Decentralised Optimisation and Control in Electrical Power Systems

Emerging smart-grid-enabling technologies will allow an unprecedented degree of observability and control at all levels in a power system. Combined with flexible demand devices (e.g. electric vehicles or various household appliances), increased distributed generation, and the potential development of small scale distributed storage, they could allow procuring energy at minimum cost and environmental impact. That however presupposes real-time coordination of demand of individual households and industries down at the distribution level, with generation and renewables at the transmission level. In turn this implies the need to solve energy management problems of a much larger scale compared to the one we currently solve today. This of course raises significant computational and communications challenges. The need for an answer to these problems is reflected in today’s power systems literature where a significant number of papers cover subjects such as generation and/or demand management at both transmission and/or distribution, electric vehicle charging, voltage control devices setting, etc. The methods used are centralized or decentralized, handling continuous and/or discrete controls, approximate or exact, and incorporate a wide range of problem formulations. All these papers tackle aspects of the same problem, i.e. the close to real-time determination of operating set-points for all controllable devices available in a power system. Yet, a consensus regarding the associated formulation and time-scale of application has not been reached. Of course, given the large scale of the problem, decentralization is unavoidably part of the solution. In this work we explore the existing and developing trends in energy management and place them into perspective through a complete framework that allows optimizing energy usage at all levels in a power system

Investigation of Maximum Possible OPF Problem Decomposition Degree for Decentralized Energy Markets

The need for improved utilization of existing system assets and energy sources, as well as the smooth incorporation of new technologies (such as electric vehicles) into the grid, has prompted the participation of small power consumers and generators in the energy markets. A problem of such scale however cannot be managed in a centralized manner in its full detail. This paper examines the idea of a decentralized approach in clearing the energy market. A general framework for the problem decomposition and its distributed solution is presented and analyzed. A key point of interest in this work is the fundamental question of how far decomposition may be pursued for a given system, while still achieving reasonable convergence properties. The corresponding optimization problem is formulated and solved through a parallel implementation of the Alternating Direction Method of Multipliers (ADMM). A thorough investigation of its convergence properties is conducted, and through its coordination with an additional proximal based decomposition method we improve its scalability characteristics