Distributed Control and Optimization of DC Microgrids: A Port-Hamiltonian Approach

Abstract

This article proposes a distributed secondary control scheme that drives a dc microgrid to an equilibrium point where the generators share optimal currents, and their voltages have a weighted average of nominal value. The scheme does not rely on the electric system topology nor its specifications; it guarantees plug-and-play design and functionality of the generators. First, the incremental model of the microgrid system with constant impedance, current, and power devices is shown to admit a port-Hamiltonian (pH) representation, and its passive output is determined. The economic dispatch problem is then solved by the Lagrange multipliers method; the Karush-Kuhn-Tucker conditions and weighted-average formation of voltages are then formulated as the control objectives. We propose a control scheme that is based on the Control by Interconnection design philosophy, where the consensus-based controller is viewed as a virtual pH system to be interconnected with the physical one. We prove the regional asymptotic stability of the closed-loop system using Lyapunov and LaSalle theorems. Equilibrium analysis is also conducted based on the concepts of graph theory and economic dispatch. Finally, the effectiveness of the presented scheme for different case studies is validated with a test microgrid system, simulated in both MATLAB/Simulink and OPAL-RT environments.INDEX TERMS Control by interconnection, economic dispatch, dc microgrid, distributed control, port-Hamiltonian modeling, secondary control.

Distributed Optimization for Reactive Power Sharing and Stability of Inverter-Based Resources Under Voltage Limits

“…Selecting τ Ω , τ d ∈ [0.1s, 1s] and following the above suggestions, we get τ v ∈ [1s, 10s] which lies in this acceptable range. 3) (k, β): Clearly, β helps solvability of the linear matrix inequality (20a); it increases the eigenvalues of −(Q+Q ⊤ ) and hence the convergence rate α s in (28). But, according to Proposition 1, it degrades the steady-state reactive power sharing.…”

“…It is worth mentioning the similarity of the problem at hand with the problem of voltage regulation and current/power sharing in dc grids, which has been studied in another line of research, see e.g. [28]- [30]. To the best of our knowledge, these distributed dc grid controllers still do not address the research gaps mentioned in the reviewed literature; for ex-ample, the controller in [28] only provides average voltage regulation, the method in [29], similar to the controller in [27], depends on the choice of "leader" converters, and the method in [30] depends on the knowledge of the grid conductance matrix.…”

“…[28]- [30]. To the best of our knowledge, these distributed dc grid controllers still do not address the research gaps mentioned in the reviewed literature; for ex-ample, the controller in [28] only provides average voltage regulation, the method in [29], similar to the controller in [27], depends on the choice of "leader" converters, and the method in [30] depends on the knowledge of the grid conductance matrix. In addition, inverter-based ac systems have different characteristics from dc systems due to the coupling between voltage and frequency-phase angle dynamics, and therefore require their own dedicated control design and system analysis.…”

“…In summary, we have identified the following research gaps. The papers in [6]- [12] have studied either regulation of individual IBR voltages or reactive power sharing, but not both, while none of the papers in [6]- [22], [28] have considered the operational voltage limits. The accuracy of power sharing and voltage regulation/containment under the proposed controllers in [13]- [17], [23], [24], [26], [27], [29], [30], strongly depends on the choice of control parameters or the selection of special converters.…”

Distributed Energy Storage Scheduling Optimization of Micro Grid Based on Particle Swarm Optimization Algorithm

“…For example, some scholars take the micro grid optimal dispatching as the research object, and establish the micro grid optimal dispatching model. The improved particle swarm optimization algorithm is used to solve the model, and a convenient micro network platform is established to design and implement the search results [1][2]. In view of the poor absorption capacity of existing microarrays for photovoltaic and wind energy, other scientists proposed a multi-objective optimization method for microarrays based on improved particle swarm optimization algorithm [3][4].…”