A Microgrid Multilayer Control Concept for Optimal Power Scheduling and Voltage Control

Abstract

In this paper, a novel multilayer control structure for microgrids is proposed. A scheduling layer comprehends the minimization of the microgrid operating costs together with the CO2 emissions produced and provides a sequence of power references for the next 24 hours. Subsequently, within the executive layer, an off line AC power flow calculation will be performed to obtain the initial values of the voltage magnitudes of the different microgrid buses. The adjustment layer, which is the scope of this paper, includes a control strategy to maintain the voltage in the network. The purpose of this third layer is to keep the voltage within a pre-specified tolerance band by adjusting the power provided by the microgrid distributed energy resources (DER). Depending on the voltage deviation, the location of the DER units in the network and their distance from the voltage deviation, an appropriate dynamic gain will be provided to the relevant DER units. The renewed settings are then fed back to the first layer, which performs a new optimization and redistributes the adjusted reference set points among the DER units.

Existing System

Multi-Objective Optimization.

Proposed System

A novel multilayer control structure for microgrids is demonstrated in this paper. The objective of this multilayer control concept is to provide an economically and environmentally viable UC that is physically feasible in terms of voltage violations. In this paper, the future operational states of the controllable units within the microgrid are determined ahead of time. The proposed concept follows the idea of a microgrid day-ahead planning including the unit commitment problem (scheduling layer), an off line power flow calculation (executive layer) and a security check with feedback control (adjustment layer). Since the complete multilayer control concept works on a day-ahead time scale, the multilayer model can be considered as an off line optimization approach. With this approach, the problem is solved on a day-ahead basis, allowing an online implementation to be achieved via real-time system state updates. The scheduling layer finds out the power set points (at quarter-hourly intervals) of the DER units and is based the day-ahead energy market, the demand bids, and the availability of renewable energy sources. The executive layer performs an off line system load flow calculation in order to determine the voltages at the different buses in the network. The adjustment layer provides a dynamic gain to adjust the boundaries of the microgrid generation units according to the data coming from the executive layer. This layer is utilized to maintain the voltage within the acceptable limits. Subsequently, when closing the loop, the scheduling layer recalculates and updates the power settings of the DER units by considering the output from the adjustment layer as a feedback. This iterative process will continue until all voltage violations are eliminated and a converged optimal solution is found.

Architecture

Microgrid multilayer control structure