Frequency regulation of a RES integrated power system with AC/DC parallel link employing a fuzzy tuned fractional order controller

This paper demonstrates the operational efficacy of a newly proposed fuzzy tuned fractional order controller to offer an improved frequency regulation of a multi area renewable energy source (RES) integrated nonlinear power system. The effect of governor dead band nonlinearity and generation rate constraint of hydro and thermal power plants are considered in the system. Moreover, a proposed appropriate High voltage direct current (HVDC) tie line model is incorporated in this work, to verify the frequency deviation. Different test cases are applied to verify the robustness of the controllers on frequency response. The superiority of the proposed controller upon Proportional integral and derivative (PID), fuzzy logic controller and fuzzy PID controller in minimizing frequency deviation has been verified through MATLAB SIMULINK environment.

Moisture effects on AC dielectric strength and partial discharge inception voltage in natural monoesters

It is essential to analyse the dielectric performance in a humid environment of insulating liquids of plant origin, considered as alternatives to mineral oil (MO) which is not environmentally friendly. This paper focuses on the effects of different moisture levels on the dielectric strength and partial discharge initiation voltage of two natural monoesters, based on castor oil (CO) and palm kernel oil (PKO), and MO. The different samples were moistened with a glycerol solution, then sealed and stored for 12 days to allow further diffusion of moisture into the samples. Dielectric strength was statistically evaluated from IEC 60156. Partial discharge inception voltage (PDIV) experiment was performed in conformity with a modified IEC 61294 purpose at ambient temperature. Based on the experimental observations, the moisture has different behavior on dielectric strength and PDIV of insulating oils. Monoesters have a better withstand to water contamination than MOs in power transformers.

A reliable islanding identification mechanism for DC microgrid using PCC transient signal

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.

Intrinsic time decomposition based differential protection with adaptive threshold for UPFC compensated transmission line

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.

Accurate estimation of modern power system harmonics using a novel LSA hybridized recursive least square technique

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.

Advanced energy management and frequency control of distributed microgrid using multi-agent systems

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.

Power quality improvement using model predictive control based shunt connected custom power device in a single phase system

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.

Frequency regulation of wind energy integrated power system using a novel optimized type II fuzzy tilted integral derivative controller

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.

Experimental verification of DSTATCOM for various non-linear load

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.

A novel Confidential Consortium Blockchain framework for peer to peer energy trading

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.