4.4 Article

Provision of flexible ramping product by battery energy storage in day-ahead energy and reserve markets

Journal

IET GENERATION TRANSMISSION & DISTRIBUTION
Volume 12, Issue 10, Pages 2256-2264

Publisher

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-gtd.2017.1522

Keywords

energy storage; power markets; power system economics; optimisation; pricing; resource allocation; flexible ramping product; battery energy storage; day-ahead energy; reserve market; renewable energy resource; power system; real-time dispatch; power balance violation; price spike mechanism; independent system operator; USA; FRP; BES; optimisation model; monetary benefit; electricity market; resource allocation; sensitivity analysis

Funding

  1. National Natural Science Foundation of China [51477151]
  2. National Basic Research Program (973 Program) [2013CB228202]
  3. Postdoctoral Innovation Talent Support Program of China [BX201700211]

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The variability and uncertainty of renewable energy resources introduce significant challenges to power system operation. One particular example is the occurrence of ramp capability shortage in real-time dispatch, which can cause power balance violations and price spikes. To meet the increasing need for ramp capability, some independent system operators in the USA have led initiatives to promote the implementation of flexible ramping product (FRP). More potential FRP providers, apart from conventional generators, are being explored, among which battery energy storage (BES) appears to be a feasible option owing to its good controllability and fast responsive characteristics. This study proposes an optimisation model for a BES aggregator to optimally provide FRP in day-ahead energy and reserve markets, aiming to maximise its monetary benefits. The basic concept of FRP is first introduced, including comparisons with traditional ancillary services, pricing mechanisms, and the extensions of market models to integrate FRP. The modes and strategies for BES aggregators to participate in the electricity markets are then addressed. Case studies indicate that an aggregator can gain more profit by optimally allocating its resources among various products than only providing energy and reserves. A sensitivity analysis on several key factors is also conducted.

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