Maintain Power System Reliability Research Articles

Novel lossy compression method of noisy time series data with anomalies: Application to partial discharge monitoring in overhead power lines

In overhead power transmission lines, particularly in regions like natural parks where establishing a safe zone is difficult, the adoption of cross-linked polyethylene insulated covered conductors (CCs) helps prevent outages due to vegetation contact. However, these CCs are susceptible to partial discharge (PD) activity, which can degrade insulation and lead to system failures. Detecting and analyzing PD are essential for maintaining power system reliability and safety. A key challenge in PD monitoring is transmitting the large volumes of PD signal data over unreliable 2G networks, as existing compression methods either compromise on data integrity or are ineffective. This paper introduces a novel lossy compression technique utilizing an autoencoder with skip connections and correction data to address this issue. Unlike previous algorithms that struggle with noisy time series data and fail to preserve crucial anomaly information, our method reconstructs the signal without anomalies, which are subsequently restored using correction data. Achieving a compression factor of about 25 (reducing data to 4.1% of its original size), this approach maintains essential PD signal features for analysis. The effectiveness of our method is validated by three classification algorithms, showing promise for future fault detection, diagnosis, and memory space reduction. This innovative compression solution marks a significant advancement in PD data processing, offering a balanced trade-off between compression efficiency and data fidelity, and paving the way for enhanced remote monitoring in power transmission systems.

Selective Auto-Reclosing of Mixed Circuits Based on Multi-Zone Differential Protection Principle and Distributed Sensing

Environmental concerns and economic constraints have led to increasing installations of mixed conductor circuits comprising underground cables (UGCs) and overhead transmission lines (OHLs). Faults on the OHL sections of such circuits are usually temporary, while there is a higher probability that faults on UGC sections are permanent. To maintain power system reliability and security, auto-reclose (AR) schemes are typically implemented to minimize outage duration after temporary OHL faults while blocking AR for UGC faults to prevent equipment damage. AR of a hybrid UCG–OHL transmission line, therefore, requires effective identification of the faulty section. However, the different electrical characteristics of UGC and OHL sections present significant challenges to existing protection and fault location methods. This paper presents a selective AR scheme for mixed conductor circuits based on the evaluation of differential currents in multiple defined protection zones, using distributed current transformer (CT) measurements provided by passive optical sensing. Case studies are conducted with a number of different UGC–OHL configurations, and the results demonstrate that the proposed scheme can accurately identify the faulty section, enabling effective selective AR of a comprehensive range of mixed conductor circuit topologies. The proposed scheme is also more cost effective, with reduced hardware requirements compared to conventional solutions. This paper thereby validates the optimal solution for mixed circuit protection as described in CIGRE Working Group B5.23 report 587.

A Novel Online Monitoring Scheme for Underground Power Cable Insulation Based on Common-Mode Leakage Current Measurement

Insulation aging of underground power cables may lead to severe fault and system outages. Condition monitoring of cable insulation is essential to maintain power system reliability. However, most existing insulation monitoring methods can only work in offline mode and cannot describe cable aging severity quantitatively. In this article, a novel online monitoring scheme for underground power cable insulation based on common-mode (CM) leakage current measurement is proposed. An online neutral-point voltage injection approach is proposed, and CM leakage current distribution model for both the cables with and without metal sheath under the injected voltage is derived. The insulation capacitance can therefore be monitored online without disturbance to the system operation. Simulations and experiments are conducted to prove the effectiveness of the proposed method. With the aid of a designed CM leakage current sensor, CM leakage current smaller than 5 mA can be detected and the accurate evaluation of aging severity is achieved. The key feature of the proposed method lies in its nonintrusiveness and online fashion: the normal operation of the system will not be interrupted, and accurate quantitative monitoring of cable insulation can be achieved online.

