Stefano Riverso

Stefano Riverso, Fabio Sarzo, Giancarlo Ferrari-Trecate

In this paper we propose a new decentralized control scheme for Islanded microGrids (ImGs) composed by the interconnection of Distributed Generation Units (DGUs). Local controllers regulate voltage and frequency at the Point of Common Coupling (PCC) of each DGU and they are able to guarantee stability of the overall ImG. The control design procedure is decentralized, since, besides two global scalar quantities, the synthesis of a local controller uses only information on the corresponding DGU and lines connected to it. Most important, our design procedure enables Plug-and-Play (PnP) operations: when a DGU is plugged in or out, only DGUs physically connected to it have to retune their local controllers. We study the performance of the proposed controllers simulating different scenarios in MatLab/Simulink and using performance indexes proposed in IEEE standards.

Stefano Riverso, Marcello Farina, Giancarlo Ferrari-Trecate

In this paper we consider a linear system represented by a coupling graph between subsystems and propose a distributed control scheme capable to guarantee asymptotic stability and satisfaction of constraints on system inputs and states. Most importantly, as in Riverso et al., 2012 our design procedure enables plug-and-play (PnP) operations, meaning that (i) the addition or removal of subsystems triggers the design of local controllers associated to successors to the subsystem only and (ii) the synthesis of a local controller for a subsystem requires information only from predecessors of the subsystem and it can be performed using only local computational resources. Our method hinges on local tube MPC controllers based on robust control invariant sets and it advances the PnP design procedure proposed in Riverso et al., 2012 in several directions. Quite notably, using recent results in the computation of robust control invariant sets, we show how critical steps in the design of a local controller can be solved through linear programming. Finally, an application of the proposed control design procedure to frequency control in power networks is presented.

Stefano Riverso, Francesca Boem, Giancarlo Ferrari-Trecate et al.

This paper deals with a novel Plug-and-Play (PnP) architecture for the control and monitoring of Large-Scale Systems (LSSs). The proposed approach integrates a distributed Model Predictive Control (MPC) strategy with a distributed Fault Detection (FD) architecture and methodology in a PnP framework. The basic concept is to use the FD scheme as an autonomous decision support system: once a fault is detected, the faulty subsystem can be unplugged to avoid the propagation of the fault in the interconnected LSS. Analogously, once the issue has been solved, the disconnected subsystem can be re-plugged-in. PnP design of local controllers and detectors allow these operations to be performed safely, i.e. without spoiling stability and constraint satisfaction for the whole LSS. The PnP distributed MPC is derived for a class of nonlinear LSS and an integrated PnP distributed FD architecture is proposed. Simulation results show the effectiveness and the potential of the general methodology.

Stefano Riverso, Michele Tucci, Juan C. Vasquez et al.

This paper presents a distributed control architecture for voltage and frequency stabilization in AC islanded microgrids. In the primary control layer, each generation unit is equipped with a local controller acting on the corresponding voltage-source converter. Following the plug-and-play design approach previously proposed by some of the authors, whenever the addition/removal of a distributed generation unit is required, feasibility of the operation is automatically checked by designing local controllers through convex optimization. The update of the voltage-control layer, when units plug -in/-out, is therefore automatized and stability of the microgrid is always preserved. Moreover, local control design is based only on the knowledge of parameters of power lines and it does not require to store a global microgrid model. In this work, we focus on bus-connected microgrid topologies and enhance the primary plug-and-play layer with local virtual impedance loops and secondary coordinated controllers ensuring bus voltage tracking and reactive power sharing. In particular, the secondary control architecture is distributed, hence mirroring the modularity of the primary control layer. We validate primary and secondary controllers by performing experiments with balanced, unbalanced and nonlinear loads, on a setup composed of three bus-connected distributed generation units. Most importantly, the stability of the microgrid after the addition/removal of distributed generation units is assessed. Overall, the experimental results show the feasibility of the proposed modular control design framework, where generation units can be added/removed on the fly, thus enabling the deployment of virtual power plants that can be resized over time.

