313 research outputs found

    Economic optimization of component sizing for residential battery storage systems

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    Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today's high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.Web of Science107art. no. 83

    Application of a simplified thermal-electric model of a sodium-nickel chloride battery energy storage system to a real case residential prosumer

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    Recently, power system customers have changed the way they interact with public networks, playing a more and more active role. End-users first installed local small-size generating units, and now they are being equipped with storage devices to increase the self-consumption rate. By suitably managing local resources, the provision of ancillary services and aggregations among several end-users are expected evolutions in the near future. In the upcoming market of household-sized storage devices, sodium-nickel chloride technology seems to be an interesting alternative to lead-acid and lithium-ion batteries. To accurately investigate the operation of the NaNiCl2 battery system at the residential level, a suitable thermoelectric model has been developed by the authors, starting from the results of laboratory tests. The behavior of the battery internal temperature has been characterized. Then, the designed model has been used to evaluate the economic profitability in installing a storage system in the case that end-users are already equipped with a photovoltaic unit. To obtain realistic results, real field measurements of customer consumption and solar radiation have been considered. A concrete interest in adopting the sodium-nickel chloride technology at the residential level is confirmed, taking into account the achievable benefits in terms of economic income, back-up supply, and increased indifference to the evolution of the electricity market

    Sizing Battery Energy Storage and PV System in an Extreme Fast Charging Station Considering Uncertainties and Battery Degradation

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    This paper presents mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations

    Recent Developments of Photovoltaics Integrated with Battery Storage Systems and Related Feed-In Tariff Policies: A Review

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    The paper presents a review of the recent developments of photovoltaics integrated with battery storage systems (PV-BESs) and related to feed-in tariff policies. The integrated photovoltaic battery systems are separately discussed in the regulatory context of Germany, Italy, Spain, United Kingdom, Australia, and Greece; the attention of this paper is focused on those integrated systems subject to incentivisation policies such as feed-in tariff. Most of the contributions reported in this paper consider already existing incentive schemes; the remaining part of the contributions proposes interesting and novel feed-in tariff schemes. All the contributions provide an important resource for carrying out further research on a new era of incentive policies in order to promote storage technologies and integrated photovoltaic battery systems in smart grids and smart cities. Recent incentive policies adopted in Germany, Italy, Spain, and Australia are also discussed

    Optimal Management of an Energy Community with PV and Battery-Energy-Storage Systems

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    Most of current prosumer-energy-management approaches are focused on economic optimization by self-consumption maximization. Nevertheless, a lack of energy management strategies (EMS) that tackle different interaction possibilities among community-clustered solar plus battery prosumers has been detected. Furthermore, such active prosumer EMS may include participation in ancillary service markets such as automatic frequency restoration reserves (aFRR) through an optimized battery-energy storage-system (BESS) operation, as well as incorporating community-level energy management. In this study, an optimal EMS that includes aggregated aFRR-market participation of five solar plus battery prosumers participating in an energy community (EC), with the aim of reducing total costs of ownership for each individual prosumer is proposed. For its validation, different scenarios have been analyzed. The results show that the proposed EMS allows a levelized cost of energy (LCOE) reduction for all community members with respect to the base-case scenario. Moreover, the most profitable scenario for all prosumers is still the only PV.This work is financially supported by the Basque Government under the Grant IT1647-22 (ELEKTRIKER research group), and by the Ministerio de Ciencia e Innovación, the Agencia Estatal de Investigación and the European Union under the Grant TED2021-129930A-I00 funded by MCIN/AEI/ 10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR”

    Optimal sizing of grid-connected rooftop photovoltaic and battery energy storage for houses with electric vehicle

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    A practical optimal sizing model is developed for grid-connected rooftop solar photovoltaic (PV) and battery energy storage (BES) of homes with electric vehicle (EV) to minimise the net present cost of electricity. Two system configurations, (1) PV-EV and (2) PV-BES-EV, are investigated for optimal sizing of PV and BES by creating new rule-based home energy management systems. The uncertainties of EV availability (arrival and departure times) and its initial state of charge, when arrives home, are incorporated using stochastic functions. The effect of popular EV models in the market is investigated on the optimal sizing and electricity cost of the customers. Several sensitivity analyses are adopted based on variations in the grid constrains, retail price and feed in tariff. Uncertainty analysis is provided based on the variations of insolation, temperature, and load to approve the optimal results of the developed model. A practical guideline is presented for residential customers in a typical grid-connected household to select the optimal capacity of PV or PV-BES system considering the model of EV. While the proposed optimization model is general and can be used for various case studies, real annual data of solar insolation, temperature, household\u27s load, electricity prices, as well as PV and BES market data are used for an Australian case study. The developed optimal sizing model is also applied to residential households in different Australian States

    Intelligent control of PV co-located storage for feeder capacity optimization

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    Battery energy storage is identified as a strong enabler and a core element of the next generation grid. However, at present the widespread deployment of storage is constrained by the concerns that surround the techno-economic viability. This thesis addresses this issue through optimal integration of storage to improve the efficiency of the electricity grid. A holistic approach to optimal integration includes the development of methodologies for optimal siting, sizing and dispatch coordination of storage

    Pool trading model within a local energy community considering flexible loads, photovoltaic generation and energy storage systems

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    This paper presents a pool trading model within a local energy community considering home energy management systems (HEMSs) and other consumers. A transparent mechanism for market clearing is proposed to incentivise active prosumers to trade their surplus energy within a rule-based pool market in the local energy community. A price-based demand response program (PBDRP) is considered to increase the consumers’ willingness to modify their consumption. The mathematical optimization problem is a standard mixed-integer linear programming (MILP) problem to allow for rapid assessment of the trading market for real energy communities which have a considerable number of consumers. This allows for novel energy trading strategies amongst different clients in the model and for the integration of a pool energy trading model at the level of the local energy community. The objective function of the energy community is to minimize the overall bills of all participants while fulfilling their demands. Two different scenarios have been evaluated, independent and integrated operation modes, to show the impacts of coordination amongst different end-users. Results show that through cooperation, end-users in the local energy community market can reduce the total electricity bill. This is shown in a 16.63% cost reduction in the independent operation and a 21.38% reduction in the integrated case. Revenues for active consumers under coordination increased compared to independent operation of the HEMS.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

    Improving Grid Hosting Capacity and Inertia Response with High Penetration of Renewable Generation

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    To achieve a more sustainable supply of electricity, utilizing renewable energy resources is a promising solution. However, the inclusion of intermittent renewable energy resources in electric power systems, if not appropriately managed and controlled, will raise a new set of technical challenges in both voltage and frequency control and jeopardizes the reliability and stability of the power system, as one of the most critical infrastructures in the today’s world. This dissertation aims to answer how to achieve high penetration of renewable generations in the entire power system without jeopardizing its security and reliability. First, we tackle the data insufficiency in testing new methods and concepts in renewable generation integration and develop a toolkit to generate any number of synthetic power grids feathering the same properties of real power grids. Next, we focus on small-scale PV systems as the most growing renewable generation in distribution networks and develop a detailed impact assessment framework to examine its impacts on the system and provide installation scheme recommendations to improve the hosting capacity of PV systems in the distribution networks. Following, we examine smart homes with rooftop PV systems and propose a new demand side management algorithm to make the best use of distributed renewable energy. Finally, the findings in the aforementioned three parts have been incorporated to solve the challenge of inertia response and hosting capacity of renewables in transmission network
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