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Flexibility Planning of Distributed Battery Energy Storage Systems in Smart Distribution Networks

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Iranian Journal of Science and Technology, Transactions of Electrical Engineering Aims and scope Submit manuscript

Abstract

The deployment of batteries in the distribution networks can provide an array of flexibility services to integrate renewable energy sources (RES) and improve grid operation in general. Hence, this paper presents the problem of optimal placement and sizing of distributed battery energy storage systems (DBESSs) from the viewpoint of distribution system operator to increase the network flexibility. The problem is formulated as an optimization framework wherein the objective function is to minimize the annualized sum of investment costs and operational costs of DBESSs while it is constrained to power flow, DBESS and RES constraints as well as distribution network operation limits. In addition, while the problem model is as nonlinear programming, this paper suggests an equivalent linear programming model for all constraints and quadratic formulation for the objective function to reach the global optimal solution with low error calculation. In the next step, the Benders decomposition approach is deployed to acquire better calculation speed. Finally, the proposed problem is applied to 19-bus LV CIGRE benchmark grid by GAMS software to investigate the capability of the model.

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Abbreviations

(b,j), t, l, k :

Indices of bus, time, linearization segments of voltage magnitude term and circular constraint, respectively

m, nf :

Index and total number of the iterations of the primal sub-problem to be feasible, respectively

r, ni :

Index and total number of the iterations of the primal sub-problem to be infeasible, respectively

φb, φt, φl, φk :

Sets of bus, time, linearization segments of voltage magnitude term and circular constraint, respectively

A :

Bus incidence matrix (if line existed between buses b and j, Ab,j is equal to 1, and 0 otherwise)

A min :

Minimum boundary rate of the stored energy of battery

c s :

Annual investment cost (in $/MWh/year)

g, b :

Line conductance and susceptance in per unit (pu), respectively

N s :

Total number of storage systems

Pch-max, Pdis-max :

Maximum charging and discharging rate of battery in pu, respectively

PD, QD :

Active and reactive load in pu, respectively

PV:

Output power of photovoltaic in pu

SGmax, SLmax :

Maximum loading of distribution line and station in pu, respectively

T :

Operating horizon, i.e., 6, 12, 24 or 48 h

Vmax, Vmin :

Maximum and minimum voltage magnitude in pu, respectively

V ref :

Voltage of reference (station) bus in pu

ω max :

Maximum capacity of battery in pu

ηch, ηdis :

Efficiency parameter for charging and discharging of the battery, respectively

λch, λdis :

Charging and discharging price of the battery, respectively, in $/MWh

E :

Stored energy of battery

Pch, Pdis :

Amount of electricity charged and discharged from battery

PG, QG :

Active and reactive power of the station, respectively

PL, QL :

Active and reactive power of lines, respectively

V, ΔV, θ :

Magnitude, deviation and angle of voltage (in rad), respectively

ω :

Capacity of battery

λsub, μsub :

Dual variables of equality and inequality constraints in the primal sub-problem

Jp, Jsub :

Master problem and sub-problem objective functions

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Acknowledgements

Parts of the research leading to these results have received funding from the European Union under the Horizon2020 Framework Programme, Grant agreement No. 731148 (INVADE H2020 Project).

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Authors and Affiliations

  1. Department of Electric Power Engineering, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway

    Jamshid Aghaei, Hossein Farahmand & Magnus Korpås

  2. Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran

    Jamshid Aghaei & Seyed Aboozar Bozorgavari

  3. Faculty of Engineering, Semirom Branch, Islamic Azad University, Semirom, Esfahan, Iran

    Sasan Pirouzi

Authors
  1. Jamshid Aghaei
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  2. Seyed Aboozar Bozorgavari
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  3. Sasan Pirouzi
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  4. Hossein Farahmand
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  5. Magnus Korpås
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Correspondence to Jamshid Aghaei.

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Aghaei, J., Bozorgavari, S.A., Pirouzi, S. et al. Flexibility Planning of Distributed Battery Energy Storage Systems in Smart Distribution Networks. Iran J Sci Technol Trans Electr Eng 44, 1105–1121 (2020). https://doi.org/10.1007/s40998-019-00261-z

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  • DOI: https://doi.org/10.1007/s40998-019-00261-z

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