Modelling and assessment of the contribution of demand response and electrical energy storage to adequacy of supply

Zhou, Yutian; Mancarella, Pierluigi; Mutale, Joseph

doi:10.1016/j.segan.2015.06.001

Cited by 92 publications

(36 citation statements)

References 19 publications

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“…One of the main reasons why this is happening is the commitment for the low-carbon future that most governments of the Western countries made (Levi and Pollitt, 2015). The future electricity networks will likely to face a number of challenges including the new patterns of consumption, planning under an increasing uncertainty and overall growing complexity due to the large number of small independent devices connected to the network (see Strbac et al, 2014;Nillesen et al, 2014;Zhou et al, 2015).…”

Section: Smart Electricity Gridsmentioning

confidence: 99%

Social and Economic Implications for the Smart Grids of the Future

Strielkowski

2017

Economics &Amp; Sociology

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ABSTRACT. This paper discusses the implications of autonomous self* (self-configuring, self-healing, selfoptimizing and self-protecting) systems for the development of the electrical smart grids of the future. It assesses several scenarios of the future development without prioritizing any of them. The paper employs the data from the Smart Metering Electricity Customer Behaviour Trials conducted by the Commission for Energy Regulation and kindly provided by the Irish Social Science Data Archive (ISSDA) to test the consumers' attitude toward smart meters and adaptive energy tariffs. The findings suggest that when it comes to the implementation of the new approaches to generating, supplying, and monitoring of electrical energy, most of the consumers retain the old-fashioned approach and are driven by the economic incentives. Thence, the developments of the smart grids of the future (or the system will exist beyond these smart grids) is very likely to be shaped by the economic behaviour of the optimizing rational agents on the market.

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Section: Smart Electricity Gridsmentioning

confidence: 99%

Social and Economic Implications for the Smart Grids of the Future

Strielkowski

2017

Economics &Amp; Sociology

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“…Modelling of DES to provide energy arbitrage to support system operation is included here, which is developed based on the storage model in [39] ), charging and discharging efficiency (η DES c , η DES dc ) and the simulation time step length (∆ ts ). Equation (16) determines the energy level of DES (e DES m,t ), which is confined within its energy capacity (E DES Max and E DES Min ).…”

Section: Basic Model Of Desmentioning

confidence: 99%

“…In this light, the following dual-stage optimisation formulation is proposed for utilisation of solar PV to contribute to the system demand at peak times, which is developed based on the relevant optimisation in [39,40]. The first stage in Equations (19) and (20) determines the minimum daily peak demand that can be achieved, while the second stage minimises the energy charged to achieve the minimum daily peak demand.…”

Section: Peak Clipping Operationmentioning

confidence: 99%

System-Level Operational and Adequacy Impact Assessment of Photovoltaic and Distributed Energy Storage, with Consideration of Inertial Constraints, Dynamic Reserve and Interconnection Flexibility

et al. 2017

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Abstract:The growing penetration of solar photovoltaic (PV) systems requires a fundamental understanding of its impact at a system-level. Furthermore, distributed energy storage (DES) technologies, such as batteries, are attracting great interest owing to their ability to provide support to systems with large-scale renewable generation, such as PV. In this light, the system-level impacts of PV and DES are assessed from both operational and adequacy perspectives. Different control strategies for DES are proposed, namely: (1) centralised, to support system operation in the presence of increasing requirements on system ramping and frequency control; and (2) decentralised, to maximise the harnessing of solar energy from individual households while storing electricity generated by PV panels to provide system capacity on request. The operational impacts are assessed by deploying a multi-service unit commitment model with consideration of inertial constraints, dynamic reserve allocation, and interconnection flexibility, while the impacts on adequacy of supply are analysed by assessing the capacity credit of PV and DES through different metrics. The models developed are then applied to different future scenarios for the Great Britain power system, whereby an electricity demand increase due to electrification is also considered. The numerical results highlight the importance of interconnectors to provide flexibility. On the other hand, provision of reserves, as opposed to energy arbitrage, from DES that are integrated into system operation is seen as the most effective contribution to improve system performance, which in turn also decreases the role of interconnectors. DES can also contribute to providing system capacity, but to an extent that is limited by their individual and aggregated energy availability under different control strategies.

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“…The latter also performs an optimisation of standard form with the intention of minimising peak load. In [7], the same authors incorporate into their objective function demand response (DR) of varying payback requirements coupled with storage. [8] assumes that the storage operator aims only to maximise profits, with perfect foresight and no direct consideration of adequacy requirements.…”

Section: Introductionmentioning

confidence: 99%

Minimizing Unserved Energy Using Heterogeneous Storage Units

Evans

Tindemans

Angeli

2019

IEEE Trans. Power Syst.

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This paper considers the optimal dispatch of energyconstrained heterogeneous storage units to maximise security of supply. A policy, requiring no knowledge of the future, is presented and shown to minimise unserved energy during supplyshortfall events, regardless of the supply and demand profiles. It is accompanied by a graphical means to rapidly determine unavoidable energy shortfalls, which can then be used to compare different device fleets. The policy is well-suited for use within the framework of system adequacy assessment; for this purpose, a discrete time optimal policy is conceived, in both analytic and algorithmic forms, such that these results can be applied to discrete time systems and simulation studies. This is exemplified via a generation adequacy study of the British system.

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Modelling and assessment of the contribution of demand response and electrical energy storage to adequacy of supply

Cited by 92 publications

References 19 publications

Social and Economic Implications for the Smart Grids of the Future

Social and Economic Implications for the Smart Grids of the Future

System-Level Operational and Adequacy Impact Assessment of Photovoltaic and Distributed Energy Storage, with Consideration of Inertial Constraints, Dynamic Reserve and Interconnection Flexibility

Minimizing Unserved Energy Using Heterogeneous Storage Units

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