The fast-growing awareness of depleting fossil fuel and the adverse impact of conventional energy generation methods on the environment has brought passionate attention to renewable energy sources (RE source). Owing to stochastic nature of energy production from renewable energy system (RES), two or more sources are combined to form hybrid RE system (HRES). Optimisation of size, cost and reliability of power production of HRES are important factors in the planning of HRES. This study presents a review of optimisation tools and constraints on which HRES system is optimised. The types of storage/backup system available for HRES are also presented in this study.

This study highlights an attempt of comparing the performance of several energy storage (ES) devices like battery ES, flywheel ES, capacitive ES, superconducting magnetic ES, ultra-capacitors and redox flow battery (RFB) in automatic generation control under bilateral deregulated scenario. The considered system comprises gas and thermal generations wherein a geothermal power plant (GTPP) is also incorporated. Gas and thermal systems are provided with appropriate generation rate constraints. A new fractional order (FO) cascade controller named as FO proportional-integral–FO proportional-derivative (FOPI–FOPD) is proposed as secondary controller and its performance is compared with commonly used classical controllers. A novel stochastic algorithm, sine cosine algorithm, has been used to optimise controller gains and other parameters. Analyses of dynamic responses reveal the superiority of FOPI–FOPD over others in terms of settling time, peak deviation and magnitude of oscillation. The effect due to GTPP introduction has been examined and the responses disclose that the integration of GTPP leads to better dynamics. Performances of various ES devices in the presence of FOPI–FOPD controller are also compared and dynamic responses of RFB found superior to others. For a more realistic scenario, analysis is done considering time delay and some practical plants of Nevada, USA.

This study presents a comparative study on dynamic behaviour of two different types of wind turbines (WTs) that are widely used in power systems. Mathematical modelling of two types of WTs in the multi-machine power system is presented, and a suitable framework for the study is provided. To compare the cost of provision of stability service by each of two different WTs, a technical–economical two-objective optimisation problem considering damping indices and generation cost will be formulated and solved by multi-objective gravitational search algorithm method. The presented strategy is carried out for each WT and Pareto-optimal curves are extracted. It is shown that in a system with poor dynamic situation, expensive production units are used that this phenomenon will increase generation cost. Generation costs are analysed by considering two WTs, doubly fed asynchronous generator and permanent magnet synchronous generator and dynamic condition for each type are evaluated. Two scenarios are assumed for evaluation; the first one without retuning of stabilisers and the second one with stabilisers retuned due to system generation situation. The proposed scheme is tested on modified 16-machine 5-area network and simulation results are compared.

This study proposes a novel method to optimally allocate capacity for a stand-alone microgrid system (SAMS). An SAMS is usually found on offshore islands or in the areas, where electricity cannot be delivered by utility companies. With the continuing development of renewable energy, the photovoltaic (PV) plant, wind turbine generator and battery energy storage system are integrated into an SAMS to reduce generation cost, mitigate environmental damage and increase generation efficiency. In terms of the uncertainty of renewable generation and to allow optimal capacity allocation for an SAMS, a combination of a Monte Carlo simulation, an enhanced charged system search algorithm and a Pareto-based fuzzy decision-making method is used in this study. The objectives considered are the minimisation of both the levelised cost of energy (LCOE) and the expected energy not supplied. An efficient scheme that reduces the convergence time is also developed. The proposed method is tested using an SAMS that is located on an offshore island of Taiwan. Testing results show that the proposed method produces more stable convergence, lower LCOE value, smaller PV capacity and lower power curtailment than those for the differential evolution and particle swarm optimisation methods.

