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A novel ultra-wideband (UWB) KAYI-shaped and common KITE-shaped ground plane tri-port antenna is proposed. The proposed research work has a small size of (30 × 30 × 1.6 mm 3 ). The MIMO antenna elements are placed in a KAYI-shaped (Y-shaped) with a symmetric phase shift of 120 ∘ between the nearby MIMO antennas element improving the isolation. The antenna's gain is more than 5 dBi for the entire bands of WiMax, WLAN, and X-band satellite communication. The suggested work includes notches at 3.2 GHz, 5.2 GHz, and 8.9 GHz, respectively. The notching characteristics are made possible by L-shaped slits for the WiMax band, the inverted U-shaped slot for WLAN, while the third is created by the interaction between the L-shaped and U-shaped notching elements. Results were measured after making the prototype antenna on the FR-4 substrate. The proposed antenna has good impedance matching for 2–20 GHz and three notching characteristics with high isolation among the MIMO elements. Mean effective gain (MEG), envelope correlation coefficient (ECC), and total active reflection coefficient (TARC) are the diversity metrics of MIMO antennas which are in good comparison to the proposed antenna. The antenna is a good candidate for deployment in wireless communication and MIMO applications. [ABSTRACT FROM AUTHOR]

The optimal allocation of protective devices is a serious issue in an electrical power system; in order to reduce the possibility of faults, the protection devices should be optimally placed. The paper presents a continuous genetic algorithm (CGA) for the optimal allocation of directional relays for the efficient energy minimization in a radial distribution system (DG). The algorithm is flexible to use for the changes and improvements in the optimal location for a DG unit and can optimize the energy consumption in the radial distribution system. The proposed algorithm has been implemented on IEEE 33 and 69-bus system using MATLAB (R2014b, MathWorks). Low energy consumption is a common design objective in an energy-constrained distribution system. Engineers, power utilities, and network operators can profit from the proposed methodology to enhance the use of DG in distribution networks. [ABSTRACT FROM AUTHOR]

In this paper, an intelligent approach for short-term wind speed forecasting (STWSF) is proposed. The STWSF models are developed to forecast the wind speed into a multi-step ahead forecasting, which is used to demonstrate the daily forecast results in One-Step-Ahead (OSA), Two-Step-Ahead (TSA), and Three-Step-Ahead (ThSA) based forecasting manner. To demonstrate the performance and results of the proposed approach, the real-site logged dataset is used for training and testing phase of the year 2015 to 2017. The STWSF is achieved recursively by utilizing the forecasted data in step-1 (OSA) as an input to generate the next forecasting data (in step-2 TSA) and the process is achieved upto level of step-3 (ThSA) forecasting. In order to results demonstration of fair adoptability of the proposed approach, different neural networks (NNs) models are developed for the same dataset, which shows that the proposed STWSF approach is outperformed and can be utilized for other locations for future applications. [ABSTRACT FROM AUTHOR]

This paper presents an improved directional overcurrent protection scheme using a two-stage hybrid GA-IPM algorithm. The developed approach considers the optimal time-current characteristic (TCC) selection and setting calculations of DOCRs simultaneously to protect meshed power networks. The developed formulation considers the optimal choice of the TCC curve and setting calculation simultaneously. Here, the problem is formulated as a mixed-integer nonlinear programming (MINLP) problem where a curve selection setting called curve-setting (CS) is added to the standard time multiplier-setting (TMS) and plug-setting (PS) of each relay in the DOCRs-based protection scheme. In modern relays, the selection of TCC curves is easily made from the available options. In this work, the IEC-standard curves have been considered to obtain the optimum characteristic curve selection and setting calculations. The formulated MINLP problem has been solved using the newly developed two-stage hybrid GA-IPM algorithm. In the first stage, the genetic algorithm (GA) is used to solve the problem formulated as MINLP. The obtained solution is considered the initial solution for the interior-point method (IPM) in the second state. The GA can solve the MINLP problems effectively, and IPM is superior in solving nonlinear programming problems, hence fine-tuning the results obtained by GA. The suitability and effectiveness of the proposed approach have been demonstrated on the IEEE 14 bus test system. Further, the efficacy of the developed method has been validated on an extensive IEEE 118 bus test system, and results are compared with those available in the literature. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RIS) are expected to bring about a revolutionary transformation in vehicular networks, thus paving the way for a future characterized by connected and automated vehicles (CAV). An RIS is a planar structure comprising many passive elements that can dynamically manipulate electromagnetic waves to enhance wireless communication by reflecting, refracting, and focusing signals in a programmable manner. RIS exhibits substantial potential for improving vehicle-to-everything (V2X) communication through various means, including coverage enhancement, interference mitigation, improving signal strength, and providing additional layers of privacy and security. This article presents a comprehensive survey that explores the emerging opportunities arising from the integration of RIS into vehicular networks. To examine the convergence of RIS and V2X communications, the survey adopted a holistic approach, thus highlighting the potential benefits and challenges of this combination. In this study, we examined several applications of RIS-aided V2X communication. Subsequently, we delve into the fundamental emerging technologies that are expected to empower vehicular networks, encompassing mobile edge computing (MEC), non-orthogonal multiple access (NOMA), millimeter-wave communication (mmWave), Artificial Intelligence (AI), and visible light communication (VLC). Finally, to stimulate further research in this domain, we emphasize noteworthy research challenges and potential avenues for future exploration. [ABSTRACT FROM AUTHOR]

