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State-estimation plays a vital role to monitor, observe and understand the combined heat and electric network. In this paper, a hybrid framework is presented to accurately estimate the system states of electric distribution network and heat network, using the limited non-redundant measurements obtained from supervisory control and data acquisition and advanced metering infrastructure systems. The presented hybrid framework involves two steps, namely, the state-forecasting and the state-estimation. The state-forecasting uses a deep neural network to forecast the system states at every fifteen minutes interval, while these forecasted states are further used by the hybrid estimator, which uses a robust extended Kalman filter to estimate the system states with help of both datasets corresponding to supervisory control and data acquisition and advanced metering infrastructure systems, at hourly interval. The proposed framework does not completely rely on the system model at different instants. The effectiveness of the method is validated through thorough comparisons with simulation studies carried out using the Barry Island test system, United Kingdom. Satisfactory performance is observed even with the presence of bad data in the measurements.

In conventional power systems, stability is ensured successfully because of large synchronous generators, where, during transient conditions, the inertia and dynamics of the synchronous generators help to retain stability. On the contrary, inverter-interfaced distributed energy resources suffer from maintaining stability because of their quick dynamics (opposite to the concept of inertia). Therefore, there exists a tradeoff between response and stability aspects and this is referred to as transient performance problem in microgrids. Conventionally, this problem is addressed from the controller side by increasing its bandwidth thereby leading to better disturbance rejection and immunity against parameter changes. Since the classification of the disturbances (as small or large) is not straightforward and uncertain, an increase in the controller's bandwidth beyond a certain limit is not possible. Therefore, it is understood that the transient performance improvement cannot be achieved from the controller alone. Hence, the chances of improving performance from other approaches in the case of grid-connected mode and advanced control strategies for the controller in the case of islanded mode need to be investigated. With this intent, a comprehensive investigation of state-of-the-art approaches and methods to improve transient performance in microgrids is carried out in this article. This work is carried out in three stages. Initially, it explores various technical challenges that are involved and possible approaches to address these challenges. Next, a critical review of each approach is carried out based on their philosophy to improve transient performance. Furthermore, a comparative analysis that projects the scope of each approach is elucidated. Finally, some future research directions are proposed to enhance the effectiveness of key approaches.

Abstract The photovoltaic (PV) power generation and cooling demand of the air conditioner are increased along with an increase in solar irradiation. Therefore, considering such fact, in this paper, PV power is integrated with the air conditioner to support the grid. With recent developments in power electronics, the air conditioning systems are operated in variable speed using variable frequency drive (VFD) technology. In this paper, taking the advantage of the VFD technology, PV power is directly injected into the DC bus of VFD using an isolated DC‐DC converter. In this methodology, due to the high‐frequency DC‐DC conversion, high power DC‐AC (50 Hz) stage is eliminated, and seamless power is transferred from PV generation to the load without interrupting the main operation of the air conditioner. Thus, the reliability of the system is enhanced with the reduction in overall cost, conversion losses and bulkiness. With the PV power support, the peak amplitude of the grid current is reduced and consequently the power consumption, reactive power intake from the grid, as well as the harmonics component of the grid current, are reduced. This scheme is used in rural or suburban areas where the solar profile is significant and air conditioner is extensively used.

Abstract The increase in the numbers of electric vehicles (EVs) is seen as an upgrading of the existing vehicles for various reasons. This calls for an in‐depth analysis of the heart of these vehicles—the motor. A motor in an electric vehicle propulsion system is a crucial component that has the ability to affect the efficiency, weight, cost, reliability, power output and performance. Hence a detailed comparative study, that compares the existing types and topologies of various motors, is the need of the hour. The various motors that can be used in electric traction, namely DC, induction, switched reluctance, permanent magnet brushless AC motors and permanent magnet brushless DC motors, are reviewed in view of their capabilities with respect to EV propulsion. A detailed review is presented of existing motors and the application of power electronic techniques to EVs, and recommendations for some new designs of brushless DC motors. These include permanent magnet hybrid motors, permanent magnet spoke motors and permanent magnet inset motors.

Abstract The intermittent nature of renewable energy sources results in an interruptible and inadequate power. The integration of the battery energy storage to renewable energy sources provides reliable and continuous power to the loads. Further, the high penetration of renewable energy sources raises the power quality problems in the grid. This work deals with performance improvement of PV‐battery energy storage based energy conversion system achieved through implementing a multi‐structural adaptive circular noise estimation control for its grid connected mode. The control is developed for the grid side voltage source converter, which provides the power quality improvement and automated transition from grid connected mode to standalone mode or vice‐versa. It provides multi‐functional features such as harmonics extraction, DC offset elimination, and power quality improvement in PV‐battery energy storage based energy conversion system even at nonlinear loading condition in grid connected mode. In standalone mode, the amplitude and waveform of load voltage are controlled sinusoidal by the voltage control. Performance of PV‐battery energy storage based energy conversion system is studied to validate the acceptability of these controls according to the IEEE‐519 standard.

