The increasing interest in integrating intermittent renewable energy sources into microgrids presents major challenges from the viewpoints of reliable operation and control. In this paper, the major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems) is also included. The paper classifies microgrid control strategies into three levels: primary, secondary, and tertiary, where primary and secondary levels are associated with the operation of the microgrid itself, and tertiary level pertains to the coordinated operation of the microgrid and the host grid. Each control level is discussed in detail in view of the relevant existing technical literature.

Trends in Microgrid Control

The placement of a minimal set of phasor measurement units (PMUs) so as to make the system measurement model observable, and thereby linear, is investigated. A PMU placed at a bus measures the voltage as well as all the current phasors at that bus, requiring the extension of the topological observability theory. In particular, the concept of spanning tree is extended to that of spanning measurement subgraph with an actual or a pseudomeasurement assigned to each of its branches. The minimal PMU set is found through a dual search algorithm which uses both a modified bisecting search and a simulated-annealing-based method. The former fixes the number of PMUs while the latter looks for a placement set that leads to an observable network for a fixed number of PMUs. In order to accelerate the procedure, an initial PMU placement is provided by a graph-theoretic procedure which builds a spanning measurement subgraph according to a depth-first search. From computer simulation results for various test systems it appears that only one fourth to one third of the system buses need to be provided with PMUs in order to make the system observable. >

Power system observability with minimal phasor measurement placement

The objective of this paper is to provide a review of distributed control and management strategies for the next generation power system in the context of microgrids. This paper also identifies future research directions. The next generation power system, also referred to as the smart grid, is distinct from the existing power system due to its extensive use of integrated communication, advanced components such as power electronics, sensing, and measurement, and advanced control technologies. At the same time, the need for increased number of small distributed and renewable energy resources can exceed the capabilities of an available computational resource. Therefore, the recent literature has seen a significant research effort on dividing the control task among different units, which gives rise to the development of several distributed techniques. This paper discusses features and characteristics of these techniques, and identifies challenges and opportunities ahead. The paper also discusses the relationship between distributed control and hierarchical control.

Distributed Control Techniques in Microgrids

A general optimization method, known as simulated annealing, is applied to generation unit commitment. By exploiting the resemblance between a minimization process and the cooling of a molten metal, simulated annealing generates feasible solutions randomly and moves among these solutions using a strategy leading to a global minimum with high probabilities. The method assumes no specific problem structures and is highly flexible in handling unit commitment constraints. A concise introduction to the method is given. Numerical results on test systems of up to 100 units are reported. >

Unit commitment by simulated annealing

This paper presents a simulated annealing approach to the long term transmission expansion planning problem which is a hard, large scale combinatorial problem. The proposed approach has been compared with a more conventional optimization technique based on mathematical decomposition with a zero-one implicit enumeration procedure. Tests have been performed on three different systems. Two smaller systems for which optimal solutions are known have been used to tune the main parameters of the simulated annealing process. The simulated annealing method has then been applied to a larger example system for which no optimal solutions are known: as a result an entire family of interesting solutions have been obtained with costs about 7% less than the best solutions known for that particular example system.

Transmission system expansion planning by simulated annealing

The authors study the minimal information structure needed for monitoring and control of the voltage profile and the reactive power flow of a power system. Emphasis is on the minimum amount of information (data) required for reliable decision-making. An effort is made to work with fewer voltage data and therefore make the real-time monitoring and control more manageable. An annealing algorithm for selecting pilot points is presented. These are the load buses at which the voltage is to be measured in real time. Simulation results obtained with the algorithm for the Central Illinois Light Company system are presented. >

J. Christensen

Papers

Secondary voltage control using pilot point information