Stefano Riverso, Marcello Farina, Giancarlo Ferrari-Trecate

In this paper we consider a linear system structured into physically coupled subsystems and propose a decentralized control scheme capable to guarantee asymptotic stability and satisfaction of constraints on system inputs and states. The design procedure is totally decentralized, since the synthesis of a local controller uses only information on a subsystem and its neighbors, i.e. subsystems coupled to it. We first derive tests for checking if a subsystem can be plugged into (or unplugged from) an existing plant without spoiling overall stability and constraint satisfaction. When this is possible, we show how to automatize the design of local controllers so that it can be carried out in parallel by smart actuators equipped with computational resources and capable to exchange information with neighboring subsystems. In particular, local controllers exploit tube-based Model Predictive Control (MPC) in order to guarantee robustness with respect to physical coupling among subsystems. Finally, an application of the proposed control design procedure to frequency control in power networks is presented.

Daniel O'Keeffe, Stefano Riverso, Laura Albiol-Tendillo et al.

Voltage stability is a critical feature of an efficiently operating power distribution system such as a DC islanded microgrid. Large-scale autonomous power systems can be defined by heterogeneous elements, uncertainty and changing conditions. This paper proposes a novel scalable decentralised control scheme at the primary level of the typical hierarchical control architecture of DC islanded microgrids with arbitrary topology. Local state-feedback $\mathcal{L}_1$ adaptive controllers are retrofitted to existing baseline voltage controllers of DC-DC boost converters, which interface distributed generation units with loads. The use of $\mathcal{L}_1$ adaptive controllers achieves fast and robust microgrid voltage stability in the presence of dynamic uncertainty and plug-and-play operations. Furthermore, local controller synthesis is modular as it only requires approximate information about the line parameters that couple neighbouring units. The performance of the proposed architecture is evaluated using a heterogeneous DC islanded-microgrid that consists of 6 DC-DC boost converters configured in a radial and meshed topology. The use of $\mathcal{L}_1$ adaptive controllers achieves fast and robust microgrid voltage stability in the presence of plug-and-play operations, unknown load and voltage reference changes, and unmodelled dynamics. Finally, sufficient conditions for global stability of the overall system are provided.

Michele Tucci, Alessandro Floriduz, Stefano Riverso et al.

In this paper, we provide an extension of the scalable algorithm proposed in (Riverso et al., 2015) for the design of Plug-and-Play (PnP) controllers for AC Islanded microGrids (ImGs). The method in (Riverso et al., 2015) assumes DGUs are arranged in a load-connected topology, i.e. loads can appear only at the output terminals of inverters. For handling totally general interconnections of DGUs and loads, we describe an approach based on Kron Reduction (KR), a network reduction method giving an equivalent load-connected model of the original ImG. However, existing KR approaches can fail in preserving the structure of transfer functions representing transmission lines. To avoid this drawback, we introduce an approximate KR algorithm, still capable to represent exactly the asymptotic periodic behavior of electric signals even if they are unbalanced. Our results are backed up with simulations illustrating features of the new KR approach as well as its use for designing PnP controllers in a 21-bus ImG derived from an IEEE test feeder.

Michele Tucci, Stefano Riverso, Giancarlo Ferrari-Trecate

We consider the problem of stabilizing voltages in DC microGrids (mGs) given by the interconnection of Distributed Generation Units (DGUs), power lines and loads. We propose a decentralized control architecture where the primary controller of each DGU can be designed in a Plug-and-Play (PnP) fashion, allowing the seamless addition of new DGUs. Differently from several other approaches to primary control, local design is independent of the parameters of power lines. Moreover, differently from the PnP control scheme in [1], the plug-in of a DGU does not require to update controllers of neighboring DGUs. Local control design is cast into a Linear Matrix Inequality (LMI) problem that, if unfeasible, allows one to deny plug-in requests that might be dangerous for mG stability. The proof of closed-loop stability of voltages exploits structured Lyapunov functions, the LaSalle invariance theorem and properties of graph Laplacians. Theoretical results are backed up by simulations in PSCAD.

Daniel O'Keeffe, Stefano Riverso, Laura Albiol-Tendillo et al.

