Whole-Systems Assessment of the Value of Energy Storage in Low-Carbon Electricity Systems

By D. Pudjianto, Marko Aunedi, P. Djapic, Goran Strbac. IEEE Transactions on Smart Grid, 2014

296 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/bff95802058317ab481e0298929a8e25302cf0b5

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In Control and Systems Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Optimal Bidding, Scheduling, and Deployment of Battery Systems in California Day-Ahead Energy Market (2016, unknown): “As a result, our work is in part comparable with the recent studies in [13]–[15], with at least three key distinctions.”
A review on experience feedback and numerical modeling of packed-bed thermal energy storage systems (2017, background): “With interconnection and demand response, energy storage is one of the most promising ways to enhance the penetration of intermittent energy sources in power grids while ensuring electricity security (Akinyele and Rayudu, 2014; Hohmeyer and Bohm, 2015; Pudjianto et al., 2014).”
Coordinated Price-Maker Operation of Large Energy Storage Units in Nodal Energy Markets (2016, unknown): “First, the prior studies in this third group, including [16], [25]–[28] do not consider large and price-maker battery systems.”
Effect of Battery Degradation on Multi-Service Portfolios of Energy Storage (2016, background): “Recent studies [7], [8] have investigated the potential of energy storage plants to deliver multiple services to various market participants.”
Market design for a high-renewables European electricity system (2018, background): “While superficially attractive, grid-scale battery storage remains too expensive to use beyond those projects where it has very high value-added, such as very fast frequency response and relieving network capacity (Pudjianto et al. 2014; Newbery, 2016c).”
A MILP model for optimising multi-service portfolios of distributed energy storage (2015, background): “Hence in contrast to the whole system cost minimisation modelling used to demonstrate the value of energy storage to the electricity system (like those proposed in [20]), a ‘storage centric’ profit maximisation MILP model is developed in this study.”
The benefits of integrating European electricity markets (2016, result): “The two main methods of computing the potential benefits of market integration are to build a simulation model of the relevant area (ideally, the whole EU, normally some region) and compare the results with and without market coupling, as in some of the studies listed below and one used in this pape”
The value of energy storage in decarbonizing the electricity sector (2016, background): “analyzed in [13] and [20] based on cost minimization, but these studies do not include binding CO2 emissions limits for the electricity sector.”