Advanced Forecasting Techniques and Grid Management Strategies (Published)
Energy forecasting is crucial for addressing challenges in data-rich smart grid (SG) systems, encompassing applications such as demand-side management, load shedding, and optimal dispatch. Achieving efficient forecasting with minimal prediction error remains a significant challenge due to the inherent uncertainty in SG data. This paper provides a comprehensive, application-focused review of advanced forecasting methods for SG systems, highlighting recent advancements in probabilistic deep learning (PDL).The review extensively examines traditional point forecasting methods, including statistical, machine learning (ML), and deep learning (DL) techniques, evaluating their suitability for energy forecasting. Additionally, the importance of hybrid approaches and data preprocessing techniques in enhancing forecasting performance is discussed.A comparative case study utilizing the Victorian electricity consumption in Australia and American Electric Power (AEP) datasets is conducted to assess the performance of deterministic and probabilistic forecasting methods. The analysis reveals that DL methods, with appropriate hyper-parameter tuning, exhibit superior efficacy when dealing with larger sample sizes and nonlinear patterns. Moreover, PDL methods demonstrate at least a 60% reduction in prediction errors compared to other benchmark DL methods. However, the increased execution time for PDL methods, due to the large sample space, necessitates a balance between computational performance and forecasting accuracy.
Keywords: Grid, Management, Strategies., advanced forecasting techniques
INVESTIGATING THE SELECTION OF A SUITABLE SLACK BUS: A CASE STUDY OF THE MULTI-GENERATING STATIONS OF THE NIGERIAN 330-KV POWER SYSTEM NETWORK. (Published)
Slack bus is a bus with generating unit and used to balance the real power (P) and reactive power (Q) in the power system while performing load flow studies. This study therefore, investigated the best slack bus suitable to be used in the load flow study of the Nigerian 330-kVtransmission network with nine (9) generating stations. The method involve the load flow analysis of the existing network with Egbin, Shiroro and Kanji generating stations chosen as a slack bus at different instances and simulated using Newton-Rapson method and Gauss Seidel. This study revealed that the use of Egbin power station as a slack bus brought about the lowest power mismatch in the network. The result also indicated violation of voltages in some of the network and high reactive power loss
Keywords: Grid, Load flow, Matlab tool, Reactive power, Slack bus
INVESTIGATING THE SELECTION OF A SUITABLE SLACK BUS: A CASE STUDY OF THE MULTI-GENERATING STATIONS OF THE NIGERIAN 330-KV POWER SYSTEM NETWORK (Review Completed - Accepted)
Slack bus is a bus with generating unit and used to balance the real power (P) and reactive power (Q) in the power system while performing load flow studies. This study therefore, investigated the best slack bus suitable to be used in the load flow study of the Nigerian 330-kVtransmission network with nine (9) generating stations. The method involve the load flow analysis of the existing network with Egbin, Shiroro and Kanji generating stations chosen as a slack bus at different instances and simulated using Newton-Rapson method and Gauss Seidel. This study revealed that the use of Egbin power station as a slack bus brought about the lowest power mismatch in the network. The result also indicated violation of voltages in some of the network and high reactive power loss.
Keywords: Grid, Load flow, Matlab tool, Reactive power, Slack bus
INVESTIGATING THE SELECTION OF A SUITABLE SLACK BUS: A CASE STUDY OF THE MULTI-GENERATING STATIONS OF THE NIGERIAN 330-KV POWER SYSTEM NETWORK (Review Completed - Accepted)
Slack bus is a bus with generating unit and used to balance the real power (P) and reactive power (Q) in the power system while performing load flow studies. This study therefore, investigated the best slack bus suitable to be used in the load flow study of the Nigerian 330-kVtransmission network with nine (9) generating stations. The method involve the load flow analysis of the existing network with Egbin, Shiroro and Kanji generating stations chosen as a slack bus at different instances and simulated using Newton-Rapson method and Gauss Seidel. This study revealed that the use of Egbin power station as a slack bus brought about the lowest power mismatch in the network. The result also indicated violation of voltages in some of the network and high reactive power loss.
Keywords: Grid, Load flow, Matlab tool, Reactive power, Slack bus