Photovoltaic systems coupled with batteries that are optimally sized for household self-consumption: Assessment of peak shaving potential

Schram, Wouter; Lampropoulos, Ioannis; Sark, W.G.J.H.M. van

doi:10.1016/j.apenergy.2018.04.023

Cited by 108 publications

(60 citation statements)

References 50 publications

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“…Sci. 2019, 9,2030 3 of 13 between actual and planned consumption during a given interval is determined through a budget ratio (R B , unitless) defined as:…”

Section: Simulation Environment Testingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…SEPS are solutions "expected to support the active participation of end users in balancing energy demand and supply in the electricity network" [1] by creating an environment where energy use is flexible [2][3][4], efficient, reliable [5], sustainable and cost-effective [6]. Examples of SEPS include smart meters, smart appliances, electric and fuel cell vehicles [7,8], residential energy storage systems [9,10], and home energy management systems (HEMS) [11] among others.The widespread implementation of SEPS in smart grids could enable greater interaction between end users, home appliances and energy suppliers, facilitating energy efficiency, local production and energy trading with the grid in order to improve the effectiveness of demand response strategies and reduce the required capacity for local energy storage [12,13]. This requires more active end user involvement which is currently limited by user acceptance, with users frequently finding SEPS difficult to understand and interact with [14][15][16].…”

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confidence: 99%

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Simulation-Supported Testing of Smart Energy Product Prototypes

et al. 2019

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Smart energy products and services (SEPS) have a key role in the development of smart grids, and testing methods such as co-simulation and scenario-based simulations can be useful tools for evaluating the potential of new SEPS concepts during their early development stages. Three innovative conceptual designs for home energy management products (HEMPs)—a specific category of SEPS—were successfully tested using a simulation environment, validating their operation using simulated production and load profiles. For comparison with reality, end user tests were carried out on two of the HEMP concepts and showed mixed results for achieving more efficient energy use, with one of the concepts reducing energy consumption by 27% and the other increasing it by 25%. The scenario-based simulations provided additional insights on the performance of these products, matching some of the general trends observed during end user tests but failing to sufficiently approximate the observed results. Overall, the presented testing methods successfully evaluated the performance of HEMPs under various use conditions and identified bottlenecks, which could be improved in future designs. It is recommended that in addition to HEMPs, these tests are repeated with different SEPS and energy systems to enhance the robustness of the methods.

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“…Sci. 2019, 9,2030 3 of 13 between actual and planned consumption during a given interval is determined through a budget ratio (R B , unitless) defined as:…”

Section: Simulation Environment Testingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Simulation-Supported Testing of Smart Energy Product Prototypes

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“…Table 5 gathers operational parameters from different battery technologies affecting their capability of energy storage. According to [58], the most prominent battery technologies for household applications are lead-acid (LA) batteries, high temperature batteries (e.g. NaS or NaNiCl) flow batteries and lithium-ion batteries (LiBs).…”

Section: Environmental and Energy Performance Indicators With An Oriementioning

confidence: 99%

“…If the battery cycles with a high DOD the cells will degrade rapidly but if the DOD is designed not to exceed 0.6, the battery lifetime is considerably high. Hence, high DOD cycling results in a shorter cycle life [61], [58]. In addition, "Battery Cycle Life (BCYL)" reflects the battery life in terms of number of cycles at 80% DoD before a predefined degradation of its performance.…”

Section: Bcl = Year Of Commissioning -Year Of Replacement (19)mentioning

confidence: 99%

A review of key environmental and energy performance indicators for the case of renewable energy systems when integrated with storage solutions

et al. 2018

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During the last years a variety of numerical tools and algorithms have been developed aiming at quantifying and measuring the environmental impact of multiple types of energy systems, as those based on Renewable Energy Sources. Plenty of studies have proposed the use of a Life Cycle Assessment methodology, to determine the environmental impact of renewable installations when coupled with storage solutions, based on a pre-selected repository of Key Performance Indicators. The main scope of this paper is to propose a limited number of best fitting, and at the same time easily adaptable to various configurations, list of KPIs for the case of renewable energy systems. This is done by capitalizing on the environmental and energy performance KPIs tracked in the open literature (e.g. "Global Warming Potential", "Energy Payback Time", "Battery Total Degradation", "Energy Stored on Invested", "Cumulative Energy Demand") and/or other proposing new simple, scalable and adaptable ones, (e.g. "Embodied Energy for Infrastructure of Materials and for the building system", "Life Cycle CO2 Emissions", "Reduction of the Direct CO2 emissions", "Avoided CO2 Emissions", "CO2 equivalent Payback Time"). Moreover, the proposed KPIs are distributed according to the individual phases of the entire life-cycle of a related component of a renewable energy system, each time the environmental impact refers to, i.e. manufacturing, operational and end-of-life. Apart from that, the current paper presents a necessary base grounded approach, which can be followed for a holistic approach in environmental point of view of renewable-based technologies, by addressing the potential competing interests of the relevant stakeholders (e.g. profit for the market operator in contrast to low-cost services for the consumer). All in all, the scalar quantification of the environmental impact of multiple energy systems, through a list of proposed assessment criteria, being evaluated in terms of the selected repository of KPIs, enables the comparison on a fair basis of the available energy systems, irrespective if they are fossil-fuel or RES based ones. As a typical example, a simple standard model of a photovoltaic integrated with an electric battery is selected, for which indicative indicators are provided.

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Stochastic battery energy storage scheduling considering cell degradation and distributed energy resources

Tang

Sun

et al. 2019

Int Trans Electr Energ Syst

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Summary The penetration of distributed energy resources (DERs) greatly raises the risk of distribution network operation such as peak shaving and voltage stability. Battery energy storage (BES) has been widely accepted as the most potential application to cope with the challenge of high penetration of DERs. To cope with the uncertainties and variability of DERs, a stochastic BES scheduling model and its algorithm are proposed. The overall economy is achieved by fully considering the cell degradation, DERs, electricity purchasing, and active power losses. The rainflow algorithm‐based cycle counting method is incorporated in the BES scheduling model to capture the cell degradation, greatly extending the expected BES lifetime and achieving a better economy. DER power scenarios are generated to consider the uncertainties and correlations based on the Copula theory. To solve the BES scheduling model, we propose a Lagrangian relaxation‐based algorithm, which has a significantly reduced complexity with respect to the existing techniques. For this reason, the proposed algorithm enables much more scenarios incorporated in the BES scheduling model and better captures the DER uncertainties and correlations. Finally, numerical studies for the day‐ahead BES scheduling in the IEEE 123‐node test feeder are presented to demonstrate the merits of the proposed method. Results show that the actual BES life expectancy of the proposed model has increased to 4.89 times compared with the traditional ones. The problems caused by DERs are greatly alleviated by fully capturing the uncertainties and correlations with the proposed method.

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Photovoltaic systems coupled with batteries that are optimally sized for household self-consumption: Assessment of peak shaving potential

Cited by 108 publications

References 50 publications

Simulation-Supported Testing of Smart Energy Product Prototypes

Simulation-Supported Testing of Smart Energy Product Prototypes

A review of key environmental and energy performance indicators for the case of renewable energy systems when integrated with storage solutions

Stochastic battery energy storage scheduling considering cell degradation and distributed energy resources

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