately identifying the mix with the least storage capacity. Applying Mixed-integer linear programming to Italy's complete PV and wind energy potential revealed a necessity for 33 TWh of storage capacity. To decrease the required storage capacity, two new scenarios were proposed: the island scenario, in which the total annual electricity production from solar and wind energy is equal to the annual electricity demand, and the peak hour scenario, where generation from PV and wind is matched to the consumption in peak hour electric demand. The economic analysis of the proposed scenarios shows that although hydrogen can be used to store enormous amounts of energy, the inefficiencies in the conversion processes make it less cost-effective compared to other technologies. Pumped-hydro storage is the most cost-effective option for energy storage. The results show that the most economically viable scenario is the island scenario with an optimal mix of 16.9 % PV and 83.1 % wind, requiring a storage capacity of 7.04 TWh and a 3.34 trillion euro investment for pump-hydro storage.

能源系统的可持续性依赖于当地可再生能源的整合。本研究旨在通过采用先进的优化技术，利用混合光伏-风能系统来优化意大利的电力供应。主要目标是在完全依赖光伏和风能的情况下，确定意大利电网所需的最小存储容量。为了实现这一目标，通过基于gis的分析评估了光伏和风能的潜力，同时使用动态模拟来估计区域间的发电量。混合整数线性规划算法经历了三个步骤：计算不同光伏和风能容量组合的每小时剩余负荷，确定每小时存储需求，最终确定存储容量最小的组合。将混合整数线性规划应用于意大利完整的光伏和风能潜力，发现需要33太瓦时的存储容量。为了减少所需的存储容量，提出了两种新的情景：孤岛情景，其中太阳能和风能的年总发电量等于年电力需求；高峰时段情景，其中光伏和风能的发电量与高峰时段电力需求的消费量相匹配。对提议方案的经济分析表明，尽管氢可以用来储存大量的能量，但与其他技术相比，转换过程中的低效率使其成本效益较低。抽水蓄能是能源储存最具成本效益的选择。结果表明，经济上最可行的方案是岛屿方案，其最佳组合为16.9%的光伏和83.1%的风能，需要7.04太瓦时的存储容量和3.34万亿欧元的抽水蓄能投资。

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引用次数: 0

Exploring the advantages of a multi-year-adaptive approach on cost-optimal long-term mini-grid design under different demand evolution scenarios 探讨不同需求演变情景下，多年自适应方法在成本最优长期微电网设计中的优势

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-05-01 Epub Date: 2025-02-28 DOI: 10.1016/j.segy.2025.100178

Milky Ali Gelchu , Jimmy Ehnberg , Dereje Shiferaw , Erik O. Ahlgren

Mini-grids are essential for rural electrification in sub-Saharan Africa, but due to uncertainty about future demand evolution in non-electrified communities, cost-optimal long-term sizing and design is particularly difficult. Standard, non-adaptive design approaches single-year and multi-year, are highly susceptible to demand evolution uncertainties. Despite potentially great advantages there is a lack of studies investigating adaptive design approaches. Thus, this study, using particle swarm optimization, explores the advantages of a multi-year-adaptive approach on cost-optimal long-term solar PV mini-grid component sizing under three demand evolution scenarios, considering the impacts of load flexibility, varying discount rates, and potential future mini-grid component cost reductions. The results show that the multi-year-adaptive approach helps to manage demand evolution challenges. It leads to significant cost-savings, up to three-quarters, in higher demand evolution scenarios, compared to multi-year and single-year approaches. These cost-savings increase with load flexibility (up to 4 % with 10 % flexibility), higher discount rates (up to 9.4 % with rates from 7 % to 20 %), and component cost reductions (up to 3.6 % per 1 % reduction). The study demonstrates how an adaptive approach can be utilized to optimize mini-grid component sizing and enhance cost efficiency.