This article proposes the idea of using Solar Energy (SE) as a source of power for designing and developing a standalone air-cooling system. This type of application is particularly suited for rural areas that have a considerable amount of solar radiation and have no access to grid systems. The proposed system is comprised of a photovoltaic (PV) array, DC-DC boost converter and DC-DC buck converter. Two Permanent Magnet Brushless Direct Current (PMBLDC) motors are employed to drive a centrifugal water pump and an air blower coupled to their individual shafts. The air blower is connected with a DC-DC boost converter that ensures a maximum power point (MPP) operation. A centrifugal water pump is connected with a DC-DC buck converter. The challenging task in an air cooling system is to maintain the constant speed of the blower under variable irradiance conditions. The power provided by the solar PV array can be shared between the two DC-DC converters in such a way that the BLDC motor connected with the blower will maintain a constant speed by maintaining the constant voltage of the DC-DC boost converter. The rest of the available PV power will be handled by the pump. The suitability of the proposed system for various perturbations is evaluated by simulating the proposed system using a MATLAB/Simulink and is validated by conducting experiments. Case studies have been performed with a variable PV irradiance and the results are explored.

This paper presents an application of power-line communication (PLC) as a viable solution for frequency regulation in a smart microgrid. The microgrid under consideration comprises a diesel generator with a frequency controller and another synchronous generator operating in the constant power mode. Frequency regulation is achieved in the microgrid by communicating the frequency deviation (information) from the control center to the diesel generator using PLC. The information received at the other end is used for frequency regulation. A simple yet effective M -ary amplitude-shift keying (ASK) modulation-based PLC system is proposed for information transmission. A comparative analysis of M -ary ASK and M -ary frequency-shift keying (FSK)-based PLC systems is also presented. Approximate closed-form expressions for the average symbol error rate and the average achievable rate are derived for both the PLC systems, assuming that the PLC channel coefficients and the additive impulsive noise samples are derived from a log-normal distribution and a Bernoulli-Gaussian process, respectively. The results show that M -ary ASK is a better choice for PLC than M -ary FSK. Furthermore, the delay introduced in the control loop while using the proposed PLC system is negligible, and therefore, the stability of the microgrid is also ensured.

Electric Vehicles (EVs) can be considered as a flexible source of energy which can receive some benefit in terms of incentives for selling their energy. For efficient and economic trading amongst the EV owners, various researchers have proposed a variety of preference based matching algorithms like College Admission Framework (CAF), Max-weight, Merge and Split, Gale-Shapley Algorithm and Brute-Force Algorithm etc, where buyer and seller EVs can exchange energy and receive better payoffs. Unlike the above mentioned algorithms, in this paper the participating entities do not submit the preferences menu (which contains preferred choices of sellers (of a buyer) and of buyers (for a seller)) to a central authority.) However, this paper proposes an assignment energy trading game where no central authority is needed, the matching algorithm is hosted on cloud which matches charging and discharging of EVs based on their aspiration level and bids. The contribution of the work is to deduce the bids and aspiration level of charging and discharging EVs which is not considered in any of the existing work. Another contribution of the work is the behavioral assignment game that eludes the need of integer linear programming problem and deduces the convergence of game by adjustments of aspiration levels. Futhermore, the entire algorithm is cloud hosted with no middleman hence trading EVs identities are concealed from each other making the system unbiased. The proposed game helps both the buyer and the seller side of EVs to achieve their best bids as well as by reducing grid dependency it boosts the profit margin of the charging stations (CS).

This study presents automatic generation control (AGC) of interconnected power systems comprising of two thermal and one hydro area having integral controllers. Emphasis is given to a delay in the area control error for the actuation of the supplementary controller and to examine its impact on the dynamic response against no delay which is usually the practice. Analysis is based on 50% loading condition in all the areas. The system performance is examined considering 1% step load perturbation. Results reveal that delayed mode operation provides a better system dynamic performance compared with that obtained without delay and has several distinct merits for the governor. The delay is linked with reduction in wear and tear of the secondary controller and hence increases the life of the governor. The controller gains are optimised by particle swarm optimisation. The performance of delayed mode operation of AGC at other loading conditions is also analysed. An attempt has also been made to find the impact of weights for different components in a cost function used to optimise the controller gains. A modified cost function having different weights for different components when used for controller gain optimisation improves the system performance.