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

Maryam Bahramipanah, Mostafa Nick, Mario Paolone
IEEE, 2015
Article de conférence

This paper presents a network partitioning strategy for the optimal voltage control of Active Distribution Networks (ADNs) by means of Dispersed Energy Storage Systems (DESSs). The proposed partitioning is based on the concept of voltage sensitivity coefficients and is adopted for a decentralized voltage- control strategy specifically developed for radial ADNs. The aim of the partitioning is to decompose the network into quasi- autonomous areas and to limit the information exchange only at the interfacing nodes between adjacent areas. The information exchange relies on Thévenin equivalents to represent the external grids of each cluster/area. The effectiveness of the proposed decentralized control approach is assessed with respect to an equivalent centralized control approach. Such an assessment is carried out using a numerical example referring to IEEE 123 buses distribution test feeder suitably adapted to include stochastic generation and DESSs.

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Maryam Bahramipanah, Mostafa Nick, Mario Paolone
IEEE, 2015
Article de conférence

Résumé

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https://infoscience.epfl.ch/record/211056?ln=fr

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Concepts associés (15)

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Publications associées (27)

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Stochastic Day-ahead Optimal Scheduling of Active Distribution Networks with Dispersed Energy Storage and Renewable Resources

Mostafa Nick, Mario Paolone

This paper focuses on the problem of the probabilistic optimal day-ahead scheduling of energy resources in Active Distribution Networks (ADNs). These resources include both dispersed energy storage systems (DESSs) and volatile renewable embedded generators. Technical constraints related to both energy resources and electrical network are modeled and taken into account in the proposed optimization problem. The paper first proposes a convex formulation of a specific optimal power flow (OPF) used to compute the resources schedule. Its objective function aims at achieving the minimum of the following quantities: network and DESSs losses, energy cost imported from the external grid, and deviations from the day-ahead scheduled power flow with the same external grid. In addition, the ability of using the substation transformer tap-changer is incorporated into the problem with a suitable cost function. The initial OPF formulation is then enhanced thanks to the use of the Mixed Integer Second Order Cone Programming approach in order to formulate a stochastic AC-OPF. The uncertainties of the problem are due to the forecast errors of the PV generation, load consumption and energy prices. The applicability and the effectiveness of the proposed scheduling approach are tested by using a modified version of the IEEE 34 buses test feeder.

IEEE2014

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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.

Institute of Electrical and Electronics Engineers2014

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Optimal siting and sizing of distributed energy storage systems via alternating direction method of multipliers

Mostafa Nick, Mario Paolone

Energy Storage Systems (ESSs) will have an important role in the optimal operation of Active Distribution Networks (ADNs). Within this context, this paper focuses on the problem of ESSs optimal siting and sizing. Following similar approaches already proposed by the Authors, this paper proposes a multi-objective procedure that accounts for various ancillary services that can be provided by ESSs to ADNs. The proposed procedure takes into account the voltage support and network losses minimization along with minimization of the cost of energy from external grid and congestion management. For the case of large-scale problems, accounting for networks with large number of nodes and scenarios, the selection of the solution methodology is a non-trivial problem. In this respect, the paper proposes and discusses the use of the Alternative Direction Method of Multipliers in order to define an efficient algorithm capable to treat large-scale networks and, also, address the issue of the optimality of the solution. A real large-scale network with real profiles of load and distributed photovoltaic generation is used as the case study to analyze the effectiveness of the proposed methodology.

Elsevier2015

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