Many technological advancements in the modern era have made actual use of electrical power and the constrained operating of power systems within stability limits. Some expeditious load variations and rising power demands initiate complications in voltage stability and can put stress on performance, leading to voltage instability. Voltage Stability Indices can be used to perform voltage stability assessment. This review evaluates various VSIs based on mathematical derivations, assumptions, critical values, and methodology. VSIs determine the maximum loadability, voltage collapse proximity, stability margin, weak areas, and contingency ranking. Stability indices can also specify the optimal placing and sizing of Distributed Generators. Thus, VSIs play a vital role in power system voltage stability. This review is a comprehensive survey of various indices and analyses their accuracy in determining the instability of power systems. Voltage stability is a crucial concern in operating a reliable power system, and the systematic evaluation of voltage stability is essential in a power system. This review considered and analyzed 34 indices from 138 articles from the literature for their significant performance in various power system stability problems. Of 33 indices, were 22 derived from transmission line parameters, referred to as line indices, and 12 from bus and line parameters, referred to as bus indices. [ABSTRACT FROM AUTHOR]

Recently, the concept of the microgrid (MG) has been developed to assist the penetration of large numbers of distributed energy resources (DERs) into distribution networks. However, the integration of DERs in the form of MGs disturbs the operating codes of traditional distribution networks. Consequently, traditional protection strategies cannot be applied to MG against short-circuit faults. This paper presents a novel intelligent protection strategy (NIPS) for MGs based on empirical wavelet transform (EWT) and long short-term memory (LSTM) networks. In the proposed NIPS, firstly, the three-phase current signals measured by protective relays are decomposed into empirical modes (EMs). Then, various statistical features are extracted from the obtained EMs. Afterwards, the extracted features along with the three-phase current measurement are input to three different LSTM network to obtain exact fault type, phase, and location information. Finally, a trip signal based on the obtained fault information is generated to disconnect the faulty portion from the rest of the MG. The significant feature of the proposed NIPS is that it does not need adaptive relaying and communication networks. Moreover, it is independent of the operating scenario and hence fault current magnitude. To evaluate the efficacy of the proposed NIPS, exhaustive simulations are performed on an international electro-technical commission (IEC) MG. The simulation results confirm the efficiency of the proposed NIPs in terms of accuracy, dependability, and security. Moreover, comparisons with existing intelligent protection schemes validate that the proposed NIPS is highly accurate, secure, and dependable. [ABSTRACT FROM AUTHOR]

In power systems protection, the optimal coordination of directional overcurrent relays (DOCRs) is of paramount importance. The coordination of DOCRs in a multi-loop power system is formulated as an optimization problem. The main objective of this paper is to develop the whale optimization algorithm (WOA) for the optimal coordination of DOCRs and minimize the sum of the operating times of all primary relays. The WOA is inspired by the bubble-net hunting strategy of humpback whales which leads toward global minima. The proposed algorithm has been applied to six IEEE test systems including the IEEE three-bus, eight-bus, nine-bus, 14-bus, 15-bus, and 30-bus test systems. Furthermore, the results obtained using the proposed WOA are compared with those obtained by other up-to-date algorithms. The obtained results show the effectiveness of the proposed WOA to minimize the relay operating time for the optimal coordination of DOCRs. [ABSTRACT FROM AUTHOR]

