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As electrical power networks transition towards net-zero emissions, accurate prediction of harmonics is crucial in ensuring the stability and reliability of the system. This paper presents a novel approach for probabilistic harmonic prediction in transmission networks with limited monitoring, utilizing sequential artificial neural networks (ANNs). The approach proposed a predicting process that incorporates both individual-order and total harmonic distortions (THD). The primary stage involves the development of an ANN model that predicts the individual-order harmonic distortions at buses connected with renewable generators and non-linear loads, leveraging their net power injections. In the subsequent stage, a sequential ANN model is constructed to estimate the probabilistic harmonic distortions at unmonitored buses by utilizing past harmonic measurements obtained from installed power quality monitors. To enhance the performance of the model, a sensitivity analysis was conducted to identify the key parameters that significantly affect accuracy, robustness, and reliability. The results affirm the effectiveness of the proposed methodology in accurately predicting harmonic propagations within power systems with limited monitoring. This capability proves valuable in identifying and mitigating potential harmonic issues, thereby aiding the development of future power networks.

The article presents the methodology for dynamic equivalent modelling of hybrid renewable energy source (HRES) plant with the aim of obtaining highly accurate time domain HRES plant power responses at any time during the year. The focus is on equivalent modelling for transient stability studies. Historical HRES plant production dataset and transmission network short-circuit fault statistical data, along with unsupervised data mining and deep learning techniques, represent a basis of the modelling procedure. Dynamic equivalent model (DEM) is developed in the form of deep Long Short Term Memory network. Real and imaginary parts of voltage at the point of common coupling (PCC) are model inputs, while real and reactive power at the PCC are model outputs. The article also proposes a practical approach for selecting the adequate DEM at any time in a year based on the forecasted HRES plant operating scenario only. Model performance is evaluated on a large number of case studies using the HRES plant consisting of three renewable energy sources. The results have shown that only a few DEMs are required for representing the annual HRES plant dynamic performance and obtaining reliable transient system stability results.

Dynamic operating envelopes (DOEs) are promising to cater for the strong uptake of distributed energy resources (DERs) in low-voltage (LV) distribution networks while ensuring secure network operation. Under the current framework, DOEs only specify active-reactive power set-points at households' point of connection (POC). In this regard, DOEs do not provide information on the feasible operating region (FOR) of end-users, which is helpful for an aggregator's market decisions. This article proposes a near real-time approach to determine DOEs that specify the FOR at end-users' POC in an LV distribution network. First, Latin hypercube sampling (LHS)-based load flow studies are performed to identify feasible pairs of P-Q injections at the POC that would not breach voltage limits. Secondly, the convex hull of feasible pairs is constructed to obtain household DOEs. Finally, a feeder-level time-varying envelope that represents the aggregate flexibility of downstream nodes of the network is calculated. A comprehensive analysis on a real Australian LV distribution network using realistic data suggests that the proposed approach is scalable and encourages active power exports beyond current industry practice. Moreover, the framework ensures privacy and separation between the distribution network service provider (DNSP) and the aggregator aligned with the existing policy and regulatory frameworks.

Modern power systems are operating much closer to stability limits due to the integration of uncertain Renewable Energy Sources (RES)-based generations and the decommissioning of traditional synchronous generations. Hence, different aspects of power system stability assessment have come into research focus again. Conventional system stability assessment typically uses dedicated stability indices describing a single aspect of system stability (e.g., voltage, frequency, angularity) or composite indices developed for one aspect of system stability. Such assessments can be ambiguous as the impacts of new devices and technologies on different aspects of system stability can be both, positive and negative to different extents. This paper introduces a probabilistic framework and two composite stability indices for the simultaneous assessment of multiple aspects of power system stability. The application of the indices is demonstrated on a range of case studies with modified IEEE 9-bus and modified IEEE 68-bus test systems without/with RES in a mixed Matlab and DigSilent PowerFactory simulation environment.

Security and transient stability (TS) constrained OPFs do not include network switching and often require excessive computation time due to discretization of the TS model. This paper proposes a non-simulation methodology to optimize active power dispatching and network switching to ensure TS and system security in the preventive control mode. Network switching is introduced in the security constrained OPF and classical TS models, giving a general dynamic security and TS constrained OPF. To ensure TS constraints are manageable in the optimization framework, TS is assessed by using proposed non-simulation based proxy measures. To this end, the key factors impacting TS are investigated and new composite robustness metrics for TS assessment are proposed; they consist of two terms, the nodal and network topology metrics. The former models generator features just before a fault, whilst the second considers impact of a fault on units. The general problem is then decomposed into two stages, the first being economic dispatching and the second optimization of network topology for TS via developed network robustness metrics. The minimum cost topology solutions are ranked by the TS performance. The proposed approach is tested on the IEEE68 Bus test system and compared with time-domain TS results.

Isolated microgrid (MG) proved its potential to electrify the remote community through the cheaper and greener renewable energy alternatives with higher reliability than the weak grid. The goal of universal electricity access and the climate change mitigation paves the way for many public/private owned microgrids in remote areas. Having in mind various uncertainties associated with the design parameters of the MG (e.g., temperature, irradiation, load), this paper presents a probabilistic approach for optimal sizing and techno-economic assessment of the PV-based MG. The potential environmental impact of the isolated MG is taken into account by considering both, the PV/Battery, and more conventional PV/Battery/Diesel Generator configuration. The effectiveness of multi-year data over the single year data in the probabilistic approach is demonstrated. The probabilistic techno-economic analysis of different configurations facilitates informed decision making regarding the configuration and size of MG components while meeting the reliability of supply and environmental constraints. The feasibility and affordability of the configurations are demonstrated through the distribution of net present cost, levelized cost of energy and the unmet load percentage.

Demand Side Management (DSM) has attracted significant attention over the past decade due to its potential contributions to power systems stability and flexibility improvement. The impact of DSM on system stability is traditionally assessed from one or two stability aspects, which may lead to less than comprehensive understanding and ambiguous deployment decisions that subsequently, deteriorate and even endanger system stability. This paper assesses the impact of transmission level advanced DSM on combined system angular and frequency stability using a newly proposed composite stability index. The versatility of the proposed composite stability index and the critical factors (i.e., penetration level of Renewable Energy Source (RES) and modelling of system demand) influencing the impact of advanced DSM on combined system stability are identified using a range of case studies. Such studies were conducted under different operating conditions based on a modified IEEE 68-bus test system and an equivalent network comprising four interconnected real power systems in a mixed environment of Matlab and DigSilent PowerFactory.