The electric power system network has become more self-sufficient and less dependent on fossil fuel-based units due to the increasing integration of renewable energy resources. It is crucial to have an efficient method or technology for managing the system’s economics, security, reliability,  environmental damage, and the un- certainties that come with fluctuating loads. In this context, this paper utilizes a framework based on probabi- listic simulation of a demand-side management approach and computational intelligence to calculate the optimal value of saving utility cost (SUC). Unlike traditional methods that dispatch peak-clipped resource blocks sequentially, a modified artificial bee colony (MABC) algorithm is employed. The SUC is then reported through a sequential valley-filling procedure. Consequently, the SUC is derived from the overall profitability of the gen- eration system and includes savings in energy costs, capacity costs, and expected cycle costs. Further investi- gation to obtain the optimal value of SUC was conducted by comparing the SUC determined directly and indirectly, explicitly referring to the peak clipping energy of thermal units (PCETU). The comparisons utilized the MABC algorithm and a standard artificial bee colony, and the results were verified using the modified IEEE RTS- 79 with varying peak load demands. The findings illustrate that the proposed method demonstrated robustness in determining the global optimal values of SUC increments, achieving increases of 7.26 % for 2850 MW and 5 % for 3000 MW, compared to indirect estimation based on PCETU. Moreover, SUC increments of 18.13 % and 25.47 % were also achieved over the conventional method.

Abstract—In the current landscape of power system utilities, ensuring stability and reliability is more crucial than ever, highlighting the  importance of your expertise and contributions. Protecting transmission lines is essential for  maintaining these key attributes in power delivery. This study introduces an innovative approach  using wavelet transform (WT) to an effective wavelet transform (WT) approach. Detect and classify  transmission line faults. The unique capabilities of wavelets make them ideal for addressing  transient disturbances in power systems. Our algorithm utilizes the discrete wavelet transform  (DWT) to extract the three-phase current signal in the case of a single line-to-ground fault.  Carefully selecting the Daubechies4 mother wavelet significantly enhances our ability to gather  helpful information about fault conditions. The classification process is based on careful  calculation. The absolute sum of the signal details at level 2 over a single cycle window provides  precise insights. We employed Power System Computer-Aided Design / Electromagnetic Transients with  DC (PSCAD/EMTDC) to generate the three-phase current signal in a tested 230 kv transmission system.  The simulation results robustly demonstrate that our proposed algorithm excels in detecting and  classifying both faulted and healthy phases, ensuring a future of heightened reliability in power  systems.

The increasing use of inverter-based generation (IBG) in power grids raises concern about system  strength. This is partly due to the inherent interactions among multiple IBGs in close proximity to  one another. This paper proposes an approach to identifying the existential boundary of interaction  in a network using the relative electrical distance (RED) concept. The mathematical formulation of  the RED concept to address the interaction problem among the IBGs involved utilising the power  system network’s admittance matrix to capture its structural characteristics. An interaction matrix  derived from the RED values of all IBG pairs was then developed to identify the interacting IBG  groups. The proposed approach was demonstrated using the IEEE 39-bus system and a practical 72-bus  Nigerian power grid. Results showed that RED values effectively group interacting IBGs, with values  closer to 0 signifying higher interaction levels, values closer to 1 indicating lower interaction,  and a value of 1 denoting no interaction. Time-domain simulations confirmed the accuracy of the  approach, demon- strating that the effect of control interaction propagates proportionally to  neighbouring IBGs based on RED values. However, fault currents can influence the impact of control  interactions. This approach, which requires less computational effort, provides a quick  identification tool for potential areas of concern based on the degree of interaction, enhancing  the reliability of power grids with high IBG penetration.

The classical Model Predictive Control (MPC) is still considered in many industrial applications, although advanced control methods have seen  significant development over the last few years. However, a lot of MPC strategies still suffer from  robustness to cope with a variety of process dynamics. For the MPC controller to work effectively,  it must be properly tuned. However, MPC is challenging and there is no ideal analytic method to  obtain exact solutions that result in the best desired responses. Based on that, this paper  investigate the robustness performance for a MPC tuning strategy. Three formulae were derived  (Proposed , Proposed  and Proposed ). These formulae are used for calculating the suppression coefficient. The three  formulae were derived by fitting the optimal empirical suppression coefficients for varies process  dynamics commonly found in industry. Simulation results show that the use of the proposed strategy results in good performance compared to other strategies previously proposed. The proposed   strategy also demonstrated a robust performance with respect to modelling errors of process  parameters. The results demonstrate the effectiveness and validity of proposed strategy when  compared with conventional strategies.

Available transfer capability is an index to measure the security and economic viability of an interconnected system. However, to accurately determine this index, other associated parameters need to be accurately evaluated. One of these parameters is the capacity benefit margin (CBM). For efficient power generation reliability and sustainability, a certain amount of supply capacity is commonly reserved by utilities, which in most cases remain unused, to reduce the effect of generation outage. To minimize this unused reserve, utilities usually reserve a predetermined amount of tie-line capacity between interconnected areas to have access to external supply. This tie-line reserved for this purpose is termed as capacity benefit margin (CBM). In this paper a technique for computing CBM is used, the sensitivity of CBM support from other areas to the increase in load in one of the areas is investigated, and conclusively, demand side management is proposed to improve the quantification of CBM. The contribution of this work is the assessment of the CBMs support from other areas during a critical condition, using the flexibility of DSM technique. The modified 24-bus IEEE reliability test system is employed for the verification of the approach.

The ceaseless efforts by power system industries to promote sustainable and competitive electric power market structure in the deregulated environment have given rise to enormous research in the area of transfer capability of transmission networks. Due to high demand for electricity, transmission components are stressed to operate close to their operating limits, and this leads to a decrease in transmission efficiency. To address this issue, efficient evaluation of available transfer capability (ATC) is crucial for system planning, operation, and control. Several approaches have been proposed for ATC computation. Surprisingly, a comprehensive literature review on ATC computation is yet to be efficiently presented. Researchers have been able to come up with fast algorithms, but most of these algorithms are not accurate, and the presented accurate techniques are not fast enough for online applications. This paper presents a comprehensive review of the different approaches for ATC determination. It provides the concepts, methods, and the features of the ATC. For each technique, the state of the art of the several contributions made by researchers has been highlighted. This review reveals that there are issues regarding ATC calculation methods that need attention: the development of fast and accurate algorithm incorporating system dynamics and system uncertainties in ATC determination. Additionally, efforts on the incorporation of renewable energy generation in the ATC evaluation need to be intensified. This review will serve as one in all for researchers as well as a guide for the entrants in this field.