This paper proposes a new distributed control architecture for distributed generation units in heterogeneous DC islanded microgrids. Each unit is equipped with state-feedback baseline and augmenting $\mathcal{L}_1$ adaptive voltage controllers at the primary level of the microgrid control hierarchy. Local controller synthesis is scalable as it only requires information about corresponding units, couplings, and at most, the addition of state-predictor measurements of neighbouring controllers. Global asymptotic stability of the microgrid is guaranteed in a plug-and-play fashion by exploiting Lyapunov functions and algebraic Riccati equations. The performance of the proposed architecture is evaluated using a heterogeneous DC islanded microgrid that consists of 6 DC-DC boost converters configured in a radial and meshed topology. The use of $\mathcal{L}_1$ adaptive controllers achieves fast and robust microgrid voltage stability in the presence of plug-and-play operations, topology changes and unknown load changes. Finally, the distributed architecture is tested on a bus-connected islanded-microgrid consisting of linear resistive load and non-linear DC motor.

Sarah O'Connell, Stefano Riverso

Flexibility is a key enabler for the smart grid, required to facilitate Demand Side Management (DSM) programs, managing electrical consumption to reduce peaks, balance renewable generation and provide ancillary services to the grid. Flexibility analysis is required to identify and quantify the available electrical load of a site or building which can be shed or increased in response to a DSM signal. A methodology for assessing flexibility is developed, based on flexibility formulations and optimization requirements. The methodology characterizes the loads, storage and on-site generation, incorporates site assessment using the ISO 50002:2014 energy audit standard and benchmarks performance against documented studies. An example application of the methodology is detailed using a pilot site demonstrator.

Daniel O'Keeffe, Stefano Riverso, Laura Albiol-Tendillo et al.

Constant-power loads are notoriously known to destabilise power systems, such as DC microgrids, due to their negative incremental impedance. This paper equips distributed generation units with decentralised L1 adaptive controllers at the primary level of the microgrid control hierarchy. Necessary and sufficient conditions are provided to local controllers for overall microgrid stability when constant-power loads are connected. The advantages of the architecture over conventional heuristic approaches are: (i) scalable design, (ii) plug-and-play functionality, (iii) well defined performance and robustness guarantees in a heterogeneous and uncertain system, and (iv) avoids the need for online measurements to obtain non-a priori system impedance information. The proposed primary control architecture is evaluated with distributed consensus-based secondary level controls using a bus-connected DC microgrid, which consists of DC-DC buck and boost converters, linear and non-linear loads. Stability of the overall hierarchical control system is proven using a unit-gain approximation of the primary level.

Michele Tucci, Stefano Riverso, Juan C. Vasquez et al.

We propose a new decentralized control scheme for DC Islanded microGrids (ImGs) composed by several Distributed Generation Units (DGUs) with a general interconnection topology. Each local controller regulates to a reference value the voltage of the Point of Common Coupling (PCC) of the corresponding DGU. Notably, off-line control design is conducted in a Plug-and-Play (PnP) fashion meaning that (i) the possibility of adding/removing a DGU without spoiling stability of the overall ImG is checked through an optimization problem; (ii) when a DGU is plugged in or out at most neighbouring DGUs have to update their controllers and (iii) the synthesis of a local controller uses only information on the corresponding DGU and lines connected to it. This guarantee total scalability of control synthesis as the ImG size grows or DGU gets replaced. Yes, under mild approximations of line dynamics, we formally guarantee stability of the overall closed-loop ImG. The performance of the proposed controllers is analyzed simulating different scenarios in PSCAD.

Stefano Riverso, Simone Mancini, Fabio Sarzo et al.

We consider the problem of dispatching WindFarm (WF) power demand to individual Wind Turbines (WT) with the goal of minimizing mechanical stresses. We assume wind is strong enough to let each WTs to produce the required power and propose different closed-loop Model Predictive Control (MPC) dispatching algorithms. Similarly to existing approaches based on MPC, our methods do not require changes in WT hardware but only software changes in the SCADA system of the WF. However, differently from previous MPC schemes, we augment the model of a WT with an ARMA predictor of the wind turbulence, which reduces uncertainty in wind predictions over the MPC control horizon. This allows us to develop both stochastic and deterministic MPC algorithms. In order to compare different MPC schemes and demonstrate improvements with respect to classic open-loop schedulers, we performed simulations using the SimWindFarm toolbox for MatLab. We demonstrate that MPC controllers allow to achieve reduction of stresses even in the case of large installations such as the 100-WTs Thanet offshore WF.