Detection of Electricity Theft Behavior Based on Improved Synthetic Minority Oversampling Technique and Random Forest Classifier

Effective detection of electricity theft is essential to maintain power system reliability. With the development of smart grids, traditional electricity theft detection technologies have become ineffective to deal with the increasingly complex data on the users’ side. To improve the auditing efficiency of grid enterprises, a new electricity theft detection method based on improved synthetic minority oversampling technique (SMOTE) and improve random forest (RF) method is proposed in this paper. The data of normal and electricity theft users were classified as positive data (PD) and negative data (ND), respectively. In practice, the number of ND was far less than PD, which made the dataset composed of these two types of data become unbalanced. An improved SOMTE based on K-means clustering algorithm (K-SMOTE) was firstly presented to balance the dataset. The cluster center of ND was determined by K-means method. Then, the ND were interpolated by SMOTE on the basis of the cluster center to balance the entire data. Finally, the RF classifier was trained with the balanced dataset, and the optimal number of decision trees in RF was decided according to the convergence of out-of-bag data error (OOB error). Electricity theft behaviors on the user side were detected by the trained RF classifier.

Synthesis and Application of Ceo2 and Zro2 Nanoparticles for Enhancement of Dielectric Strength of Transformer Oil

Power and Distribution transformers are the key devices to maintain power system reliability. Thus in-order to have continuous power supply ,a fault tolerant system is to be developed by avoiding the failures on major devices like transformers. As insulation failure is accounted as 13.0% occurrence of all the faults on transformer, there is always a point of interest to enhance the breakdown strength of the transformer oil. Also to cater to the demand , an increase in the number and unit capacity of high voltage transformers require transformer oil with high oxidation stability and good electric properties. In this work , ceramic nanomaterials zirconia(ZrO2) and Ceria ( CeO2) are preferred due to their strong insulating property and high relative permittivity. The synthesized nanomaterials of concentration (0.5%wt) are dispersed into the transformer oil by sonication and AC breakdown measurements have been performed on the prepared nano transformer oil. The obtained results clearly indicates a remarkable increase in the dielectric strength of transformer oil filled with ZrO2 and CeO2nanoparticle.

Stochastic multi‐stage model for co‐planning of transmission system and merchant distributed energy resources

In recent years, while energy consumption is still increasing, system peak load is decreasing due to deregulation in power systems, application of demand response programmes, microgrids and smart grids implementation, and so on. Thus, transmission system operators (TSOs), which are usually a public entity, must reinforce the transmission systems to maintain power system reliability. They are not interested in investing transmission network because of high investment costs. In this regard, this study presents a new bi-level model for co-planning of transmission system and merchant distributed energy resources (DERs). The upper level takes the TSOs perspective and aims to minimise the line investment cost and cost of buying energy from conventional generators and DERs, while ensuring a given rate of return on DERs investments. The lower level simulates market clearing to find nodal prices for calculating DERs' profit and cost of buying energy. The proposed model is reformulated as a single-level mixed integer linear programming problem by strong duality technique, bigM method, and the complementary slackness conditions. The IEEE RTS 24 bus test system has been used to show the usefulness of the proposed model.

A New Approach for Contingency Analysis Based on Centrality Measures

The contingency analysis of power systems represents a critical part of security monitoring, required to maintain power system reliability. In general, traditional $N-1$ contingency analysis methods simulate a few outages, due to the high computational costs involved. Thus, they may fail to identify some critical contingencies that can lead to cascading failures. This paper proposes a new approach to $N-1$ contingency analysis of electric transmission systems, based on network centrality measures. The proposed method evaluates all possible transmission line outages in a very short computational time, and it requires only topological information. Results are shown for two electric power systems: ITAIPU 11 bus and IEEE 39 bus. Comparisons between the results obtained by the proposed method and traditional ones show the accuracy of the proposed method to identify critical buses and transmission lines, in local and global context, even in absence of electrical information. The proposed method is interesting as a direct and fast tool applied to the pre-analysis process, since topological network behavior is verified. Thus, pre-analysis provides a prior response to the system operator of the points by which the electrical power system analysis should begin, in order to ensure safe operational state of the system.

Keeping It Together: Transient Stability in a World of Wind and Solar Generation

While there are myriad economic, societal, and operational debates associated with the continued growth of wind and solar generation, on one aspect there is uniform consensus: maintaining power system reliability is essential. There are many facets to system reliability, and one is transient stability. This arcane branch of power system engineering is opaque to the casual participant, yet successful system operation demands that we get it right. In greatly simplified shorthand, maintaining transient stability means keeping enough of the bits of the power system, i.e., generation, transmission, and distribution, connected to avoid interrupting customers after the grid is whacked by Mother Nature or more nefarious forces. (See ?Transient Stability in a Nutshell.?)

