Volume 23, Issue 5

This paper focuses on investigating the steady-state and dynamic performance of the permanent magnet synchronous motor (PMSM) drive using modified model predictive torque control (MPTC) method with multi-level inverters (MLIs). The MPTC method is simple and easy to implement for motor control as they don’t involve cascaded PI controllers unlike required the conventional controllers, such as field oriented control (FOC) and direct torque and flux control (DTFC). The proposed modified MPTC method eliminates the use of weighing factors and it is a fusion of model predictive current control (MPCC) and MPTC. Initially, the proposed modified MPTC fed PMSM drive is implemented using two-level inverter. It provides better steady-state and dynamic performance, but the ripple contents of torque, flux, and currents are high. In order to reduce the ripple contents and improve the performance of the PMSM drive, a modified MPTC is implemented using three-level inverter. The proposed modified MPTC fed PMSM drive using two-level and three-level inverters are simulated in MATLAB/SIMULINK environment under different operating conditions, such as no-load, loading, speed reversal, step change in speed operations. In order to show the effectiveness and feasibility of the proposed method, it is also validated with the experimental results.

The resilience of the power grid is taking a vital role in the energy supply and distribution process. But due to the rapid growth of integration of renewable distributed energy sources to the traditional power grid, the nature of the trading system is shifted from the centralized to decentralized or distributed manner. Blockchain is one of the most emerging security technologies that change the dimension of the financial and energy sector with openness and complete freedom. Blockchain implemented distributed energy trading promotes decentralized electricity markets. The physical system consists of the planning of the routing of energy from one place to another. A user can not send power to another customer in any severe outage or natural disaster in a traditional system. The user cannot participate in the trade globally. So in this proposed methodology, the connections of each customer to the central grid through several microgrids have been shown. In this work, an innovative approach in trading and finding a solution to a payment method is proposed. Ethereum blockchain-based smart contracts completed the entire trading system in automation mode in our proposed system. Any power outage at one place can be compensated by routing a new path of energy inflow from another active source, which enhances the system’s resiliency to a certain degree. While trading, no third parties will be engaged so that the transaction is efficient and fast.

The vital dependence of peer to peer (P2P) energy trading frameworks on creative Internet of Things (IoT) has been making it more vulnerable against a wide scope of attacks and performance bottlenecks like low throughput, high latency, high CPU, memory use, etc. This hence compromises the energy exchanging information to store, share, oversee, and access. Blockchain innovation as a feasible solution, works with the rule of untrusted members. To alleviate this threat and performance issues, this paper presents a Blockchain based Confidential Consortium (CoCo) P2P energy trading system that works on the trust issues among the energy exchanging networks and limits performance parameters. It reduces the duplicate validation by creating a trusted network on nodes, where participants identities are known and controlled. A Java-script-based smart contract is sent over the Microsoft CoCo system with Proof of Elapsed Time (PoET) consensus protocol. Also, a functional model is designed for the proposed framework and the performance bench-marking has been done considering about latency, throughput, transaction rate control, success and fail transaction, CPU and memory usage, network traffic. Additionally, it is shown that PoET’s performance is superior to proof of work (PoW) for multi-hosting conditions. The measured throughput and latency moving toward database speeds with more flexible, business-specific confidentiality models, network policy management through distributed governance, support for non-deterministic transactions, and reduced energy consumption.

This paper elaborates a hybrid synchronous reference frame method has been proposed for the distribution static compensator (DSTATCOM) to enhance the compensation performance. This controller is designed in such a way that it generate the reference with respect to the change in load to reject the harmonics. Furthermore, a hysteresis controller is employed for switching pattern generation. Fuzzy logic controller is also implemented in MATLAB/simulink environment here to analyze the total harmonic distortion. Experimental analysis of the DSTATCOM demonstrates the potency and reliability of proposed controller over existing control strategy in the from of total harmonic distortion.

Grid connected hybrid renewable energy sources (RES) are main challenges nowadays. Interconnecting of two or more RES is called hybrid system and battery is optional in this kind of systems where grid is in active. The normal inverters are unable to produce sinusoidal voltages and this will cause many problems in grid connected system. Hence, many topologies of multilevel inverters are proposed which can able to produce sinusoidal output voltage. However, the cost and operational complexity will increase due to increasing number of switches. In order to reduce total number of switches, an Aligned Multilevel Inverter (AMI) configuration of three phase is implemented in this paper. Wind energy-based electrical power generation system and solar energy based electrical power generation systems are considered for interconnection. Energy storage devices such as batteries are not incorporated to system since considered grid is in active mode. Maximum power point tracker (MPPT) devices are available to extract maximum power from photovoltaic arrays and wind turbines, hence a boost converter is considered as MPPT converter for wind turbine and proposed AMI also works as MPPT converter for PV by using proposed controller. Hence extra DC–DC converters are not essential for PV system for MPPT, resulting in reduction of overall system cost. Also, the modified invasive weed optimization (MIWO) based algorithm is proposed for PV system to harvest maximum energy under partial shading conditions. The proposed MIWO is compared with particle swarm optimization (PSO) and grey wolf optimization (GWO) to enhance the performance of proposed algorithm. Extensive results are validated with Hardware-in-Loop (HIL) designed on OPAL-RT platform.

