Distributed hierarchical control architecture for transient dynamics improvement in power systems

Printed in the United States of America Executive summaryWith large-scale plans to integrate renewable generation driven mainly by state-level renewable portfolio requirements, more resources will be needed to compensate for the uncertainty and variability associated with intermittent generation resources. Distributed assets can be used to mitigate the concerns associated with renewable energy resources and to keep costs down. Under such conditions, performing primary frequency control using only supply-side resources becomes not only prohibitively expensive but also technically difficult. It is therefore important to explore how a sufficient proportion of the loads could assume a routine role in primary frequency control to maintain the stability of the system at an acceptable cost.The main objective of this project is to develop a novel hierarchical distributed framework for frequency based load control. The framework involves two decision layers. The top decision layer determines the optimal gain for aggregated loads for each load bus. The gains are computed using decentralized robust control methods, and will be broadcast to the corresponding participating loads every control period. The second layer consists of a large number of heterogeneous devices, which switch probabilistically during contingencies so that aggregated power change matches the desired amount according to the most recently received gains. The simulation results show great potential to enable systematic design of demand-side primary frequency control with stability guarantees on the overall power system. The proposed design systematically accounts for the interactions between the total load response and bulk power system frequency dynamics. It also guarantees frequency stability under a wide range of time varying operating conditions. The local device-level load response rules fully respect the device constraints (such as temperature setpoint, compressor time delays of HVACs, or arrival and departure of the deferrable loads), which are crucial for implementing real load control programs.

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“…The optimal feedback gains , obtained from the LMI optimization problem, as defined in [10], can be formulated in the following way, …”

Section: Aggregate-level Control Designmentioning

confidence: 99%

Distributed Smart Grid Asset Control Strategies for Providing Ancillary Services

Kalsi

Zhang

Lian

et al. 2013

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“…The proposed hierarchical decentralized control strategy is validated using the IEEE 16-machine, 68-bus, 5-area power system as shown in Fig. 2.4 (adapted from [1]).…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The source code for transient stability studies in PST was modified in order to incorporate load frequency response to local frequency measurement. Figure 2.4: IEEE 68-bus power system (adopted from [1]) .…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Such an approach can achieve robust stability of the system without linearization of the power system model, and can be efficiently solved through Linear Matrix Inequalities (LMI). The robust decentralized control method has been used to design generation-side controllers [1,9]. Its application to the demand-side frequency control is novel.…”

Section: Background and Motivationmentioning

confidence: 99%

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A hierarchical framework for demand-side frequency control

Moya

Zhang

Lian

et al. 2014

2014 American Control Conference

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This thesis develops a hierarchical framework for demand-side frequency control. First, we study the implementation of the hierarchical decentralized controller based on a reduced nonlinear multi-machine power system model in order to stabilize the system. The framework involves two decision layers. The supervisory layer determines a power control command for the aggregated power output response on each load bus using robust decentralized control theory. The device layer involves a large number of controllable loads, which switch probabilistically during contingencies based on a Markov-chain model, local frequency and angle measurements, so that the aggregated power output deviation from the controllable loads matches the desired droop amount according to the power control command determined in the supervisory layer. The proposed framework can deal with time-varying system operating conditions while respecting the physical constraints of individual devices. Realistic simulation results based on a 68-bus system are provided to demonstrate the effectiveness of the proposed strategy. Then, we extend the hierarchical implementation to a structure preserving multi-machine power system model with only frequency measurements. The idea of implementing primary frequency control through end-use devices is investigated. The hierarchical decentralized framework is implemented in order to provide the system with a droop-like response. The proposed framework enables the systematic design of practically implementable demand-side frequency controllers that can

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“…In Short et al (2007) and Fabozzi et al (2013) loads are included in LFC, while Suvire et al (2012) concentrate on effective energy storage, and Chang-Chien et al (2011) suggests how wind generators can participate in LFC. Others concentrate on new control methods for LFC, such as including primary control in local decentralized generators (Marinovici et al, 2013), or improving LFC through fuzzy logic (Yousef et al, 2014), sliding mode control (Vrdoljak et al, 2010), internal model control (Saxena and Hote, 2013), and various PID tuning methods (Tan, 2010). Many have also investigated model predictive control (MPC) as a way of improving LFC, e.g.…”

Section: Introductionmentioning

confidence: 99%

Model predictive load–frequency control taking into account imbalance uncertainty

Ersdal

Imsland

Uhlen

et al. 2016

Control Engineering Practice

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Nonlinear model predictive control (NMPC) is investigated for load frequency control (LFC) of an interconnected power system which is exposed to increasing wind power penetration. The robustified NMPC (RNMPC) proposed here uses knowledge of the estimated worst-case deviation in wind-power production to make the NMPC more robust. The NMPC is based on a simplified system model that is updated using state-and parameter estimation by Kalman filters, and takes into account limitations on among others tie-line power flow. Tests on a proxy of the Nordic power system, shows that the RNMPC is able to fulfill system constraints under worst-case deviations in wind-power production in cases where the nominal NMPC is not. Keywords

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Distributed hierarchical control architecture for transient dynamics improvement in power systems

Cited by 12 publications

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Distributed Smart Grid Asset Control Strategies for Providing Ancillary Services

Distributed Smart Grid Asset Control Strategies for Providing Ancillary Services

A hierarchical framework for demand-side frequency control

Model predictive load–frequency control taking into account imbalance uncertainty

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