Robust N−k Security-constrained Optimal Power Flow Incorporating Preventive and Corrective Generation Dispatch to Improve Power System Reliability

As extreme weather events have become more frequent in recent years,improving the resilience and reliability of power systems has become an important area of concern.In this paper,a robust preventive-corrective security-constrained optimal power flow(RO-PCSCOPF)model is proposed to improve power system reliability under N−k outages.Both the short-term emergency limit(STL)and the long-term operating limit(LTL)of the post-contingency power flow on the branch are considered.Compared with the existing robust corrective SCOPF model that only considers STL or LTL,the proposed ROPCSCOPF model can achieve a more reliable generation dispatch solution.In addition,this paper also summarizes and compares the solution methods for solving the N−k SCOPF problem.The computational efficiency of the classical Benders decomposition(BD)method,robust optimization(RO)method,and line outage distribution factor(LODF)method are investigated on the IEEE 24-bus Reliability Test System and 118-bus system.Simulation results show that the BD method has the worst computation performance.The RO method and the LODF method have comparable performance.However,the LODF method can only be used for the preventive SCOPF and not for the corrective SCOPF.The RO method can be used for both.

Reliability of Power System Integrated with Wind Generation Considering Carbon Tax

This paper proposes a method to evaluate the reliability of power system with different capacities of wind power while considering carbon tax. The proposed method is a hybrid approach which combines Frequency and Duration (F&D) method and Monte Carlo Simulation (MCS) method. MCS method is used to achieve a model to simulate the random status of power system. Also, the proposed method is applied on the IEEE 14-bus test system to investigate the effects of integrating different capacities of wind energy to the reliability of power system with considering carbon tax.

Statistics and Analysis on Reliability of HVDC Transmission Systems of SGCC

Reliability level of HVDC power transmission systems becomes an important factor impacting the entire power grid.The author analyzes the reliability of HVDC power transmission systems owned by SGCC since 2003 in respect of forced outage times,forced energy unavailability,scheduled energy unavailability and energy utilization eff iciency.The results show that the reliability level of HVDC power transmission systems owned by SGCC is improving.By analyzing different reliability indices of HVDC power transmission system,the maximum asset benef its of power grid can be achieved through building a scientif ic and reasonable reliability evaluation system.

Impact of climate simulation resolutions on future energy system reliability assessment:A Texas case study

The reliability of energy systems is strongly influenced by the prevailing climate conditions.With the increasing prevalence of renewable energy sources,the interdependence between energy and climate systems has become even stronger.This study examines the impact of different spatial resolutions in climate modeling on energy grid reliability assessment,with the Texas interconnection between 2033 and 2043 serving as a pilot case study.Our preliminary findings indicate that while low-resolution climate simulations can provide a rough estimate of system reliability,high-resolution simulations can provide more informative assessment of low-adequacy extreme events.Furthermore,both high-and low-resolution assessments suggest the need to prepare for severe blackout events in winter due to extremely low temperatures.

Operation Strategies for Coordinating Battery Energy Storage with Wind Power Generation and Their Effects on System Reliability

The variability of wind power generation requires the allocation of a flexible energy reserve which is capable of compensating for possible imbalances between the load and generation. To reduce the variability of wind power generation and loss of load in generation deficit, we propose operation strategies for coordinating battery energy storage with wind power generation. The effects of the operation strategies on system reliability are evaluated by the developed computation model that represents the main aspects and operation limitations of the batteries. The performance evaluation of the power system is based on the composite reliability indices of loss of load probability(LOLP) and expected energy not supplied(EENS), which is calculated through sequential Monte Carlo simulation. Tests are performed by the developed model with a tutorial system consisting of five busbars and the IEEE RTS system. The results show that the use of large-scale batteries is an alternative to physically guarantee the wind power plants and to act as an operation reserve to reduce the risk of loss of load.

An Optimization Model for Reliability Improvement and Cost Reduction Through EV Smart Charging

There is a general concern that the increasing penetration of electric vehicles(EVs)will result in higher aging failure probability of equipment and reduced network reliability.The electricity costs may also increase,due to the exacerbation of peak load led by uncontrolled EV charging.This paper proposes a linear optimization model for the assessment of the benefits of EV smart charging on both network reliability improvement and electricity cost reduction.The objective of the proposed model is the cost minimization,including the loss of load,repair costs due to aging failures,and EV charging expenses.The proposed model incorporates a piecewise linear model representation for the failure probability distributions and utilizes a machine learning approach to represent the EV charging load.Considering two different test systems(a 5-bus network and the IEEE 33-bus network),this paper compares aging failure probabilities,service unavailability,expected energy not supplied,and total costs in various scenarios with and without the implementation of EV smart charging.

Primary energy congestion of power systems

Primary energy has the potential to bring challenges to the reliability,economic,and eco-friendliness of global electric power systems.The concept of electric power security are proposed,including many factors that are not considered in power system reliability analysis,such as coal supply for power system,fuel price for electricity power market,carbon emissions of power generation,and so on.It is broader than power system reliability and security,which means that providing energy in the form of reliable,economical,and eco-friendly electric power.Following an account of existing blackout defence methods and systems,the processes of transforming various kinds of primary energy into electric power and the interactions between them are described,particularly with regard to flows of energy,capital,and information.Factors that limit the liquidity of these flows are defined as“generalized congestion”,and the challenges presented by primary energy are named“primary energy congestion”.China’s dilemma on coal supply for power generation is presented in some detail as an example of primary energy congestion.To cope with impacts of the primary energy on electric power systems,an idea is introduced to extend the scope of existing coordinated blackout defence systems to account for primary energy,which would lead to an integrated tool to provide decision support to power system operators accounting for primary energy congestion.

