Energy storage for mitigating the variability of renewable electricity sources: An updated review

Beaudin, Marc; Zareipour, Hamidreza; Schellenberglabe, Anthony; Rosehart, William

doi:10.1016/j.esd.2010.09.007

Cited by 860 publications

(473 citation statements)

References 78 publications

(138 reference statements)

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“…heat taken from TES, minus losses due to the discharge efficiency, as shown in Figure 2. The overall heat consumption is calculated according to (5) and (6), (5) (6) where is the heat used to charge the HT/LT section of TES. Similar to the discharge process, there are losses associated with the charge process, as shown in Figure 2.…”

Section: New Thermal Energy Storage Model In Der-cammentioning

confidence: 99%

“…Storage systems, both electric and thermal, can play a key role in DER deployment, not only by creating a buffer to arbitrage market prices, but also by allowing variable small-scale technology integration and promoting more efficient use of resources [5]. In this context, thermal energy storage (TES) is commonly seen as an effective way to reduce operational costs and increase overall efficiency and capacity factors of micro-CHP units, solar thermal units and heat pumps (HPs) [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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Modeling of thermal storage systems in MILP distributed energy resource models

et al. 2015

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-Thermal energy storage (TES) and distributed generation technologies, such as combined heat and power (CHP) or photovoltaics (PV), can be used to reduce energy costs and decrease CO 2 emissions from buildings by shifting energy consumption to times with less emissions and/or lower energy prices. To determine the feasibility of investing in TES in combination with other distributed energy resources (DER), mixed integer linear programming (MILP) can be used. Such a MILP model is the well-established Distributed Energy Resources Customer Adoption Model (DER-CAM); however, it currently uses only a simplified TES model to guarantee linearity and short run-times. Loss calculations are based only on the energy contained in the storage. This paper presents a new DER-CAM TES model that allows improved tracking of losses based on ambient and storage temperatures, and compares results with the previous version. A multi-layer TES model is introduced that retains linearity and avoids creating an endogenous optimization problem. The improved model increases the accuracy of the estimated storage losses and enables use of heat pumps for low temperature storage charging. Results indicate that the previous model overestimates the attractiveness of TES investments for cases without possibility to invest in heat pumps and underestimates it for some locations when heat pumps are allowed. Despite a variation in optimal technology selection between the two models, the objective function value stays quite stable, illustrating the complexity of optimal DER sizing problems in buildings and microgrids.

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Section: New Thermal Energy Storage Model In Der-cammentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling of thermal storage systems in MILP distributed energy resource models

et al. 2015

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“…We do not consider other storage options that transform electric power to other energy carriers, for example power-to-heat or power-to-gas. Beaudin et al (2010) review the status quo, development potentials and challenges of different electricity storage technologies that can be applied for wind and solar power integration. Østergaard (2012) compares different storage options in a 100% renewable energy scenario for a Danish city and shows that power storage can better facilitate wind integration compared to biogas storage or heat storage.…”

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confidence: 99%

Residual load, renewable surplus generation and storage requirements in Germany

Schill

2014

Energy Policy

165

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Abstract:We examine the effects of increasing amounts of fluctuating renewable energy on residual load. We draw on policy-relevant scenarios for Germany and make use of extensive sensitivity analyses. Our simulations show that the expansion of fluctuating renewables shifts the right-hand side of the residual load curve downwards. Whereas yearly renewable surplus energy is low in most scenarios analyzed, peak surplus power can become very high. Decreasing thermal must-run requirements and increasing biomass flexibility substantially reduce surpluses. Using an optimization model, we determine the storage capacities required for taking up renewable surpluses, allowing for varying levels of curtailment. Allowing curtailment of 1% of the yearly feed-in of non-dispatchable renewables would render storage investments largely obsolete until 2032 under the assumption of a flexible power system. Further restrictions of curtailment and lower system flexibility strongly increase storage requirements. Our results suggest that policy makers should not be too concerned about additional storage for taking up renewable surpluses, but should rather focus on measures to avoid surplus generation in the first place, in particular by decreasing the must-run of thermal generators. In a sufficiently flexible power system, minor renewable curtailment does not impede achieving the German government's renewable energy targets.JEL codes: Q42; Q47; Q48

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“…An extensive report by Denholm et al (2010) [2] for the National Renewable Energy Laboratory, USA concludes that high penetrations of variable generation increases the need for all flexibility options, including energy storage. Eyer and Corey (2010) [3] also conclude that renewables integration is one of the major drivers for energy storage while Beaudin et al (2010) [4] concludes that large scale renewables integration will be a more difficult challenge without energy storage. Steinke et al (2013) [5] investigates a 100% renewable Europe and finds that without grid and storage extensions the necessary backup generation amounts to roughly 40% of the demand.…”

Section: Introductionmentioning

confidence: 99%

“…Bulk EES also has many other benefits throughout the electrical supply chain, and several studies have discussed these [2]Ð [4], [12]Ð [15]. They include:…”

Section: Introductionmentioning

confidence: 99%