Highlights • This paper proposes two controlling methods for SVC in smart grid with connected EV charger. • SMC, ASRFC with a HVC are separately applied in the grid. • This paper presents usage of proposed methods for decreasing size of capacitor and value of apparent power loss. • The proposed scheme is validated through computer simulations of a 22.9-kV grid. Abstract Electric Vehicles (EVs) play a pivotal role in reducing the emissions of greenhouse gases in the world. Currently demand for EVs has abruptly increased for transportation and other applications. Using more EVs causes an increasing load on the power system. Random EV charging yields voltage distortion, which results in an unbalanced grid. In a distributed system, the connection of EVs to the grid may diminish the power factor, which increases the apparent power loss. The Static VAR Compensator (SVC), which is a FACTS device, is applied to the power system to compensate the voltage distortions and apparent power loss. In this paper, two controlling methods are contemplated and tested in a SVC to reduce the apparent power loss and minimize the capacitor size of the SVC in comparison with the conventional control method in a SVC. Proposed methods are also compared with the conventional control method used for SVC. The Slide Mode Controller (SMC) and Asymmetric Synchronous Reference Frame Controller (ASRFC) with a Harmonic Voltage Compensator (HVC) are separately applied in the grid. This paper presents usage of SMC and ASRFC methods for decreasing size of capacitor and value of apparent power loss through computer simulations of a 22.9-kV grid. With application of new controllers, apparent power loss of grid will be reduced as compared with conventional method of SVC controller. Moreover, the size of SVC capacitor can also be reduced. [ABSTRACT FROM AUTHOR]

Speech emotion recognition (SER) is a challenging task in human–computer interaction (HCI) systems. One of the key challenges in speech emotion recognition is to extract the emotional features effectively from a speech utterance. Despite the promising results of recent studies, they generally do not leverage advanced fusion algorithms for the generation of effective representations of emotional features in speech utterances. To address this problem, we describe the fusion of spatial and temporal feature representations of speech emotion by parallelizing convolutional neural networks (CNNs) and a Transformer encoder for SER. We stack two parallel CNNs for spatial feature representation in parallel to a Transformer encoder for temporal feature representation, thereby simultaneously expanding the filter depth and reducing the feature map with an expressive hierarchical feature representation at a lower computational cost. We use the RAVDESS dataset to recognize eight different speech emotions. We augment and intensify the variations in the dataset to minimize model overfitting. Additive White Gaussian Noise (AWGN) is used to augment the RAVDESS dataset. With the spatial and sequential feature representations of CNNs and the Transformer, the SER model achieves 82.31% accuracy for eight emotions on a hold-out dataset. In addition, the SER system is evaluated with the IEMOCAP dataset and achieves 79.42% recognition accuracy for five emotions. Experimental results on the RAVDESS and IEMOCAP datasets show the success of the presented SER system and demonstrate an absolute performance improvement over the state-of-the-art (SOTA) models. [ABSTRACT FROM AUTHOR]

This paper proposes a two-degree-of-freedom (2-DoF) modulation technique for the efficient optimization of an open-loop three-phase dual-active-bridge series resonant converter (3P-DABSRC). The efficiency and performance of an conventional dual-active-bridge (DAB) converter decrease when it is operated over a wide range of voltage gain. The efficiency and performance of a DAB converter depend upon the switching and conduction losses. Circulating current is the main cause of conduction loss, and hard switching of active switches adds a switching loss. To increase the performance of DAB converters, the first objective is to minimize the conduction loss, and the second objective is to reduce the switching loss. Still, unfortunately, it is not easy to achieve these two objectives simultaneously. Circulating current helps us to reduce the switching loss, but the unbridled amount of circulating current will increase the root-mean-square inductor tank current, and as a result, the conduction loss will be increased. This paper presents an advanced modulation scheme for a 3P-DABSRC that can be used not only in low-power applications, but also in high-power applications. The DABSRC consists of a series LC resonant tank, isolated high-frequency transformer, and dual active bridge connected with the primary and secondary sides of the transformer. The proposed 2-DoF modulation technique not only minimizes the circulating current, but also eliminates the switching loss. Keeping the minimum phase shift between the primary and secondary bridges reduces the circulating current, and thus, all switches can be operated with zero-voltage switching (ZVS) for the entire power range. The power is controlled by changing the switching frequency from 45 to 63 kHz. To confirm the proposed topology and modulation scheme, a 1500 W DABSRC, which interfaces a 300 V DC bus with a 75 V DC bus, is simulated. A loss model of the proposed topology is also made to verify the results. The simulation results are used to confirm the proper operation of the 3P-DABSRC. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surfaces (IRS) and mobile edge computing (MEC) have recently attracted significant attention in academia and industry. Without consuming any external energy, IRS can extend wireless coverage by smartly reconfiguring the phase shift of a signal towards the receiver with the help of passive elements. On the other hand, MEC has the ability to reduce latency by providing extensive computational facilities to users. This paper proposes a new optimization scheme for IRS-enhanced mobile edge computing to minimize the maximum computational time of the end users' tasks. The optimization problem is formulated to simultaneously optimize the task segmentation and transmission power of users, phase shift design of IRS, and computational resource of mobile edge. The optimization problem is non-convex and coupled on multiple variables which make it very complex. Therefore, we transform it to convex by decoupling it into sub-problems and then obtain an efficient solution. In particular, the closed-form solutions for task segmentation and edge computational resources are achieved through the monotonical relation of time and Karush–Kuhn–Tucker conditions, while the transmission power of users and phase shift design of IRS are computed using the convex optimization technique. The proposed IRS-enhanced optimization scheme is compared with edge computing nave offloading, binary offloading, and edge computing, respectively. Numerical results demonstrate the benefits of the proposed scheme compared to other benchmark schemes. [ABSTRACT FROM AUTHOR]

