The growing use of DGs presents challenges for system planners and operators, demanding strategic adaptations to accommodate diverse energy sources while ensuring grid stability and operational efficiency. HC analysis has recently been proposed as an essential tool capable of guiding investments into the areas of the network, most likely to offer optimal benefits. This paper presents a method for estimation of photovoltaic HC of the distribution network. For this purpose, the OpenDSS program, employing the Monte Carlo-based method, is utilized to quantify the HC of the electrical distribution network. The simulation is conducted using a real electrical MV network and then verified against the IEEE Test System for validation. This research reports higher HC in comparison with similar methods and models, investigates the influence of constant generation in daily simulation and proves that voltage constraint is violated before line loading. A considerable increase of the circuit losses is recorded if the optimal penetration of PV is exceeded. The contribution of this work is development, testing and implementation of HC estimation method in complex power systems using open-source tools and integrating them in innovative fashion. The results of this research contribute to collective endeavours of energy transition and sustainability.

Power system stability plays a significant role in the overall power system analysis. With the high penetration level of distributed generation (DG), especially large-scale wind farms, this problem needs to be addressed. This study investigates the system stability in case of a wind park (WP) integration using doubly fed induction generators (DFIGs) to transmission grid, while focusing on WP fault ride-through ability. The system was modelled for time-domain simulations. The results indicate that WP parallel operation with the high voltage network is possible if specific conditions are met, with fault clearance time being crucial. This is shown through scenarios, in which each of the overhead lines (OHL) was disconnected due to three-phase short circuit symmetrical fault, and the network parameters were observed for each case. The predefined control and protection configurations in the DFIG-based wind farm model simplify the analysis. The introduction of a battery energy storage system (BESS) with P and Q control strategies, improves WP stability during faults. Professional software tools, PSSE, and EMTP-RV, were employed for the analysis. The study showed that simulated WP and BESS connected to a real network, paired with appropriate fault clearance time and protection settings, can operate effectively while maintaining overall system stability. This research is significant for power system planning, especially with the growing integration of large-scale wind generation.

Abstract Islanded microgrids with low-inertia distributed energy resources (DERs) are prone to frequency fluctuations. With the increasing integration of DERs in microgrids, the complexity of control and stability has also increased. Moreover, the integration of DERs into microgrids may result in a power imbalance between energy supply and demand during sudden changes in load or energy generation. This can cause frequency variations in the microgrid, which could have disastrous consequences such as equipment damage or even blackouts. This paper proposes a control strategy to ensure the efficient operation of an islanded hybrid microgrid consisting of a PV generator, battery energy storage system (BESS), and emergency diesel generator. According to Energy Exchange Model proposed in this paper, the hybrid system presented operates independently without being connected to the electrical grid, where the PV system and BESS act as the main energy sources, while the emergency diesel generator provides active power backup with voltage and frequency regulation. The novel in this paper is also that DER aids in frequency regulation during active power transients by delivering and absorbing active power in accordance with the inverter's suggested P droop control strategy. In this way inverter droop control decreases system frequency nadir emulating so called “synthetic inertia”. To design both the islanded hybrid system and the proposed control strategy, the MATLAB/Simulink environment is utilized. Based on the results, it can be concluded that the analyzed microgrid system is capable of maintaining stability and operating efficiently in a range of operating conditions.

Abstract This paper presents a method for distributed generation (DG) allocation in medium voltage (MV) distribution system based on energy loss minimization. The main objective of the research is to design, implement and test a DG allocation (siting and sizing) method and to investigate how optimal DG allocation influence the operational parameters of the system from the Distribution System Operator (DSO) perspective. The problem is formulated as a single objective optimization problem solved by using both genetic algorithm and particle swarm optimization techniques. Model of a realistic Electric Power Distribution System (EPDS) and IEEE 37-bus EPDS are used as test systems. The results confirm that proposed algorithms can be used for practical DG allocation. The research presented contributes to the field as it provides a DG allocation method for energy loss reduction performed on a EPDS which can be applied in realistic planning and regulatory situations using open-source software.

Abstract Environmental issues and the current global energy crisis serve as further motivators for the promotion of renewable energy sources. However, integrating these sources into existing power grids presents numerous challenges. As the connection capacity approaches its limits, it is imperative to employ innovative engineering methods to integrate distributed generation (DG) into resilient, self-healing smart grids of the future. One such tool is Hosting Capacity (HC) analysis, which is an emerging power system-planning tool used to position investments toward parts of the network that can absorb additional generation and promote efficient use of energy sources, avoiding overloading, inefficiencies, DG misallocations, and network failures. In this study, a technique for calculating the ideal HC in a power system is presented. The goal of this research is to develop a replicable optimization methodology for determining HC in smart distribution systems using a single objective constrained optimization problem solved through the use of genetic algorithm (GA). Detailed power system load and generation modeling and the use of advanced open-source research tool for load flow optimization improve the confidence in the proposed model. This research contributes to collective knowledge of the subject matter and establishes a reliable optimization methodology for determining HC in power systems.

With the decreasing reserves of conventional sources and the high emission of harmful gases caused by them, the inclusion of renewable energy sources in power system is increasing. However, to best utilize them, different site location criteria for PV generator installment need to be considered in the decision-making process. This paper presents Fuzzy Analytical Hierarchical Process (AHP) method used in energy planning to find the best Photovoltaic (PV) system site location for the established criteria and factors. Eight criteria were identified and evaluated. These include the solar energy potential, distance to the transmission line, PV surface slope, sunshine duration, the total amount of energy/PV, the temperature ratio, site survey, and performing shading analysis. PVGIS software tool is used to collect necessary data. Evaluation criteria are prioritized by applying fuzzy AHP, fuzzifying the inputs of the decision matrix using triangular fuzzy numbers. The obtained results and the methodology show potential in finding the best location where the PV system can be best utilized.

This paper investigates the allocation model, the flexibility, and the scalability of fully distributed communication architectures for metering systems in smart grids. Smart metering infrastructure aggregates data from Smart Meters (SMs) and sends the collected data to the fog or the cloud data centres to be stored and analysed. The system needs to be scalable and reliable and to respond to increased demand with minimal cost. The problem is to find the optimal distribution of application data among devices, data centres or clouds. The need for support computing at marginal resources, which can be hosted within the building itself or shared within the construction of the complex, has become important over recent years. The resource allocation model is presented to optimize the cost of the resources in the communications and relevance parts of computing (the data processing cost). The fog helps cloud computing connectivity on the edge network. This paper explains how calculation/analysis can be performed closer to the data collection site to complement the analysis that would be undertaken at the data centre. Results for a range of typical scenarios are presented to show the effectiveness of the proposed method.

— This paper presents a study of the effect of microstructure and magnetic texture on the hysteresis loop through quasi-static micromagnetic simulations using the open-source software OOMMF. Results show that microstructure and magnetic texture parameters can be used to control the coercivity. The anisotropy constant is the parameter mainly controlling the coercivity. The increase in the volume fraction of hard inclusions in a soft matrix typically leads to higher coercivity. In the case of randomly oriented inclusions, the calculated coercivity is lower than that for the homogeneous soft case which is explained through the prominent anisotropy energy density compared to the much weaker exchange energy density. The results will be used to correlate simulation parameters with magnetic parameters obtained from major hysteresis loop measurements.