Optimal Allocation of Dispersed Energy Storage Systems in Active Distribution Networks for Energy Balance and Grid Support

Abstract

Abstract-Dispersed storage systems (DSSs) can represent an important near-term solution for supporting the operation and control of active distribution networks (ADNs). Indeed, they have the capability to support ADNs by providing ancillary services in addition to energy balance capabilities. Within this context, this paper focuses on the optimal allocation of DSSs in ADNs by defining a multi-objective optimization problem aiming at finding the optimal trade-off between technical and economical goals. In particular, the proposed procedure accounts for: 1) network voltage deviations; 2) feeders/lines congestions; 3) network losses; 4) cost of supplying loads (from external grid or local producers) together with the cost of DSS investment/maintenance; 5) load curtailment; and 6) stochasticity of loads and renewables productions. The DSSs are suitably modeled to consider their ability to support the network by both active and reactive powers. A convex formulation of ac optimal power flow problem is used to define a mixed integer second-order cone programming problem to optimally site and size the DSSs in the network. A test case referring to IEEE 34 bus distribution test feeder is used to demonstrate and discuss the effectiveness of the proposed methodology.Index Terms-Ancillary services, energy storage, mixed integer second order cone programming, power distribution, power system planning. NOMENCLATURE: DSSDispersed storage system. DG Distributed generation.Variables: 1 Binary variable associated with the presence of energy storage at bus .

Decentralized voltage control of clustered active distribution network by means of energy storage systems

“…Several methods have been proposed in the literature to overcome this issue including centralized and decentralized schemes [5][6][7][8][9][10][11][12][13][14][15][16][17][18].…”

“…In this paper, the locations of DESSs are considered to be given and provided by the process described in [11]. Indeed, the cost of using DESSs for controlling ADNs has been already treated by [11] where the Authors have proposed a solution to the problem of DESSs optimal planning accounting for the investment and operation costs of these systems.…”

“…Indeed, the cost of using DESSs for controlling ADNs has been already treated by [11] where the Authors have proposed a solution to the problem of DESSs optimal planning accounting for the investment and operation costs of these systems. Thus, the paper assumes to regulate each zone by a controller situated inside each DESS.…”

Network clustering for voltage control in active distribution network including energy storage systems

“…In order to decouple the voltage control, given a set B of DESSs optimally located in a balanced and radial ADN (for instance, following the procedure proposed in [5]), the proposed partitioning algorithm decomposes the ADN into several quasiautonomous zones; each under the control of one DESS. Therefore, the boundaries of each area are determined based on the following rule: each DESS within a zone of unknown extension must have significant influence on the co-zonal controlled variables (in our case the node voltages) in comparison with the nodes outside the zone of interest.…”

Congestion management with demand response considering uncertainties of distributed generation outputs and market prices

“…Specific to distribution systems, the integration of distributed energy resources (DERs) such as distributed generations (DGs) [1], energy storage devices [2,3], active loads [4][5][6][7][8][9][10][11] and electric vehicles (EVs) [10][11][12], has greatly changed the operation conditions of the distribution system concerned. DERs are believed to play critical roles in shifting peak loads [7], improving power qualities, enhancing operation efficiency [13] and mitigating possible congestions at distribution system levels [14] in future power systems.…”