The prime objective of the proposed research work is to study the frequency response of a wind plant integrated two area power system under sudden load disturbances when considered under deregulated market environment. The thermal power system has been modelled with suitable generation constraint and governor dead bands. Erratic behaviour of wind power makes the power system very sensitive to frequency deviations and proper frequency control is needed for stability. A new tilted integral derivative controller (TID) with type II fuzzy controller is considered as secondary controller for minimizing frequency fluctuations. The gains of the controller are set at an optimal value with the help of newly designed hybrid Dragonfly algorithm–Whale optimization algorithm for proper control action. System dynamic performance with and without renewable penetration is studied and robustness of the proposed controller is established under various market conditions and varying renewable power integration.

The performance evaluation of a single-phase shunt-connected custom power device (SC-CPD) for current quality improvement is discussed in this paper. The SC-CPD performance is compared based on the linear triangle-comparison pulse width modulation (TC-PWM) control, hysteresis current control (HCC), and the predictive non-linear switching control strategies. The predictive switching control is implemented using the finite control set-model predictive control (FCS-MPC). The switching control techniques’ operational and implementation features are discussed for the given control objectives of the SC-CPD for a particular nonlinear load. Basic functional case studies with sinusoidal and non-sinusoidal supply mains in the presence of non-linear loads are presented to illustrate the appropriateness of the switching techniques. The SC-CPD model and control methodologies are developed in the MATLAB/Simulink environment, including designing of various circuit components. Finally, performance simulation results using the switching techniques have been compared and validated using OPAL-RT 4510-based real-time simulations.

The islanding detection is a major problem for both AC and DC Microgrids. Failure to do so may result in problems such as system instability, increased non-detection zone, out-of-phase reclosing, personnel safety, and power quality deterioration. To address this issue, this paper presents a reliable island identification method for DC Microgrids that employs a Cumulative Sum of Rate of change of Voltage (CSROCOV) to reduce the non-recognition region. The proposed islanding protection scheme employs point of common coupling (PCC) transient signal to detect islands events. The voltage, power, and current sampling are accumulated from the PCC of the distributed generation terminals. The proposed scheme detects islanding in three test cases with varying power mismatching conditions, while non-islanding events are classified as capacitor switching and faults. The system is modelled and simulated in the MATLAB/Simulink environment, then islanding conditions are applied by turning off the main circuit breaker. Simulation results are presented to verify the methodology under different test cases. The robustness of the proposed scheme is also validated against measurement noise.

In the presence of nonlinear response created by power electronics-based compensators, reliable fault detection and classification by distance protection relays is a major concern. The unified power flow controller (UPFC) has a dynamic characteristics that causes stability and protection issues. A intrinsic time decomposition (ITD) based strategy is proposed for addressing this issue. A differential energy based detection index computed using ITD and adaptive thresholding technique is employed such that unerring fault detection is achieved wherein faulty phases of a UPFC compensated transmission line are well pointed out. Various fault and non-fault cases considering critical power system conditions are analysed for power systems with varying configurations modelled using EMTDC/PSCAD. A comparison of the current detection method to recently proposed techniques reveals the benefits and feasibility of the presented detection strategy, which has been proved to be accurate and efficient. Highlights – Unit protection of UPFC-compensated lines irrespective of compensation mode and level. – Intrinsic Time Decomposition based detection index using current signal to detect faults. – Accurate identification and discrimination of fault and non-fault events. – Adaptive threshold technique immune to power system structure. The executional burden time is near about 5 ms.

One of the main objectives of the Energy Management System (EMS) is to achieve a very high level of flexibility, stability, and the system must be able to adapt to most changes in the distribution network. This paper proposes a multi-agent system-based microgrid energy management to balance the energy supply and demand by feasibly integrating the energy storage system and demand response. An overall power management strategy is necessary to manage power flows among all interconnected elements of the microgrid. The principal contribution of this paper is an energy management system based on intelligent agents; each agent uses the microgrid data to manage the power flow in the microgrid. The interaction between agents proposed is simulated using JADE (Java Agent Development Environment) and the microgrid model is simulated using MATLAB/Simulink, both platforms are connected through the MACSimJX middleware for a dynamic simulation.

This paper purposes a new type of hybrid technique depends on lightning search algorithm (LSA) and recursive least square (RLS) named as LSA-RLS to overcome the harmonic estimation issues in time varying modern power system signals buried with noises. LSA is based on a natural phenomenon of lightning. It consists of three types of projectiles: transition, space and lead projectiles. Transition projectiles create population, space projectiles do the exploration and the lead projectiles do the work of exploitation and find the optimal solution. The basic LSA algorithm is mixed with RLS algorithm in an adaptive way to estimate the states of the harmonic signals. Simulation and validation are made with real time data obtained from a converter fed D.C motor drive. The efficacy of the proposed algorithm is verified by comparing the simulation results of recently reported algorithms such as particle swarm optimization (PSO), differential evolution (DE), bacteria foraging optimization (BFO), gravity search algorithm hybridized recursive least square method (GSA-RLS). It is verified that proposed (LSA-RLS) technique is the best in terms of computational time, convergence, accuracy.