迷你电网对于撒哈拉以南非洲地区的农村电气化至关重要，但由于非电气化社区未来需求演变的不确定性，成本最优的长期规模和设计尤其困难。标准的、非自适应的设计方法是单年和多年的，非常容易受到需求演变不确定性的影响。尽管具有潜在的巨大优势，但缺乏对适应性设计方法的研究。因此，本研究采用粒子群优化方法，在三种需求演变情景下，考虑负载灵活性、不同贴现率和未来潜在的微网组件成本降低的影响，探讨了多年自适应方法在成本最优的长期太阳能光伏微网组件规模上的优势。结果表明，多年自适应方法有助于管理需求演变的挑战。与多年和单年方法相比，在更高的需求演变场景中，它可以节省高达四分之三的成本。这些成本节约增加了负载灵活性（10%的灵活性可达4%），更高的折扣率（从7%到20%的折扣率可达9.4%），以及组件成本降低（每降低1%可达3.6%）。该研究展示了如何利用自适应方法来优化微型电网组件大小并提高成本效率。

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引用次数: 0

Smart flexibility in energy communities: Scenario-based analysis of distribution grid implications and economic impacts 能源社区的智能灵活性：基于场景的配电网影响和经济影响分析

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-05-01 Epub Date: 2025-06-05 DOI: 10.1016/j.segy.2025.100184

Magnus Askeland, Sigurd Bjarghov, Rubi Rana, Andrei Morch, Henning Taxt

The transition of the power system towards increased renewable energy generation necessitates enhanced flexibility at all system levels, especially within distribution grids. This study investigates the integration of Energy Communities (ECs) as a potential strategy to manage consumer-level flexibility within the context of Norwegian distribution grids. An equilibrium model is developed to analyse both implicit and explicit flexibility activation mechanisms to investigate potential strategies for distribution grid operators (DSOs) and assess the interactions between different stakeholders. The scenarios are evaluated based on their impact on peak load reduction, cost efficiency, and grid usage. Results from a Norwegian case study show that EC flexibility activation can reduce total system costs by 1.8% while lowering peak grid capacity needs by 13.1%. These reductions contribute to mitigating distribution grid congestion and deferring costly infrastructure reinforcements. Although derived from a specific geographical context, the findings offer valuable insights applicable to other regions with similar grid conditions and regulatory frameworks. The study concludes that combining active DSO strategies with local coordination in ECs enhances the cost-efficiency of flexibility activation, though careful consideration of pricing structures is necessary to realise the potential while preventing unintended consequences. Our scenario-based framework illustrates the potential of smart flexibility activation mechanisms to optimise grid operations, reduce peak loads, and enhance cost-efficiency. Key challenges and prerequisites to overcome them are also highlighted. By integrating advanced flexibility mechanisms and leveraging local market coordination, this study underscores the role of energy communities in accelerating the transition to decentralised smart energy systems.

电力系统向增加可再生能源发电的过渡需要在所有系统级别，特别是在配电网内提高灵活性。本研究调查了能源社区（ec）的整合作为在挪威配电网背景下管理消费者级灵活性的潜在策略。建立了一个均衡模型来分析隐式和显式柔性激活机制，以研究配电网运营商（dso）的潜在策略，并评估不同利益相关者之间的相互作用。这些场景是根据它们对峰值负载减少、成本效率和电网使用的影响来评估的。挪威的一个案例研究结果表明，EC灵活性激活可以将系统总成本降低1.8%，同时将电网峰值容量需求降低13.1%。这些减少有助于缓解配电网拥堵和推迟昂贵的基础设施加固。尽管研究结果来自特定的地理环境，但它为具有类似电网条件和监管框架的其他地区提供了有价值的见解。该研究的结论是，将主动DSO策略与ec中的本地协调相结合，可以提高灵活性激活的成本效益，尽管需要仔细考虑定价结构，以实现潜力，同时防止意外后果。我们基于场景的框架说明了智能灵活性激活机制在优化电网运行、降低峰值负荷和提高成本效益方面的潜力。报告还强调了主要挑战和克服这些挑战的先决条件。通过整合先进的灵活机制和利用当地市场协调，本研究强调了能源社区在加速向分散式智能能源系统过渡中的作用。