An induction motor is generally used in industrial applications because it is reliable, robust, and low cost. Reliability is one of the essential parameters based on which the motor is selected, and the induction motor primarily comes into force. The well-founded induction motor gives good results under various operating states. To achieve this, the values of the motor are kept in mind. Dynamic simulation plays a significant part in evaluating the model's design process to eliminate design errors in typical construction types and when testing the motor drive system. The induction motor is modeled in a synchronously revolving rotor flux-oriented frame, which is used as a reference. For sensorless vector control and induction motor control methods, accurate knowledge of a few induction motor parameters is necessary. The presentation of the drive will degrade if the original data in the motor do not match the values utilized in the controller. Various mechanisms have been developed to calculate the online and offline parameters of the induction machine for its application in high-performance drives. The foremost grail of this review paper is to present dynamic modeling and other considerable approaches used for estimating the induction motor parameter. This paper also constitutes some simulation examples related to dynamic modeling and parameter estimation techniques, which may be useful for specialists in the field of electric drive control systems. [ABSTRACT FROM AUTHOR]

Type-1 diabetes mellitus (T1DM) is a challenging disorder which essentially involves regulation of the glucose levels to avoid hyperglycemia as well as hypoglycemia. For this purpose, this research paper proposes and develops control algorithms using an intelligent predictive control model, which is based on a UVA/Padova metabolic simulator. The primary objective of the designed control laws is to provide an automatic blood glucose control in insulin-dependent patients so as to improve their life quality and to reduce the need of an extremely demanding self-management plan. Various linear and nonlinear control algorithms have been explored and implemented on the estimated model. Linear techniques include the Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR), and nonlinear control strategy includes the Sliding Mode Control (SMC), which are implemented in this research work for continuous monitoring of glucose levels. Performance comparison based on simulation results demonstrated that SMC proved to be most efficient in terms of regulating glucose profile to a reference level of 70 mg/dL compared to the classical linear techniques. A brief comparison is presented between the linear techniques (PID and LQR), and nonlinear technique (SMC) for analysis purposes proving the efficacy of the design. [ABSTRACT FROM AUTHOR]

The relay coordination problem is of dire importance as it is critical to isolate the faulty portion in a timely way and thus ensure electrical network security and reliability. Meanwhile a relay protection optimization problem is highly constraint and complicated problem to be addressed. To fulfill this purpose, Harris Hawk Optimization (HHO) is adapted to solve the optimization problem for Directional Over-current Relays (DOCRs) and numerical relays. As it is inspired by the intelligent and collegial chasing and preying behavior of hawks for capturing the prey, it shows quite an impressive result for finding the global optimum values. Two decision variables; Time Dial Settings (TDS) and Plug Settings (PS) are chosen as the decision variables for minimization of overall operating time of relays. The proposed algorithm is implemented on three IEEE test systems. In comparison to other state-of-the-art nature inspired and traditional algorithms, the results demonstrate the superiority of HHO. [ABSTRACT FROM AUTHOR]

