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The European Union is targeting a 20% share of energy from renewable resources by 2020, and this increase is in turn expected to lead to operational challenges that will require various congestion management actions by system operators. In this paper, we deal with topology control of the transmission network as a congestion management resource and evaluate the impacts of topology control on the European electricity network. To do this, we co-optimize unit commitment and transmission switching over 24 h, and we use a decomposition scheme to tackle the resulting large-scale problem. Our analysis is conducted on different scenarios of load and renewable power generation. We find that topology control results in significant cost savings within Europe which tend to be inversely related to net load. The robustness of our results is supported by an extensive sensitivity analysis. [ABSTRACT FROM AUTHOR]

Optimal transmission switching (OTS) optimizes simultaneously the generation dispatch and the topology of a power system. It has been shown that taking some transmission lines out of service can significantly reduce the operating cost of the system while respecting the traditional deterministic N-1 security criterion of operational reliability. However, topology modifications could adversely affect probabilistic security metrics. The operational reliability of a power system can be translated into a cost by multiplying the expected energy not served by the value of lost load. This paper therefore explores whether it is possible to maintain a positive economic balance with OTS when considering not only the cost of generation but also the expected socio-economic cost of disruptions in the supply. This is done in two steps: the computation of an N-1 secure OTS and then the calculation of a probabilistic estimate of the operational reliability of the OTS solution. Based on the results obtained with two test systems, it is shown that OTS tends to significantly degrade probabilistic measures of security. It is thus not obvious that OTS can lead to a positive economic balance, even when N-1 security is enforced. Consequently, a probabilistic security analysis should be performed before implementing an OTS solution. [ABSTRACT FROM AUTHOR]

This paper proposes a two-level voltage controller for large-scale power systems. The aim of the controller is to maintain a near-optimal voltage profile in the transmission network by coordinating discrete reactive power (var) control devices in the system. The controller is targeted for implementation in electric power transmission utility companies where most of the voltage controls are coordinated by switching of discrete var devices such as shunt capacitor and reactor banks and transformer banks load tap changers (LTCs). By effectively dividing the controller responsibilities between local substation controls and a central coordinator at control center level, the design is aimed at voltage control of large-scale power systems. At local level, the substation controllers maintain their respective substation bus voltages by local power-flow-like computations using mostly local PMU measurements. The central coordinator computes and provides the voltage set-points to the substation controllers and also coordinates by enabling or disabling the local controllers as needed. The controller is being designed towards prototype implementation in Southern California Edison (SCE), starting with local controllers at specific substations in the first stage. It is tested on real-time dynamic models and large-scale power-flow simulations of SCE transmission network. [ABSTRACT FROM AUTHOR]

In power system operation, network topology optimization (NTO) based on bus-branch model and opening/closing transmission lines has been previously proposed and utilized as a congestion mitigating tool to reduce operation cost. The bus-branch model cannot provide a detailed picture of all substation switching actions (e.g., bus splitting) that are well known to operators. In this paper, an NTO model based on substation and node-breaker modeling is presented to relieve congestion and consequently reduce cost. The substation reconfiguration provides a practical and realistic picture of switching actions, while having a higher flexibility in switching actions. However, due to introducing more number of nodes and binary variables associated with breakers, solving an NTO model would be challenging. Therefore, some tightening bounds are presented to maintain the reliability and accelerate the computations. Furthermore, using sensitivity analysis of substations, a method to cluster the network to congestion zones is then employed to determine suitable candidate substations for reconfiguration, thus significantly reducing the number of binary variables associated with breaker switchings. The results of applying the NTO model to the IEEE 118-bus test system demonstrate the effectiveness of the proposed method to remove congestion, while utilizing less number of switching actions compared to bus-branch switching. [ABSTRACT FROM AUTHOR]

This paper proposes a new transmission-constrained unit commitment method that combines the cost-efficient but computationally demanding stochastic optimization and the expensive but tractable interval optimization techniques to manage uncertainty on the expected net load. The proposed hybrid unit commitment approach applies the stochastic formulation to the initial operating hours of the optimization horizon, during which the wind forecasts are more accurate, and then switches to the interval formulation for the remaining hours. The switching time is optimized to balance the cost of unhedged uncertainty from the stochastic unit commitment against the cost of the security premium of the interval unit commitment formulation. These hybrid, stochastic, and interval formulations are compared using Monte Carlo simulations on a modified 24-bus IEEE Reliability Test System. The results demonstrate that the proposed unit commitment formulation results in the least expensive day-ahead schedule among all formulations and can be solved in the same amount of time as a full stochastic unit commitment. However, if the range of the switching time is reduced, the hybrid formulation in the parallel computing implementation outperforms the stochastic formulation in terms of computing time. [ABSTRACT FROM PUBLISHER]