Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. This paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

https://ieeexplore.ieee.org/ielaam/5165411/8075182/7990560-aam.pdf

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

This paper reviews distributed/decentralized algorithms to solve the optimal power flow (OPF) problem in electric power systems. Six decomposition coordination algorithms are studied, including analytical target cascading, optimality condition decomposition, alternating direction method of multipliers, auxiliary problem principle, consensus+innovations, and proximal message passing. The basic concept, the general formulation, the application for dc-OPF, and the solution methodology for each algorithm are presented. We apply these six decomposition coordination algorithms on a test system, and discuss their key features and simulation results.

Toward Distributed/Decentralized DC Optimal Power Flow Implementation in Future Electric Power Systems

This paper reviews signal processing research for applications in the future electric power grid, commonly referred to as smart grid. Generally, it is expected that the grid of the future would differ from the current system by the increased integration of distributed generation, distributed storage, demand response, power electronics, and communications and sensing technologies. The consequence is that the physical structure of the system becomes significantly more distributed. The existing centralized control structure is not suitable any more to operate such a highly distributed system. Hence, in this paper, we overview distributed approaches, all based on consensus ${+}$ innovations, for three common energy management functions: state estimation, economic dispatch, and optimal power flow. We survey the pertinent literature and summarize our work. Simulation results illustrate tradeoffs and the performance of consensus ${+}$ innovations for these three applications.

Distributed State Estimation and Energy Management in Smart Grids: A Consensus ${+}$ Innovations Approach

The current separate transmission and distribution energy management system faces multiple challenges associated with integrating distributed generators (DGs) into future grids. These challenges, such as a voltage rise issue resulting in curtailment of DGs, are difficult to solve via the current separate energy management. Thus, coordination between transmission and distribution is suggested, and a coordinated transmission and distribution AC optimal power flow (TDOPF) is proposed in this paper. A mathematical TDOPF model is established and analyzed in a master-slave structure. A heterogeneous decomposition algorithm (HGD), which is inspired by heterogeneous transmission and distribution characteristics, is proposed to solve the TDOPF in a distributed manner. The HGD is compared to other typical multi-area OPF decomposition algorithms and the differences are discussed. Numerical tests verify the benefit of the TDOPF to both transmission and distribution systems. The TDOPF improves economic operations, mitigates voltage rises, and decreases boundary bus mismatches. Hence, more DGs can be accommodated by the grid. In addition, a series of numerical tests indicate that the HGD competitively solves the TDOPF.

Coordinated Transmission and Distribution AC Optimal Power Flow

This work presents a decentralized implementation of the DC Optimal Power Flow (OPF) problem on a network of workstations. Each workstation is assigned to a regional Transmission System Operator (TSO), who manages the operation of the transmission system of his own region, as well as cross-border exchanges with neighboring regions. The workstations take part in an iterative process, exchanging information with each other and solving regional OPF sub-problems, until the global OPF solution is reached. Tie-line related information is exchanged between workstations assigned to neighboring regions. A master workstation, assigned to a "Super-TSO", checks for the convergence of the algorithm. The parallel processing system is tested on various test systems, including a large real-world system, the Balkan power system.

A decentralized implementation of DC optimal power flow on a network of computers

An approach to paralleling optimal power flow is described that is applicable to very large interconnected power systems and is suitable for distributed implementation. The proposed scheme is based on an augmented Lagrangian approach using the 'auxiliary problem principle'. The objective is to find a set of control parameters with which the auxiliary problem principle can be best implemented in solving distributed optimal power flow problems. The paper is a useful guide to the choice of control parameters that are highly problem dependent and sensitive to problem data. Several IEEE Reliability Test Systems and the Korea Electric Power System demonstrate alternative parameter sets that are the key elements in achieving fast convergence.

Evaluation of convergence rate in the auxiliary problem principle for distributed optimal power flow

Transmission reliability cost allocation method based on market participants' reliability contribution factors

A modified power flow analysis to remove a slack bus with a sense of economic load dispatch

A method of inclusion of security constraints with distributed optimal power flow

This paper presents an algorithm for the parallel solution of the security constrained optimal power flow (SCOPF) problem in a decentralized framework, consisting of regions, using a price-based mechanism that models each region as an economic unit. We first solve the distributed optimal power flow (OPF) problem to determine the maximum secure simultaneous transfer capability of each tie-line between adjacent regions by taking only the security constraints imposed on the tie-lines into account. In this study, the line outage distribution factors (LODF) calculated at the current state are used to formulate the appended constraints. Once the secure transfer capability of each tie-line is determined, the maximum secure transfer capability of tie-lines joining two regions is solved in such a way that the transmission system can also stay within limits in the event of turning generation units off when they are not needed. A description on the inclusion of security constraints with distributed optimal power flow algorithm is given, followed by case studies for Korea power system.

Don Hur

Papers

Evaluation of convergence rate in the auxiliary problem principle for distributed optimal power flow

Transmission reliability cost allocation method based on market participants' reliability contribution factors

A modified power flow analysis to remove a slack bus with a sense of economic load dispatch

A method of inclusion of security constraints with distributed optimal power flow

Security constrained optimal power flow for the evaluation of transmission capability on Korea electric power system