Sizing of battery energy storage for end-user applications under time of use pricing

Sizing of battery energy storage for end-user applications under time of use pricing

For access to this article, please select a purchase option:

Buy chapter PDF
(plus tax if applicable)
Buy Knowledge Pack
10 chapters for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Energy Storage at Different Voltage Levels: Technology, integration, and market aspects — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This chapter focuses on the optimal sizing of BESSs in end-user applications in the frame of time-varying energy pricing structures by adopting a probabilistic approach. More in detail, the proposed procedure focuses on one of the most used time-varying tariff structures (i.e. the ToU tariff) but it can be easily extended to other structures. In this chapter, starting from the procedure proposed, the probabilistic optimal sizing is performed applying the point estimate method (PEM), an algorithm that guarantees accuracy of the results with computational effort significantly lower than that implied by the Monte Carlo procedure.

Chapter Contents:

  • 6.1 Introduction
  • 6.2 Energy tariff structures
  • 6.3 The cost of the storage system
  • 6.4 Probabilistic approach for sizing battery systems
  • 6.4.1 Brief background on PEM algorithm
  • 6.4.2 Applications of PEM for the BESS sizing procedure
  • 6.5 Numerical applications
  • 6.5.1 Industrial load
  • 6.5.2 Commercial load
  • 6.5.3 Residential load
  • 6.6 Conclusions
  • References

Inspec keywords: Monte Carlo methods; power generation economics; battery storage plants; pricing; tariffs; probability

Other keywords: probabilistic approach; point estimate method; battery energy storage sizing; end-user applications; time of use pricing; time-varying energy pricing structures; time-varying tariff structures; Monte Carlo procedure; probabilistic optimal sizing; PEM; BESS optimal sizing

Subjects: Monte Carlo methods; Other power stations and plants; Power system management, operation and economics

Preview this chapter:
Zoom in

Sizing of battery energy storage for end-user applications under time of use pricing, Page 1 of 2

| /docserver/preview/fulltext/books/po/pbpo111e/PBPO111E_ch6-1.gif /docserver/preview/fulltext/books/po/pbpo111e/PBPO111E_ch6-2.gif

Related content

This is a required field
Please enter a valid email address