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引用次数: 0

Long-term energy scenario ranking with MCDA analysis: The case of Reunion Island 基于MCDA分析的长期能源情景排序：留尼旺岛案例

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-02-01 Epub Date: 2024-12-12 DOI: 10.1016/j.segy.2024.100171

Dominique Grondin , Chao Tang , Andrew Barney , Agnès François , Heracles Polatidis , Michel Benne , Béatrice Morel

Island territories rely heavily on fossil fuel resources, and transitioning to other energy sources is essential for their progress. To accomplish this, it is imperative to utilize local renewable energy sources. In this study, an analysis of energy planning for Reunion Island has been conducted where Multi-Criteria Decision Analysis (MCDA) methodologies have been used to evaluate the sustainability of energy scenarios for 2050. This evaluation is carried out considering criteria encompassing technical, economic, environmental, and social aspects of the scenarios. Further, perspectives of local actors were considered in the evaluation of these criteria. The results indicate that the greenhouse gas emissions and job creation criteria are considered to be of utmost significance, whilst technical criteria were regarded as the least significant by these local stakeholders. PROMETHEE II and TOPSIS MCDA analysis reveal that the Combined scenario, a scenario where all local energy resources are exploited to their maximum, is the preferred electricity generation scenario. The findings are used to formulate policy recommendations for island planners, helping them to adjust the island's current energy strategies. This study also serves as a valuable resource for other non-interconnected islands undergoing an energy transition.

岛屿领土严重依赖矿物燃料资源，向其他能源过渡对其进展至关重要。为了实现这一目标，必须利用当地的可再生能源。在这项研究中，对留尼旺岛的能源规划进行了分析，其中使用了多标准决策分析（MCDA）方法来评估2050年能源情景的可持续性。这项评估是根据技术、经济、环境和社会方面的标准进行的。此外，在评价这些标准时还考虑了当地行动者的观点。结果表明，温室气体排放和创造就业的标准被认为是最重要的，而技术标准被这些地方利益相关者认为是最不重要的。PROMETHEE II和TOPSIS MCDA分析表明，所有当地能源资源被最大限度利用的组合方案是首选的发电方案。研究结果被用来为岛屿规划者制定政策建议，帮助他们调整该岛目前的能源战略。这项研究也为其他正在经历能源转型的非互联岛屿提供了宝贵的资源。

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引用次数: 0

A data-based comparison of methods for reducing the peak flow rate in a district heating system 基于数据的降低区域供热系统峰值流量方法比较

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-02-01 Epub Date: 2024-11-30 DOI: 10.1016/j.segy.2024.100168

Felix Agner , Ulrich Trabert , Anders Rantzer , Janybek Orozaliev

This work concerns reduction of the peak flow rate of a district heating grid, a key system property which is bounded by pipe dimensions and pumping capacity. The peak flow rate constrains the number of additional consumers that can be connected, and may be a limiting factor in reducing supply temperatures when transitioning to the 4th generation of district heating. We evaluate a full year of operational data from a subset of customer meters in a district heating system in Germany. We consider the peak flow rate reduction that could be achieved with full a posteriori knowledge of this data. Three strategies for reducing the peak flow rate are investigated: A load shifting demand response strategy, an upper limitation in substation return temperatures, and an upper limitation on each substation’s volume flow rate. We show that imposing up to 18 % load flexibility for the customers provides an equal reduction in the peak system flow rate under the load shifting strategy. The limited return temperature strategy is less efficient at curtailing the peak flow rate, but provides an overall reduction of volume flow rates. Finally, the flow rate limitation method can introduce new, higher flow rate peaks, reducing performance.

