Electricity and heat energy carriers are mostly produced by the fossil fuel sources that are conventionally operated independently, but these carriers have low efficiency due to heat losses. Moreover, a high share of variable renewable energy sources disrupts the power system reliability and flexibility. Therefore, the coupling of multiple energy carriers is underlined to address the above-mentioned issues that are supported by the latest technologies, such as combined heat and power, heat pumps, demand response, and energy storages. These coupling nodes in energy hubs stimulate the conversion of the electric power system into the integrated energy system that proves to be cost-effective, flexible, and carbon-free. The proposed work uses EnergyPLAN to model electricity, district, and individual heating integrated energy system of China for the year 2020. Furthermore, the addition of heat pumps, thermal storage, and demand response is analyzed in different scenarios to minimize the annual costs, fuel consumption, and CO ₂ emissions. Technical simulation strategy is conducted for optimal operation of production components that result in the reduction of the above-mentioned prominent factors while calculating the critical and exportable excess electricity production. The simulation results demonstrate that demand response and thermal storage significantly enhance the share of variable renewable energy sources. In addition, it substantially reduces the annual costs and fuel consumption, while heat pump increases the system efficiency.

Photovoltaic (PV) is a highly promising energy source because of its environment friendly property. However, there is an uncertainty present in the modeling of PV modules owing to varying irradiance and temperature. To solve such uncertainty, the fuzzy logic control-based intelligent maximum power point tracking (MPPT) method is observed to be more suitable as compared with conventional algorithms in PV systems. In this paper, an isolated PV system using a push pull converter with the fuzzy logic-based MPPT algorithm is presented. The proposed methodology optimizes the output power of PV modules and achieves isolation with high DC gain. The DC gain is inverted into a single phase AC through a closed loop fuzzy logic inverter with a low pass filter to reduce the total harmonic distortion (THD). Dynamic simulations are developed in Matlab/Simulink by MathWorks under linear loads. The results show that the fuzzy logic algorithms of the proposed system efficiently track the MPPT and present reduced THD.

Medical image fusion (MIF) has received painstaking attention due to its diverse medical applications in response to accurately diagnosing clinical images. Numerous MIF methods have been proposed to date, but the fused image suffers from poor contrast, non-uniform illumination, noise presence, and improper fusion strategies, resulting in an inadequate sparse representation of significant features. This paper proposes the morphological preprocessing method to address the non-uniform illumination and noise by the bottom-hat–top-hat strategy. Then, grey-principal component analysis (grey-PCA) is used to transform RGB images into gray images that can preserve detailed features. After that, the local shift-invariant shearlet transform (LSIST) method decomposes the images into the low-pass (LP) and high-pass (HP) sub-bands, efficiently restoring all significant characteristics in various scales and directions. The HP sub-bands are fed to two branches of the Siamese convolutional neural network (CNN) by process of feature detection, initial segmentation, and consistency verification to effectively capture smooth edges, and textures. While the LP sub-bands are fused by employing local energy fusion using the averaging and selection mode to restore the energy information. The proposed method is validated by subjective and objective quality assessments. The subjective evaluation is conducted by a user case study in which twelve field specialists verified the superiority of the proposed method based on precise details, image contrast, noise in the fused image, and no loss of information. The supremacy of the proposed method is further justified by obtaining 0.6836 to 0.8794, 0.5234 to 0.6710, and 3.8501 to 8.7937 gain for ${\mathrm{Q}}_{\mathrm{F}}^{\mathrm{AB}}$, CRR, and AG and noise reduction from 0.3397 to 0.1209 over other methods for objective parameters.