A New Hybrid Approach Using the Simultaneous Perturbation Stochastic Approximation Method for the Optimal Allocation of Electrical Energy Storage Systems

Guido Carpinelli, Fabio Mottola, Christian Noce, Angela Russo and Pietro Varilone
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Guido Carpinelli: Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Napoli, Italy
Fabio Mottola: Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Napoli, Italy
Christian Noce: ENEL Global Infrastructure and Networks Srl, Italy
Angela Russo: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, 10129 Torino, Italy
Pietro Varilone: Dipartimento di Ingegneria Elettrica e dell′Informazione “Maurizio Scarano”, Università di Cassino e del Lazio Meriodionale, 03043 Cassino, Italy

Energies, 2018, vol. 11, issue 6, 1-20

Abstract: This paper deals with the optimal allocation (siting and sizing) of distributed electrical energy storage systems in unbalanced electrical distribution systems. This problem is formulated as a mixed, non-linear, constrained minimization problem, in which the objective function involves economic factors and constraints address the technical limitations of both network and distributed resources. The problem is cumbersome from the computational point of view due to the presence of both constraints of an intertemporal nature and a great number of state variables. In order to guarantee reasonable accuracy-although limiting the computational efforts-a new approach is proposed in this paper: it is based on a Simultaneous Perturbation Stochastic Approximation (SPSA) method and on an innovative inner algorithm, which allows it to quickly carry out the daily scheduling (charging/discharging) of the electrical energy storage systems. The proposed method is applied to a medium voltage (Institute of Electrical and Electronics Engineers) IEEE unbalanced test network, to demonstrate the effectiveness of the procedure in terms of computational effort while preserving the accuracy of the solution. The obtained results are also compared with the results of a Genetic Algorithm and of an exhaustive procedure.

Keywords: distributed electrical energy storage systems; optimization method; unbalanced distribution networks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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