这项工作涉及降低区域供热网的峰值流量，这是一个受管道尺寸和抽水能力限制的关键系统属性。峰值流量限制了可以连接的额外消费者的数量，并且可能是过渡到第四代区域供热时降低供应温度的限制因素。我们评估了德国区域供热系统中客户仪表子集的全年运行数据。我们考虑峰值流量的降低，可以实现与充分的后验知识的数据。研究了降低峰值流量的三种策略：负荷转移需求响应策略、变电站返回温度上限和每个变电站体积流量上限。我们表明，在负荷转移策略下，为客户施加高达18%的负荷灵活性可提供相等的峰值系统流量降低。限制回流温度策略在降低峰值流量方面效率较低，但总体上降低了体积流量。最后，流量限制方法会引入新的、更高的流量峰值，降低性能。

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引用次数: 0

Power grid operation in distribution grids with convolutional neural networks 基于卷积神经网络的配电网运行

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-02-01 Epub Date: 2024-12-09 DOI: 10.1016/j.segy.2024.100169

Manuela Linke, Tobias Meßmer, Gabriel Micard, Gunnar Schubert

The efficient and reliable operation of power grids is of great importance for ensuring a stable and uninterrupted supply of electricity. Traditional grid operation techniques have faced challenges due to the increasing integration of renewable energy sources and fluctuating demand patterns caused by the electrification of the heat and mobility sector. This paper presents a novel application of convolutional neural networks in grid operation, utilising their capabilities to recognise fault patterns and finding solutions. Different input data arrangements were investigated to reflect the relationships between neighbouring nodes as imposed by the grid topology. As disturbances we consider voltage deviations exceeding 3% of the nominal voltage or transformer and line overloads. To counteract, we use tab position changes of the transformer stations as well as remote controllable switches installed in the grid. The algorithms are trained and tested on a virtual grid based on real measurement data. Our models show excellent results with test accuracy of up to 99.06% in detecting disturbances in the grid and suggest a suitable solution without performing time-consuming load flow calculations. The proposed approach holds significant potential to address the challenges associated with modern grid operation, paving the way for more efficient and sustainable energy systems.

电网的高效、可靠运行对保证电力的稳定、不间断供应具有重要意义。由于可再生能源的日益一体化以及热能和机动部门电气化造成的需求模式波动，传统的电网运行技术面临挑战。本文介绍了卷积神经网络在电网运行中的新应用，利用其识别故障模式和寻找解决方案的能力。研究了不同的输入数据安排，以反映网格拓扑所施加的相邻节点之间的关系。作为干扰，我们考虑电压偏差超过标称电压的3%或变压器和线路过载。为了抵消这种影响，我们利用了变电站标签位置的变化以及电网中安装的遥控开关。在基于实际测量数据的虚拟网格上对算法进行了训练和测试。我们的模型在检测电网扰动方面显示出优异的结果，测试精度高达99.06%，并提出了一个合适的解决方案，而无需进行耗时的负荷流计算。提出的方法在解决与现代电网运行相关的挑战方面具有巨大的潜力，为更高效和可持续的能源系统铺平了道路。

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引用次数: 0

Optimizing solar energy integration in Tallinn's district heating and cooling systems 优化塔林地区供热和制冷系统中的太阳能集成

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-02-01 Epub Date: 2024-11-13 DOI: 10.1016/j.segy.2024.100166

K. Lepiksaar , G.-M. Kajandi , S. Sukumaran , I. Krupenski , T. Kirs , A. Volkova

Using solar energy is one way to integrate sustainable, clean and non-combustional energy to energy mix. In electricity sector, the share of solar energy has significantly grown over the last decade because of increased public awareness, declining costs and government incentives. However, the adoption of solar energy in heating and cooling sector is relatively new. There is a visible relation between solar energy production curves and cooling energy consumption curves which indicates that using solar energy in cooling sector would be efficient way to use solar energy. Still, the utilisation of solar heat for district cooling remains a grey area. In district heating and cooling sector, the use of solar energy in Estonia has been modest so far, although there is a significant solar energy potential. Hence, Tallinn district heating and cooling system has been chosen as a case study to investigate how solar energy can be used most beneficially and efficiently. In this regard, three main integration scenarios with respect to the different technical configurations and energy transformations are analysed. It was observed that the proposed solar park could generate 27.58 GWh thermal energy per annum. The share of useful solar energy (or solar fraction) reached more than 98.5 %, when TES integration is considered. From the analysed scenarios, it can be concluded that integration of TES is highly important to tap solar heat to the fullest. The seasonal match between load and generation contributed to higher share of solar energy for district cooling than district heating. This study is expected to be useful reference material for project developers, investors and policy makers.

