Advanced optimization methods for power systems

Panciatici, Patrick; Campi, Marco C.; Garatti, Simone; Low, Steven H.; Molzahn, Daniel K.; Sun, Andy; Wehenkel, Louis

doi:10.1109/pscc.2014.7038504

Cited by 41 publications

(33 citation statements)

References 72 publications

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“…In this context, maintaining power system reliability in the traditional manner [6] is getting increasingly difficult and costly. Hence the growing interest in post-contingency corrective actions [1]. Monticelli et al [3] are the first to incorporate the possibility of corrective actions in a SCOPF and demonstrate that it reduces the operating cost of the system without compromising its operational reliability.…”

Section: Literature Review and Proposed Methodsmentioning

confidence: 99%

“…The optimization models (23) and (26) are solved only when L > 0, where L defined in Eq. (1). Note that L is greater than 0 if and only if a contingency situation is occurring.…”

Section: Simulation Environmentmentioning

confidence: 99%

“…T RADITIONALLY, power systems have been operated in N-1 preventive security mode, which means that no immediate action is required following a single generation or transmission outage. However, because of the cost of implementing preventive security measures, power systems are increasingly operated in corrective security mode [1]. This means that actions must be taken soon after an outage to prevent line overloads from causing cascading outages or voltage violations from leading to a voltage collapse [2].…”

Section: Introductionmentioning

confidence: 99%

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An Online Optimization Algorithm for Alleviating Contingencies in Transmission Networks

Mazzi

Zhang

Kirschen

2018

IEEE Trans. Power Syst.

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Power systems are increasingly operated in corrective rather than preventive security mode, which means that appropriate control actions must be taken immediately after a contingency has occurred. This paper proposes an online algorithm for automatically alleviating contingencies such as voltage limit violations and line overloads. Unlike previously proposed approaches, the network itself serves as a natural solver of the power flow equations. This makes it possible to start the implementation immediately and avoids problems caused by modeling errors. Every time the controller receives measurements from the grid, it evaluates the presence of contingencies and computes the optimal corrective actions that can be implemented before the next sampling period, subject to ramping constraints of the generators. These corrective actions are implemented through the standard Automatic Generation Control. Finding the optimal incremental corrective actions is fast because this problem is linearized. The effectiveness of this algorithm at correcting both line overloads and voltage violations is demonstrated using the IEEE-118 Bus test system.

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Section: Literature Review and Proposed Methodsmentioning

confidence: 99%

“…The optimization models (23) and (26) are solved only when L > 0, where L defined in Eq. (1). Note that L is greater than 0 if and only if a contingency situation is occurring.…”

Section: Simulation Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Online Optimization Algorithm for Alleviating Contingencies in Transmission Networks

Mazzi

Zhang

Kirschen

2018

IEEE Trans. Power Syst.

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“…Since the problem was first formulated, several specific and dedicated techniques have been used for its solution [4]. Among others, non-linear and quadratic programming techniques, Newton-based methods, and interior point methods in earlier years, as well as heuristic approaches based on genetic algorithms, evolutionary programming, and particle swarm optimization in more recent years.…”

Section: Need For Rigorous Methodsmentioning

confidence: 99%

Editorial

Paolone¹

2015

Sustainable Energy, Grids and Networks

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journal homepage: www.elsevier.com/locate/segan Editorial 1. The evolution of modern power systems as our starting point Fundamental changes are currently taking place in modern energy systems and, particularly, in electrical ones. Infrastructures have to satisfy conflicting requirements: providing reliable and secure services to an increasing number of customers, taking into account a rational use of energy and the protection of the environment. This last requirement drives major changes in electrical and energy systems where increasingly renewable energy sources need to be connected to the grid. It is generally acknowledged that these sources need to be massive and distributed, in order to provide a non-negligible part of the consumed electrical energy [1]. It is also generally agreed that such integration of renewables into existing grids depends on the successful combination of specific processes (e.g. demand side/response management, real-time consumption management, real-time local energy balance, accurate forecasting of renewables at continental, country and regional scales) and new technologies (e.g. smart meters, agent-based distributed controls).Currently, there is a major effort from different research communities, in particular those of applied mathematics, control theory, computer science and, of course, power systems, to propose, discuss and validate new methodologies for the planning, operation and control of future electrical and energy systems. It is within this context that Sustainable Energy, Grids and Networks (SEGAN) has been launched.

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“…The use of corrective security has increased over the past years [1]. On the one hand, the use of corrective actions is driven by increased uncertainty from renewable electricity generation, economic considerations due to market liberalization and operation of the system closer to its limits.…”

Section: Introductionmentioning

confidence: 99%

Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow

Roald

Misra

Krause

et al. 2016

IEEE Trans. Power Syst.

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Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and new technology such as phase shifting transformers (PSTs) and high voltage direct current connections (HVDC). Previous studies have shown that the use of corrective control in response to outages contributes to a reduction in operating cost, while maintaining N-1 security. In this work, we propose a method to extend the use of corrective control of PSTs and HVDCs to react to uncertainty. We characterize the uncertainty as continuous random variables, and define the corrective control actions through affine control policies. This allows us to efficiently model control reactions to a large number of uncertainty sources. The control policies are then included in a chance constrained optimal power flow formulation, which guarantees that the system constraints are enforced with a desired probability. By applying an analytical reformulation of the chance constraints, we obtain a second-order cone problem for which we develop an efficient solution algorithm. In a case study for the IEEE 118 bus system, we show that corrective control for uncertainty leads to a decrease in operational cost, while maintaining system security. Further, we demonstrate the scalability of the method by solving the problem for the IEEE 300 bus and the Polish system test cases.

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Advanced optimization methods for power systems

Cited by 41 publications

References 72 publications

An Online Optimization Algorithm for Alleviating Contingencies in Transmission Networks

An Online Optimization Algorithm for Alleviating Contingencies in Transmission Networks

Editorial

Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow

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