A dual-band bandpass filter (BPF) composed of a coupling structure and a bent T-shaped resonator loaded by small L-shaped stubs is presented in this paper. The first band of the proposed BPF covers 4.6 to 10.6 GHz, showing 78.9% fractional bandwidth (FBW) at 7.6 GHz, and the second passband is cantered at 11.5 GHz with a FBW of 2.34%. The bent T-shaped resonator generates two transmission zeros (TZs) near the wide passband edges, which are used to tune the bandwidth of the first band, and the L-shaped stubs are used to create and control the narrow passband. The selectivity performance of the BPF is analyzed using the transfer function extracted from the lumped circuit model verified by a detailed even/odd mode analysis. The BPF presents a flat group delay (GD) of 0.45 ns and an insertion loss (IL) less than 0.6 dB in the wide passband and a 0.92 IL in the narrow passband. A prototype of the proposed BPF is fabricated and tested, showing very good agreement between the numerically predicted and measured results.

Energy generation and its utilization is bound to increase in the following years resulting in accelerating depletion of fossil fuels, and consequently, undeniable damages to our environment. Over the past decade, despite significant efforts in renewable energy realization and developments for electricity generation, carbon dioxide emissions have been increasing rapidly. This is due to the fact that there is a need to go beyond the power sector and target energy generation in an integrated manner. In this regard, energy systems integration is a concept that looks into how different energy systems, or forms, can connect together in order to provide value for consumers and producers. Cogeneration and trigeneration are the two most well established technologies that are capable of producing two or three different forms of energy simultaneously within a single system. Integrated energy systems make for a very strong proposition since it results in energy saving, fuel diversification, and supply of cleaner energy. Optimization of such systems can be carried out using several techniques with regards to different objective functions. In this study, a variety of optimization methods that provides the possibility of performance improvements, with or without presence of constraints, are demonstrated, pinpointing the characteristics of each method along with detailed statistical reports. In this context, optimization techniques are classified into two primary groups including unconstrained optimization and constrained optimization techniques. Further, the potential applications of evolutionary computing in optimization of Integrated Energy Systems (IESs), particularly Combined Heat and Power (CHP) and Combined Cooling, Heating, and Power (CCHP), utilizing renewable energy sources are grasped and reviewed thoroughly. It was illustrated that the employment of classical optimization methods is fading out, replacing with evolutionary computing techniques. Amongst modern heuristic algorithms, each method has contributed more to a certain application; while the Genetic Algorithm (GA) was favored for thermoeconomic optimization, Particle Swarm Optimization (PSO) was mostly applied for economic improvements. Given the mathematical nature and constraint satisfaction property of Mixed-Integer Linear Programming (MILP), this method is gaining prominence for scheduling applications in energy systems.

Nowadays, ever-increasing energy demands and the depletion of fossil fuels require efficient and environmentally friendly technologies for energy generation. In this context, energy systems integration makes for a very strong proposition since it results in energy saving, fuel diversification, and the supply of cleaner energy. To this end, it is of the utmost importance to realize the current developments in this field and portray the state of the art of renewable generation in integrated energy systems. This review evaluates the utilization of bioenergy in cogeneration and trigeneration systems. The statistical reports of bioenergy and combined heat and power deployments in 28 countries of the European Union are discussed. Then, the most common research objectives of biomass-fueled combined heat and power systems are classified into three primary performance analyses, namely, energy and exergy analysis, thermo-economic optimization, and environment assessment. The influencing parameters of biomass utilization on each type of assessment are discussed, and the basic principles for carrying out such analyses in energy systems are explained. It is illustrated that the properties of feedstock, selection of appropriate conversion technology, associated costs with the biomass-to-bioenergy process, and sustainability of biomass are the primary influencing factors that could significantly affect the results of each assessment.

Cloud-to-ground (CG) lightning is a natural phenomenon that poses significant threats to human safety, infrastructure, and equipment. The destructive impacts of lightning strikes on humans and their property have been a longstanding concern for both society and industry. Countries with high thunderstorm frequencies, such as Malaysia, experience significant fatalities and damage due to lightning strikes. To this end, a lightning locating system (LLS) was developed and deployed in a 400 km² study area at the University Technology Malaysia (UTM), Johor, Malaysia for detecting cloud-to-ground lightning discharges. The study utilized a particle swarm optimization (PSO) algorithm as a mediator to identify the best location for a lightning strike. The algorithm was initiated with 30 particles, considering the outcomes of the MDF and TDOA techniques. The effectiveness of the PSO algorithm was found to be dependent on how the search process was arranged. The results of the detected lightning strikes by the PSO-based LLS were compared with an industrial lightning detection system installed in Malaysia. From the experimental data, the mean distance differences between the PSO-based LLS and the industrial LLS inside the study area was up to 573 m. Therefore, the proposed PSO-based LLS would be efficient and accurate to detect and map the lightning discharges occurring within the coverage area. This study is significant for researchers, insurance companies, and the public seeking to be informed about the impacts of lightning discharges.

The interconnection of wind power plants (WPPs) with distribution networks has posed many challenges concerned with voltage stability at the point of common coupling (PCC). In a distribution network connected WPP, the short-circuit ratio (SCR) and impedance angle ratio seen at PCC (X/R_PCC) are the most important parameters, which affect the PCC voltage (V_PCC) stability. Hence, design engineers need to conduct the WPP siting and sizing assessment considering the SCR and X/R_PCC seen at each potential PCC site to ensure that the voltage stability requirements defined by grid codes are provided. In various literature works, optimal siting and sizing of distributed generation in distribution networks (DG) has been carried out using analytical, numerical, and heuristics approaches. The majority of these methods require performing computational tasks or simulate the whole distribution network, which is complex and time-consuming. In addition, other works proposed to simplify the WPP siting and sizing have limited accuracy. To address the aforementioned issues, in this paper, a decision tree algorithm-based model was developed for WPP siting and sizing in distribution networks. The proposed model eliminates the need to simulate the whole system and provides a higher accuracy compared to the similar previous works. For this purpose, the model accurately predicts key voltage stability criteria at a given interconnection point, including V_PCC profile and maximum permissible wind power generation, using the SCR and X/R_PCC values seen at that point. The results confirmed the proposed model provides a noticeable high accuracy in predicting the voltage stability criteria under various validation scenarios considered.

The global climate protection policy aimed at achieving a zero greenhouse gas emissions target has led to the fast incorporation of large-scale photovoltaics into the power network. The conventional AC grid was not modeled to be incorporated with large-scale non-synchronous inverter-based energy resources (IBR). Incorporating inertia-free IBR into the grid leads to technical issues such as the degradation of system strength and inertia, therefore affecting the safety and reliability of the electrical power system. This research introduced a new solution to incorporate a flywheel in the rotor of a synchronous machine to improve the dynamic inertia control during a system disruption and to maintain the constancy of the system. The objective of this work is to enhance large-scale photovoltaic systems in such a way that they can avoid failures during a fault. A model of transient constancy with two synchronous generators and a LSPV is established in PowerWorld modeling software. A line-to-ground and three-phase fault are simulated in a system with up to 50% IBR penetration. The outcomes showed that the power network was able to ride through faults (RTFs) and that the stability of frequency and voltage are enhanced because of a flywheel that improved grid inertia and strength.