利用太阳能是将可持续、清洁和非燃烧能源纳入能源组合的一种方式。在过去十年中，由于公众意识的提高、成本的下降和政府的激励措施，太阳能在电力行业所占的比例大幅增长。然而，太阳能在供热和制冷领域的应用相对较新。太阳能生产曲线与制冷能耗曲线之间存在明显的关系，这表明在制冷领域使用太阳能是一种有效的太阳能利用方式。然而，在区域冷却中利用太阳能热能仍然是一个灰色地带。在地区供暖和制冷部门，尽管太阳能潜力巨大，但爱沙尼亚迄今为止对太阳能的利用还很有限。因此，塔林地区供热和冷却系统被选为案例研究，以调查如何最有益、最高效地利用太阳能。在这方面，分析了不同技术配置和能源转换的三种主要集成方案。据观察，拟建的太阳能公园每年可产生 27.58 千兆瓦时的热能。如果考虑到 TES 集成，有用太阳能的比例（或太阳能部分）将超过 98.5%。从分析的方案中可以得出结论，要充分利用太阳能热能，集成热ES非常重要。负荷与发电量之间的季节性匹配使得太阳能在区域供冷中的比例高于区域供热。本研究有望成为项目开发商、投资者和政策制定者的有用参考资料。

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引用次数: 0

Advancements in smart energy system operation and planning 智慧能源系统运行与规划研究进展

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-02-01 DOI: 10.1016/j.segy.2025.100176

Vladimir Z. Gjorgievski , Brian Vad Mathiesen

Effective decarbonization depends on the use integrated approaches that coordinate technologies, markets, and energy sectors. Tackling energy challenges in isolation often results in inefficiencies and missed opportunities, whereas holistic approaches like Smart Energy Systems enable sector coupling across electricity, heating, cooling, and transport to enhance cost-effectiveness and overall efficiency. This editorial introduces the Special Issue dedicated to 8th International Conference on Smart Energy Systems, held in September 2022 in Aalborg, Denmark. The featured contributions address key topics such as system-edge control solutions, optimization strategies, waste heat integration, and the development of decentralized, scalable energy solutions. Together, these works highlight innovative approaches to managing the technical, economic, and operational complexities of the energy transition while supporting global decarbonization goals.

有效的脱碳取决于采用协调技术、市场和能源部门的综合方法。孤立地应对能源挑战往往会导致效率低下和错失机会，而智能能源系统等整体方法可以实现电力、供暖、制冷和运输等部门的耦合，从而提高成本效益和整体效率。这篇社论介绍了2022年9月在丹麦奥尔堡举行的第八届智能能源系统国际会议的特刊。特色贡献涉及关键主题，如系统边缘控制解决方案，优化策略，废热集成，以及分散的，可扩展的能源解决方案的发展。总之，这些工作突出了管理能源转型的技术、经济和运营复杂性的创新方法，同时支持全球脱碳目标。

引用次数: 0

Optimization of baseload electricity and hydrogen services by renewables for a nuclear-sized district in South Italy 优化南意大利核电区的基荷电力和可再生能源制氢服务

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-02-01 Epub Date: 2024-11-19 DOI: 10.1016/j.segy.2024.100165