Multi-functional grid-connected inverter (MFGCI) is an effective solution for smart grid application to interface renewable energy sources and provide ancillary services. In this study, the controller of an MFGCI-based distributed generator (DG) is investigated. On the basis of impedance reconfiguration, multiple coupled ancillary services of a DG are modelled to upgrade DG, including power quality conditioning, virtual synchronous generator emulation, and harmonic resonance damping. Analyses highlight potential benefits of DGs to actively participate in some possible services. From the perspective of impedance model, an upgrading solution is also proposed to coordinate these services in a DG. Using the proposed equivalent circuit model, these ancillary services can be uniformly considered as impedance control of the distribution network. Detailed models are presented to explain the principles of ancillary services. Experimental results of a test rig confirm the ancillary services of DG to enhance the power quality, provide virtual inertia, and eliminate the harmonic resonance.

This study presents an improved solar system with maximum power point tracking (MPPT). A digital signal processor is used to control the converter with the proposed control; thus, the system can implement MPPT independently for each solar panel whether it is under shading, various irradiation conditions or with faulty solar cells. A modified MPPT method is designed to reduce the power oscillation significantly, thus the power loss is reduced. With the proposed scheme, most of the solar panel available output power is delivered to the load only through a diode, reducing the converter power loss. In addition, the converter only handles part of the solar panel output power. Therefore, the system cost is reduced due to the low-power rating converter. A laboratory prototype is constructed and tested to evaluate the effectiveness of the proposed system. The proposed photovoltaic (PV) system and the PV balancer are compared through simulations and experiments under various shading conditions. The experimental results show that the proposed PV system can produce more output power with high efficiency.

The environmental and economic impact of photovoltaic (PV) systems is continuously growing, serving as an effective alternative energy source. Yet, failures and underperformance, e.g. due to soiling and deterioration, can significantly affect PV production and shrink the capacity available. This becomes an important issue, especially when the plant is not easily accessible for manual checking. Typical monitoring tools can help energy managers to deal with such issues. However, their diagnostics might be misleading as reduced performance could also be caused by low radiation and other relative factors, which are difficult to identify given the non-linear and stochastic relation of energy production and weather variables. In addition, accurate component-based models that use local weather measurements as inputs are not always applicable. In this regard, a methodological approach for tracking the performance of PV systems is proposed, which uses an artificial neural network, trained using reported system data and irradiation predictions. Possible abnormalities are identified through the model and alerts are generated to proceed with maintenance actions. The approach is implemented into a decision support system for smart cities, demonstrating encouraging results.

This study presents a detailed performance analysis of multi-phase (six-phase) induction generator in conjunction with different types of wind energy conversion systems (WECS). It targets to emphasise the advantages of considering an asymmetrical six-phase induction generator (ASIG) in stand-alone, grid-connected fixed speed and grid-connected variable speed operation. Various aspects such as efficiency, reliability and productivity are considered while performing the analysis. In stand-alone mode, reliability and efficiency of the self-excited ASIG are ascertained by disconnecting one of the two three-phase sets connected to a resistive load. In grid-connected fixed speed mode, two different scenarios are implemented to pursue the applicability of ASIG. In the first scenario, only one three-phase winding set is connected to the grid and another set is connected to a local resistive load. In the second scenario, both three-phase windings are connected to the grid via Y−/Y three-winding transformer. Variable speed operation in grid-connected mode is accomplished by employing back-to-back pulse-width modulation converters between the generator and grid. In this configuration, ASIG is operated with indirect field oriented control to obtain maximum aerodynamic efficiency. Transmission of active and reactive power is monitored with vector-oriented control. Experimental results of considered scenarios are presented to verify the viability of ASIG in various configurations of WECS.