Framework of Probabilistic Power System Planning

This paper presents the framework of probabilistic power system planning.The basic concepts,criteria,procedure,analysis techniques and tasks of probabilistic power system planning are discussed.Probabilistic reliability evaluation and probabilistic economic assessment are two key steps.It should also be recognized that probabilistic system planning has a wider coverage than these two aspects.An actual example using a utility system is given to demonstrate an application of probabilistic transmission development planning.

Applications of survival functions to continuous semi-Markov processes for measuring reliability of power transformers

The reliability of power transformers is subject to service age and health condition.This paper proposes a practical model for the evaluation of two reliability indices:survival function(SF)and mean residual life(MRL).In the proposed model,the periodical modeling of power transformers are considered for collecting the information on health conditions.The corresponding health condition is assumed to follow a continuous semi-Markov process for representing a state transition.The proportional hazard model(PHM)is introduced to incorporate service age and health condition into hazard rate.In addition,the proposed model derives the analytical formulas for and offers the analytical evaluation of SF and MRL.SF and MRL are calculated for new components and old components,respectively.In both cases,the proposed model offers rational results which are compared with those obtained from comparative models.The results obtained by the contrast of the proposed analytical method and the Monte Carlo method.The impact of differentmodel parameters and the coefficient of variation(CV)on reliability indices are discussed in the case studies.

A Tabu-search-based Algorithm for Distribution Network Restoration to Improve Reliability and Resiliency

Fault restoration techniques have always been crucial for distribution system operators(DSOs).In the last decade,it started to gain more and more importance due to the introduction of output-based regulations where DSO performances are evaluated according to frequency and duration of energy supply interruptions.The paper presents a tabu-searchbased algorithm able to assist distribution network operational engineers in identifying solutions to restore the energy supply after permanent faults.According to the network property,two objective functions are considered to optimize either reliability or resiliency.The mathematical formulation includes the traditional feeders,number of switching operation limit,and radiality constraints.Thanks to the DSO of Milan,Unareti,the proposed algorithm has been tested on a real distribution network to investigate its effectiveness.

Data-driven Operation Risk Assessment of Wind-integrated Power Systems via Mixture Models and Importance Sampling

The increasing penetration of highly intermittent wind generation could seriously jeopardize the operation reliability of power systems and increase the risk of electricity outages. To this end, this paper proposes a novel data-driven method for operation risk assessment of wind-integrated power systems. Firstly, a new approach is presented to model the uncertainty of wind power in lead time. The proposed approach employs k-means clustering and mixture models(MMs) to construct time-dependent probability distributions of wind power.The proposed approach can also capture the complicated statistical features of wind power such as multimodality. Then, a nonsequential Monte Carlo simulation(NSMCS) technique is adopted to evaluate the operation risk indices. To improve the computation performance of NSMCS, a cross-entropy based importance sampling(CE-IS) technique is applied. The CE-IS technique is modified to include the proposed model of wind power.The method is validated on a modified IEEE 24-bus reliability test system(RTS) and a modified IEEE 3-area RTS while employing the historical data of wind generation. The simulation results verify the importance of accurate modeling of shortterm uncertainty of wind power for operation risk assessment.Further case studies have been performed to analyze the impact of transmission systems on operation risk indices. The computational performance of the framework is also examined.

Smart Grid Functionalities Evaluation

In the last years, with the advent of Smart Grids, many research and demonstration projects have seen the light in order to involve electric system in the implementation of advances in information and communication technologies, in order to improve network efficiency, reliability, security and quality of service. Before new implementations are performed, previous results have to be studied, and taken into account. In this line, this work presents the methodology, results and conclusions of the evaluation of the Smart Grid functionalities developed by 5 different DSOs during DISCERN project in order to select the optimal, cost-effective and most replicable solutions for the strategic development of the intelligence at medium voltage (MV) and low voltage (LV) networks.

Additional Overloading Assessment for Future Low Voltage Networks Based on Smart Metering

The purpose of this article is to present an additional overloading assessment scheme to the current protection scheme, which can be applied in the low voltage distribution network to prevent overloading of network assets. As higher penetration of distributed generators is envisioned among distribution networks, the network operators will have an challenging task in the future to maintain the reliability and quality of supply. The distribution networks are going to be challenged simultaneously by increasing penetration of distributed generators and by increasing loading （inter alia heat pumps, air conditioners or electric vehicles）, which will change the operational perspective of the future distribution networks. Presented simulation results show that the increasing penetration of those appliances can jeopardize the functionality of current protection scheme in distribution networks. Therefore, an additional scheme for assessment of network overloading applicable at low voltage distribution networks is proposed and the application of this scheme, supported by smart metering infrastructure, is demonstrated in a case study. The proposed overloading assessment scheme should help the network operators to increase the flexibility of distribution networks, their hosting capacity, safety and reliability.