In this paper, Improved Moth Flame Optimization (IMFO) algorithm is implemented to restore power flow solvability by transferring of adequate amount of load shedding (LS) through the power system. Shunt Flexible Alternating Current Transmission System (FACTS) devices including Static VAR Compensator (SVC) and Static Synchronous Compensator (STATCOM) are incorporated with the system for obtaining better reactive power support. Maximum power system loadability is obtained using Continuation Power Flow (CPF). Both of normal operation and contingency conditions for generator and bus outages are considered for the fruition of the validity of the suggested method to operate under various conditions. The proposed approach is validated using IEEE-30 bus standard test system. The obtained results manifest the capability of the suggested method to reduce the LS values leading to continuous service to the customers and the capability of preventing voltage collapse and restore the bus voltages to the permissible limits. The emulation results reveal the effectiveness of the suggested method for enhancement of the power system loadability. [ABSTRACT FROM AUTHOR]

The remarkable progress of power electronic converters (PEC) technology has led to their increased penetration in distributed energy systems (DES). Particularly, the direct current (dc) nanogrid-based DES embody a variety of sources and loads, connected through a central dc bus. Therefore, PECs are required to be employed as an interface. It would facilitate incorporation of the renewable energy sources and battery storage system into dc nanogrids. However, it is more challenging as the integration of multiple modules may cause instabilities in the overall system dynamics. Future dc nanogrids are envisioned to deploy ready-to-use commercial PEC, for which designers have no insight into their dynamic behavior. Furthermore, the high variability of the operating conditions constitute a new paradigm in dc nanogrids. It exacerbates the dynamic analysis using traditional techniques. Therefore, the current work proposes behavioral modeling to perform system level analysis of a dc nanogrid-based DES. It relies only on the data acquired via measurements performed at the input–output terminals only. To verify the accuracy of the model, large signal disturbances are applied. The matching of results for the switch model and its behavioral model verifies the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

It is difficult for wireless local area networks (WLANs), IEEE 802.11ax high-efficiency WLAN (HEW), to join next-generation innovations such as 5th generation (5G) and Internet of Things (IoT) because they still have their conventional channel access mechanism as their essential medium access control (MAC) protocol. The MAC protocol uses a traditional binary exponential backoff (BEB) algorithm to access channel resources that depend on the noncognitive increment of contention parameters for collision avoidance. In BEB, the collision issue increases with the increase in connected devices in the network due to a fixed contention window size. The larger the size of the network, the larger the collision in the network. To avoid such a circumstance, in this paper, we propose a sliding group window (sGW) mechanism dependent on collision-point assessment in order to improve the performance of MAC protocol for HEW. The proposed algorithm additionally presents a rebacking off for collision avoidance (ReBOCA) system for sGW, which combines the uniform dispersion of the contention parameters. This variation of an ordinary backoff algorithm permits the reasonable sliding of the user groups in the case of collision. The algorithm explicitly accounts for the peculiarities of dense environments and backward compatibility. Key aspects of the proposed solution include collision-point estimation, rebacking off for collision distribution convergence for fair treatment, and adaptive sliding of group windows to mitigate contention unfairness. We further formulated a closed-form Markov chain model for the performance analysis of our proposed sGW with ReBOCA scheme. Theoretical and practical results prove that our proposed scheme achieved maximal efficiency, even under dense environments. An increase in throughput with a lower packet collision probability was achieved with the proposed mechanism, and the efficiency increased as the number of contending stations increased than compared to traditional BEB performance. Our proposed ReBOCA mechanism enhanced network throughput by 38.18% than compared to the conventional BEB mechanism. [ABSTRACT FROM AUTHOR]

In this paper, a modified Rao-2 (MRao-2) algorithm is proposed to solve the problem of optimal power flow (OPF) in a power system incorporating renewable energy sources (RES). Quasi-oppositional and Levy flight methods are used to improve the performance of the Rao algorithm. To demonstrate effectiveness of the MRao-2 technique, it is tested on two standard test systems: an IEEE 30-bus system and an IEEE 118-bus system. The objective function of the OPF is the minimization of fuel cost in five scenarios. The IEEE 30-bus system reflects fuel cost minimization in three scenarios (without RES, with RES, and with RES under contingency state), while the IEEE 118-bus system reflects fuel cost minimization in two scenarios (without RES and with RES). The achieved results of various scenarios using the suggested MRao-2 technique are compared with those obtained using five recent techniques: Atom Search Optimization (ASO), Turbulent Flow of Water-based Optimization (TFWO), Marine Predators Algorithm (MPA), Rao-1, Rao-3 algorithms, as well as the conventional Rao-2 algorithm. Those comparisons confirm the superiority of the MRao-2 technique over those other algorithms in solving the OPF problem. [ABSTRACT FROM AUTHOR]

