Plug-and-play control and optimization in microgrids

Abstract

Abstract-A hierarchical layering of primary, secondary, and tertiary control is the standard operation paradigm for bulk power systems. Similar hierarchical decision architectures have been proposed for microgrids. However, the control objectives in microgrids must be achieved while allowing for robust plugand-play operation and maximal flexibility, without hierarchical decision making, time-scale separations, and central authorities. Here, we explore control and optimization strategies for the three decision layers and illuminate some possibly-unexpected connections and dependencies among them. Our analysis builds upon first-principle models and decentralized droop control. We investigate distributed architectures for secondary frequency regulation and find that averaging-based distributed controllers using communication among the generation units offer the best combination of flexibility and performance. We further leverage these results to study constrained AC economic dispatch in a tertiary control layer. We show that the minimizers of the economic dispatch problem are in one-to-one correspondence with the set of steady-states reachable by droop control. This equivalence results in simple guidelines to select the droop coefficients, which include the known criteria for load sharing.

Optimal Load-Side Control for Frequency Regulation in Smart Grids

“…We consider the widely used IEEE 39 bus system, shown in Figure 4, to test our scheme. We assume that the system has two independent control areas that are connected through lines (1, 2), (2,3) and (26,27). The network parameters as well as the initial stationary point (pre fault state) were obtained from the Power System Toolbox [43] are corrected so that they initially add up to zero by evenly distributing the mismatch among the load buses.P is obtained from the starting stationary condition.…”

“…This has motivated the recent development of new analytic studies assessing the effect of distributed frequency control in power systems [15]- [22], and microgrids [23]- [27], which can be grouped into three main approaches.…”

“…The first approach builds on consensus algorithms to provide efficiency guarantees to classical PI controllers [15], [16], [24]- [27]. It achieves efficiency but does not manage congestion, i.e., it does not enforce constraints such as thermal limits.…”

Distributed supply–demand balancing and the physics of smart energy systems

“…In addition, studying voltage control via droop control is increasingly popular, e.g. [45], and coupled to the economic dispatch problem [13], though not so explicit as in the two-layered approach from [29]. These methods in general rely on 2nd order swing equation models or on the structure preserving network models introduced by [8], often called the Bergen-Hill models.…”

“…A relation with the above-mentioned optimal control point of view is not so clear yet, even though recent work aims at making a step towards such coupling through the analysis and control of power systems with generators described by 2nd order equations, e.g. [48,13]. However, these 2nd order models for generators are approximations of the original 8 order models that capture the full transient behavior of the system [28].…”