Luigi Moccia

We present an optimization model of an energy district in South Italy that supplies baseload electricity and hydrogen services. The district is sized such that a nuclear reactor could provide these services. We define scenarios for 2050 to explore the system effects of discount rate sensitivity, vetoes on technologies, and cost uncertainties. We address the following issues relevant to decarbonization in South Italy: land-based wind and solar vs. exclusive solar rooftop, extra cost of a veto on nuclear, conservative assumptions on future storage technology and the role of pumped hydro storage, lack of low-cost geological storage of hydrogen and the industrial competitiveness of this carrier, and the methanation synergy with the agroforestry sector. Our results quantify the high system cost of vetoes on land-based wind and solar. Nuclear may enter the optimal mix only with a veto against onshore wind and a hypothesis of equal project risk, hence an equal discount rate, with renewables. Scenarios with land-based wind and solar obtain low-cost hydrogen and thus allow industrial uses for this carrier. The methanation synergy with the agroforestry sector does not offer a system cost advantage but improves the district’s configuration. The extra cost of full decarbonization relative to unregulated fossil gas is small with land-based wind and solar, and significant with vetoes to these technologies.

我们介绍了南意大利一个能源区的优化模型，该能源区提供基荷电力和氢气服务。该地区的规模决定了核反应堆可以提供这些服务。我们定义了 2050 年的情景，以探索贴现率敏感性、技术否决权和成本不确定性对系统的影响。我们探讨了与南意大利去碳化相关的以下问题：陆基风能和太阳能与专用太阳能屋顶、否决核能的额外成本、对未来存储技术的保守假设和抽水蓄能的作用、缺乏低成本氢气地质存储和这种载体的工业竞争力，以及甲烷化与农林业的协同作用。我们的结果量化了否决陆基风能和太阳能的高系统成本。只有在否决陆上风能，并假设与可再生能源的项目风险相等，即贴现率相等的情况下，核电才能进入最优组合。利用陆上风能和太阳能的方案可以获得低成本的氢气，因此可以将这种载体用于工业用途。与农林业部门的甲烷化协同作用不会带来系统成本优势，但会改善该地区的配置。与不受管制的化石天然气相比，陆基风能和太阳能的完全脱碳额外成本较小，而否决这些技术的额外成本较大。

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引用次数: 0

Optimal price signal generation for demand-side energy management 需求侧能源管理的最优价格信号生成

IF 5.4 Q2 ENERGY & FUELS

Smart Energy

Pub Date : 2025-02-01 Epub Date: 2025-01-24 DOI: 10.1016/j.segy.2025.100173

Seyed Shahabaldin Tohidi, Henrik Madsen, Davide Calì, Tobias K.S. Ritschel

Renewable Energy Sources play a key role in smart energy systems. To achieve 100% renewable energy, utilizing the flexibility potential on the demand side becomes the cost-efficient option to balance the grid. However, it is not trivial to exploit these available capacities and flexibility options profitably. The amount of available flexibility is a complex and time-varying function of the price signal and weather forecasts. In this work, we use a Flexibility Function to represent the relationship between the price signal and the demand and investigate optimization problems for the price signal computation. Consequently, this study considers the higher and lower levels in the hierarchy from the markets to appliances, households, and districts. This paper investigates optimal price generation via the Flexibility Function and studies its employment in controller design for demand-side management, its capability to provide ancillary services for balancing throughout the Smart Energy Operating System, and its effect on the physical level performance. Sequential and simultaneous approaches for computing the price signal, along with various cost functions are analyzed and compared. Simulation results demonstrate the generated price/penalty signal and its employment in a model predictive controller.

可再生能源在智能能源系统中发挥着关键作用。为了实现100%的可再生能源，利用需求侧的灵活性潜力成为平衡电网的成本效益选择。然而，利用这些可用的能力和灵活性选项并不是一件容易的事情。可用灵活性的数量是价格信号和天气预报的复杂和时变函数。在这项工作中，我们使用灵活性函数来表示价格信号与需求之间的关系，并研究价格信号计算的优化问题。因此，本研究考虑了从市场到家电、家庭和地区的层次结构中的较高和较低层次。本文通过柔性函数研究了最优电价生成，并研究了其在需求侧管理控制器设计中的应用，其为整个智能能源操作系统提供辅助服务的能力，以及其对物理层性能的影响。顺序和同时计算价格信号的方法，以及各种成本函数进行了分析和比较。仿真结果验证了所生成的价格/惩罚信号及其在模型预测控制器中的应用。

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引用次数: 0