The 5th generation (5G) wireless networks propose to address a variety of usage scenarios, such as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). Due to the exponential increase in the user equipment (UE) devices of wireless communication technologies, 5G and beyond networks (B5G) expect to support far higher user density and far lower latency than currently deployed cellular technologies, like long-term evolution-Advanced (LTE-A). However, one of the critical challenges for B5G is finding a clever way for various channel access mechanisms to maintain dense UE deployments. Random access channel (RACH) is a mandatory procedure for the UEs to connect with the evolved node B (eNB). The performance of the RACH directly affects the performance of the entire network. Currently, RACH uses a uniform distribution-based (UD) random access to prevent a possible network collision among multiple UEs attempting to access channel resources. However, in a UD-based channel access, every UE has an equal chance to choose a similar contention preamble close to the expected value, which causes an increase in the collision among the UEs. Therefore, in this paper, we propose a Poisson process-based RACH (2PRACH) alternative to a UD-based RACH. A Poisson process-based distribution, such as exponential distribution, disperses the random preambles between two bounds in a Poisson point method, where random variables occur continuously and independently with a constant parametric rate. In this way, our proposed 2PRACH approach distributes the UEs in a probability distribution of a parametric collection. Simulation results show that the shift of RACH from UD-based channel access to a Poisson process-based distribution enhances the reliability and lowers the network's latency. [ABSTRACT FROM AUTHOR]

• The sizing of PV and BES is determined by modified HGSO algorithm. • The probabilistic of PV and load demand is considered in the methodology. • The total system power loss is defined as single objective function. • The modified HGSO algorithm is compared with HGSO algorithm. • Numerical results proved the efficiency of the proposed algorithm. Recently, solar photovoltaic (PV) is becoming widespread overall the world as it is a renewable free source of energy. PV alone is considered as a non-dispatchable source as it relies on variable source during the day. Therefore, the primary goal of this paper is to integrate the battery energy storage (BES) with PV as a dispatchable source in radial distribution system (RDS). In addition, this paper proposes a modified version of Henry gas solubility optimization algorithm (modified HGSO) to improve the performance of the conventional HGSO algorithm. This modified version is created by inserting the simulated annealing (SA) algorithm into the conventional HGSO algorithm. The proposed algorithm is used to determine the best size of PV and BES, considering the probabilistic of PV generation and time-varying load, in order to minimize the total system power loss. IEEE 69-bus RDS is used to demonstrate the effectiveness of proposed algorithm. The results show that integration of PV and BES in RDS reduces the system power loss, enhances the system voltage and increases the system capacity. The results also prove that the proposed algorithm is highly effective in integrating multiple PV and BES units in distribution system compared with the conventional algorithms. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Renewable energy resources like solar energy, wind energy, hydro energy, photovoltaic etc. are gaining much importance due to the day by day depletion of conventional resources. Owing to the lower efficiencies of renewable energy resources, much attention has been paid to improving them. The concept of utilizing phase change materials (PCMs) has attracted wide attention in recent years. This is due to their ability to extract thermal energy when used in collaboration with photovoltaic (PV), thus improving the photoelectric conversion efficiency. In this paper, the objective is to design and fabricate a novel thermal energy storage system using phase change material. An investigation on the characteristics of Potash Alum as a phase change material due to its low cost, easy availability and its usage as an energy storage for the indoor purposes are taken into account. The use of a latent heat storage system using phase change materials (PCMs) is an effective way of storing thermal energy and has the advantage of high-energy storage density and the isothermal nature of the storage process. In the current study, potash alum was identified as a phase change material combined with renewable energy sources, that can be efficiently and effectively used in storing thermal energy at compartively lower temperatures that can later be used in daily life heating requirements.A parabolic dish which acts of a heat collector is used to track and reflects solar radiation at a single point on a receiver tank. Heat transfer from the solar collector to the storage tank is done by using a circulating heat transfer fluid with the help of a pump. The experimental results show that this system is capable of successfully storing and utilizing thermal energy on indoor scale such as cooking, heating and those applications where temperature is below 92 °C. [ABSTRACT FROM AUTHOR]