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Abstract

Abstract. This paper describes a decomposition methodology applied to the multi-area optimal power fiow problem in the context of an electric energy system. The proposed procedure is simple and efficient, and presents sorne advantages with respect to other common decomposition techniques such as Lagrangian relaxation and augmented Lagrangian decomposition. The application to the multi-area optimal power fiow problem allows the computation of an optimal coordinated but decentralized solution. The proposed method is appropriate for an Independent System Operator in charge of the electric energy system technical operation. Convergence properties of the proposed decomposition algorithm are described and related to the physical coupling between the areas. Theoretical and numerical results show that the proposed decentralized methodology has a lower computational cost than other decomposition techniques, and in large large-scale cases even lower than a centralized approach.

Distributed Optimal Power Flow in Hybrid AC–DC Grids

“…An early overview on distributed OPF algorithms can be found in [11] and the most recent developments are examined in detail in [12]. The most popular branches to tackle the non-convex AC OPF problem are the Optimality Condition Decomposition (OCD) [13]- [15], Auxiliary Problem Principle (APP) [16], [17] and the Alternating Direction of Multipliers Method (ADMM) [18]- [20]. In OCD technique, primal and dual variables are assigned to a specific sub-problem.…”

“…relatively weakly coupled sub-problems). Those assumptions can not be guaranteed for any problem, however, the method is shown to work for certain networks up to a few hundred buses [15]. In a different way from OCD, in APP and ADMM each sub-problem uses variable duplicates from neighboring sub-problems and is solved to optimality.…”

Methodology for multiarea state estimation solved by a decomposition method

“…It is often desirable to preserve the autonomy of each subsystem. A decentralized operation can be preserved while still attaining overall optimality by applying decomposition techniques [16]. In this paper, a decomposition procedure is described and applied to solve the state estimation problem of a multi-area system.…”

“…These techniques solve many power system problems, and may provide potential advantages in computational efficiency and useful information as part of the decomposition process [16].…”

“…These techniques have been applied in many study cases, among them: multiarea optimal power flow control [16,17,30,31], multiarea decentralized state-estimation [32][33][34][35], decentralized power flow optimization [36], distributed control of energy hubs [37][38][39][40], economic power dispatch [41][42][43], voltage control [44][45][46], and optimal reactive power flow [1]. The OCD exhibits the most efficient computational behavior in many cases [17,47].…”