Load-shedding Strategies for Preventing Cascading Failures in Power Grid

Load shedding has always been a commonly adopted method in emergency situations to maintain power system reliability. Several load-reduction strategies have been suggested in the past, but most are complex and not scalable. This article proposes and thoroughly investigates three load-shedding strategies to prevent cascading failures in the power grid. The first strategy is a baseline case called the homogeneous load-shedding strategy. It homogeneously reduces load in all of the buses of the system. This strategy is extremely simple and fast, and these properties motivate its use in some specific scenarios in spite of its inefficiencies. Next, to accurately find the location and amount of load shedding, a polynomial complexity optimization formulation is proposed, which is much more efficient in overall load shedding in the system. A novel tree heuristic is proposed to overcome the drawbacks of the optimization, namely fairness and scalability. The tree heuristic is linear and very simple to implement. In general, it gives close to optimal results. The results of the tree strategy are compared with that of another existing heuristic, and it is found that the tree performs equal to or better than the existing heuristic for all cases.

Compensating Electrical Storage Resources

The growth of intermittent renewable resources has sparked interest in the use of electrical storage facilities as tools for enhancing the value of renewables and maintaining power system reliability. This raises questions about how storage facilities should be compensated for their services. A main point of controversy is whether storage facilities provide transmission services, as the resolution of this point determines whether storage should receive the sort of “guaranteed” compensation that is available to transmission providers.

Intermittent renewable generation and the cost of maintaining power system reliability

There have been attempts, using various approaches, to assess the additional cost of running an electricity system when intermittent renewable generation is used to provide a significant proportion of the energy. The key issues are the difference, in statistical terms, between the resource availability of the intermittent source and conventional generation and the contribution the intermittent source can make to meet the system peak demand while maintaining system reliability. There is considerable agreement over the capacity credits that can be attributed to renewable energy sources, that is the amount of conventional capacity that renewables can reliably displace, yet the implications for costs have proved more controversial. Approaches to calculate changes in overall system cost are examined and an expression for the additional cost that intermittent generation imposes on a system that is attributable to its intermittent nature is identified. Further, it is shown that this expression can be reconciled with approaches that look at intermittent renewables on a stand-alone basis and factor in the additional costs of ‘standby’ capacity. It is shown that the main source of divergence between estimates of the cost of intermittency is the load factor implicitly assumed for the conventional plant used as a reference. There is only one consistent way to impute the costs of intermittency when the unit cost of intermittent plant is being compared with that of baseload generation plant.

Calling for backup

In this paper, the importance of, and key design issues for, backup control centers (BCC) in maintaining power system reliability are discussed. It also highlights the importance of the key factors incorporated into the initial design studies of the BCC of the Alberta Electric System Operator (AESO) and may help other utilities that might want to implement a similar backup facility at their premises.

Tighter controls for busier systems [power systems

A variety of new technologies are becoming available that will help utilities maintain power system reliability while handling the larger volume of transactions. For example, power electronic systems can provide unprecedented control over electricity flow on transmission networks, preventing or containing cascading disturbances. In addition, new sensor technology, faster communications between control centers, and advanced software tools can enable utilities to monitor system conditions in real time, letting them respond more quickly to disturbances and minimize their impact. Over the next decade, these technologies will facilitate increased power transfers through power delivery systems that are presently constrained, providing power at lower cost to a greater number of customers. It is a question of how to optimize power flow through an entire network by integrating multiple technologies and coordinating control over wide areas. Such integration and coordination will be necessary for deregulation to proceed smoothly toward its twin goals: reducing electricity costs to US consumers, while maintaining the high levels of reliability they have come to expect. The authors discuss the following technologies to help achieve these goals including: flexible AC transmission systems (FACTS), the next generation of FACTS controllers, hierarchical control of FACTS, on-line power systems analysis, control centre communications, and wide area measurement system.