Emergency voltage control using search and predictive control

Larsson, Mats; Hill, David; Olsson, Gustaf

doi:10.1016/s0142-0615(01)00017-5

Cited by 120 publications

(78 citation statements)

References 18 publications

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“…MPC has first been applied to a voltage control problem in [26], in which a coordinated system protection scheme against voltage collapse using search and predictive control is presented. To be tractable, this approach uses a single-step linearized prediction model, that is, a constant control input is assumed over the entire prediction interval.…”

Section: Power Network Modeling and Controlmentioning

confidence: 99%

Prevention of Emergency Voltage Collapses in Electric Power Networks using Hybrid Predictive Control

Leirens

Negenborn

2009

Intelligent Infrastructures

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Section: Power Network Modeling and Controlmentioning

confidence: 99%

Prevention of Emergency Voltage Collapses in Electric Power Networks using Hybrid Predictive Control

Leirens

Negenborn

2009

Intelligent Infrastructures

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“…Due to the stochastic characteristic of renewable energy, the model predictive control (MPC) method [21] is applied for online optimization. MPC was first applied in the power system area for emergency voltage control [22]. Reference [4] presents a linearized MPC-based scheme for voltage regulation.…”

Section: Introductionmentioning

confidence: 99%

Critical Bus Voltage Support in Distribution Systems With Electric Springs and Responsibility Sharing

Zheng

Hill

Meng

et al. 2017

IEEE Trans. Power Syst.

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Abstract-With the development of a new smart load device, the electric spring (ES), the operation of distribution systems with high renewable penetration becomes more flexible. The ESs can be installed at non-critical loads for grid support. This paper proposes a two-level voltage management scheme to optimize the voltage profiles of the network, especially at chosen critical buses. In the upper level, the tap positions of load tap changer and capacitor banks switching are optimized to prevent the voltages along the feeder from being out of limits. The model predictive control technique is applied to handle the uncertainties in renewable energy and demand. In the lower level, the responsibility of maintaining the voltages of the critical buses is shared among the electric springs ( II. INTRODUCTIONN the past, distribution systems have been designed for a one-way flow of energy from substations to customers. However, in recent years, increasing numbers of distributed generators have being connected at the customer side, such as wind or solar, due to environmental and economic concerns [1]. These renewables, besides offering sustainability solutions to energy crisis, can defer network reinforcement, reduce energy transaction, and save power losses. However, due to the high penetration level, energy now can flow in reverse directions during peak generation time, which is not allowed in the traditional systems, causing the voltage rise issue. Additionally, the voltage fluctuation along feeder caused by the intermittent nature of renewable energy is unacceptable for some critical energy consumers, who require more reliable energy supply with higher power quality.In a conventional distribution system without renewable energy penetration, voltage regulation is achieved through compensating voltage drop along feeder by typical means, such as load tap changer (LTC) and capacitor banks (CB). Such voltage regulation devices can respond to the voltage deviations according to different control strategies. Classic control algorithms and device models were proposed to keep the system voltages within constraints in [2]. However, in future distribution systems with the emerging voltage issues, LTC and CB are not flexible enough, especially for the voltage fluctuation mitigation [3]. The high intermittency of renewable energy causes increased number of tap operation actions and capacitor switching, which will decrease the lifetime of such devices [4], [5]. Meanwhile, the most common problem is shifted from voltage drop to voltage rise which cannot be handled by CBs. As a result, developing new control devices and control approaches for voltage regulation in a centralized or a distributed way are needed

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“…In this study, the original predictive control scheme is separated into two sub-problems, namely the static and dynamic sub-problems taking into account the transmission delays and asynchronous measurement. A tree search method has been employed in [8] to co-ordinate the generator voltages, tapchangers and load shedding in the RHC approach and an Euler State predictor (ESP) has been used to predict the output state trajectories. Reference [9] also used ESP based on non-linear system equations and the optimization problem was solved using pseudo-gradient evolutionary programming (PGEP).…”

Section: Introductionmentioning

confidence: 99%

Multi‐agent receding horizon control with neighbour‐to‐neighbour communication for prevention of voltage collapse in a multi‐area power system

Islam

Muttaqi

Sutanto

2014

IET Generation, Transmission & Distribution

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-agent receding horizon control with neighbour-to-neighbour communication for prevention of voltage collapse in a multi-area power system," IET Generation, Transmission and Distribution, vol. 8, (9) pp. 1604-1615, 2014 Multi-agent receding horizon control with neighbour-to-neighbour communication for prevention of voltage collapse in a multi-area power system AbstractIn this study, a multi-agent receding horizon control is proposed for emergency control of long-term voltage instability in a multi-area power system. The proposed approach is based on a distributed control of intelligent agents in a multi-agent environment where each agent preserves its local information and communicates with its neighbours to find an optimal solution. In this study, optimality condition decomposition is used to decompose the overall problem into several subproblems, each to be solved by an individual agent. The main advantage of the proposed approach is that the agents can find an optimal solution without the interaction of any central controller and by communicating with only its immediate neighbours through neighbour-toneighbour communication.The proposed control approach is tested using the Nordic-32 test system and simulation results show its effectiveness, particularly in terms of its ability to provide solution in distributed control environment and reduce the control complexity of the problem that may be experienced in a centralised environment. The proposed approach has been compared with the traditional Lagrangian decomposition method and is found to be better in terms of fast convergence and real-time application. Abstract:In this paper, a multi-agent receding horizon control is proposed for emergency control of long-term voltage instability in a multi-area power system. The proposed approach is based on a distributed control of intelligent agents in a multi-agent environment where each agent preserves its local information and communicates with its neighbours to find an optimal solution. In this paper, optimality condition decomposition (OCD) is used to decompose the overall problem into several sub-problems, each to be solved by an individual agent. The main advantage of the proposed approach is that the agents can find an optimal solution without the interaction of any central controller and by communicating with only its immediate neighbours through neighbour-to-neighbour communication.The proposed control approach is tested using the Nordic-32 test system and simulation results show its effectiveness, particularly in terms of its ability to provide solution in distributed control environment and reduce the control complexity of the problem that may be experienced in a centralized environment. The proposed approach has been compared with the traditional Lagrangian decomposition method and is found to be better in terms of fast convergence and real-time application.

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Emergency voltage control using search and predictive control

Cited by 120 publications

References 18 publications

Prevention of Emergency Voltage Collapses in Electric Power Networks using Hybrid Predictive Control

Prevention of Emergency Voltage Collapses in Electric Power Networks using Hybrid Predictive Control

Critical Bus Voltage Support in Distribution Systems With Electric Springs and Responsibility Sharing

Multi‐agent receding horizon control with neighbour‐to‐neighbour communication for prevention of voltage collapse in a multi‐area power system

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