This study presents a novel application of a hybrid adaptive neuro-fuzzy inference system (ANFIS)-genetic algorithm (GA)-based control scheme to enhance the performance of a variable-speed wind energy conversion system. The variable-speed wind turbine drives a permanent-magnet synchronous generator, which is connected to the power grid through a frequency converter. A cascaded ANFIS-GA controller is introduced to control both of the generator-side converter and the grid-side inverter. ANFIS is a non-linear, adaptive, and robustness controller, which integrates the merits of the artificial neural network and the FIS. A GA-based learning design procedure is proposed to identify the ANFIS parameters. Detailed modelling of the system under investigation and its control strategies are demonstrated. For achieving realistic responses, real wind speed data extracted from Zaafarana wind farm, Egypt, are considered in the analyses. The effectiveness of the ANFIS-GA controller is compared with that obtained using optimised proportional–integral controllers by the novel grey wolf optimiser algorithm taking into consideration severe grid disturbances. The validity of the ANFIS-GA control scheme is verified by the extensive simulation analyses, which are performed using MATLAB/Simulink environment. With the ANFIS-GA controller, the dynamic and transient stability of grid-connected wind generator systems can be further enhanced.

Sub-synchronous oscillation (SSO) caused by direct-drive permanent magnet synchronous generators (PMSGs) occurs frequently in Xinjiang Uygur Autonomous Region, China. As a new type of SSO, the mechanism of power oscillation triggered by PMSGs has not been clarified yet. In this study, a small-signal analysis method was used to investigate the response process of the grid-side converter (GSC) controller and a phase-locked loop (PLL) to harmonics. Components with the same frequency of input disturbance signal and an output signal which generated by response process of controller superpose at the outlet of PMSGs could be amplified by positive feedback. Amplified harmonics will cause sustained power oscillation in sub-synchronous frequency. A criterion for judging dangerous frequencies of SSO was deduced based on phase relation between input and output signals, and the form of output signal was predicted under the condition of certain parameters setting. The theoretical analysis is then validated by the simulation results and the on-site data measured by the phasor measurement unit. Furthermore, the impacts of GSC and PLL parameters on SSO were discussed. This study provides the theoretical basis for SSO mechanism and judgement method in practical engineering.

This study presents a new approach in application of distance relay in distribution system. During the heavy load conditions, the load encroachment of impedance into the distance relay protection zones is a well-known reason for distance relay mal-operation. Therefore, all the modern digital distance relays are equipped with the load encroachment scheme. This study proposes the idea of using the load encroachment scheme of distance relay for monitoring purpose in the presence of renewable energy resources (RES) integration. Furthermore, it will be presented that based on the defined monitoring zones some alarms can be defined. The OpenDSS and Matlab software are used to test the effectiveness of the method with the IEEE 8500 node test feeder. The proposed method is tested with the unbalanced distribution system feeder loading and distributed model of solar generations. The dynamic performance of the proposed method is studied for on-line power factor monitoring of the feeder with the sun irradiation dynamic. The results show the necessity of power factor monitoring in the distribution system with RES integration. In addition, the simplicity of the proposed method allows its easy application in the digital distance relay.

New telecommunication towers are installed in remote/rural areas to facilitate the increasing connectivity worldwide. With concerns over environmental issues, such towers are to be environmentally friendly. Conventionally, diesel generator supply power to towers in remote/rural areas, which leads to carbon emission. Also, the operation of diesel generator entails considerable operating cost (fuel and maintenance costs). Thus, a wind-photovoltaic (PV) based DC microgrid is proposed for supplying power to telecommunication towers in remote/rural areas ensuring reliable, economical, and green power supply. Therefore, techno-economic analysis is carried out here to determine the feasibility and cost of electricity (COE) per unit of the proposed DC microgrid. A non-dominated sorting genetic algorithm II is implemented to solve the multi-objective optimal sizing problem to achieve a trade-off between the cost and the reliability. Hourly solar irradiation and wind speed data is used for long-term analysis equivalent to the lifespan of the battery. Further, de-rating factor and maximum power point tracking factor are considered while modelling the renewable resources. The loss of power supply probability, excess energy, and COE are calculated and different scenarios are studied to examine the techno-economic feasibility of the proposed DC microgrid.

Here, the authors present a theoretical and experimental study for the hybrid solar collector system photovoltaic thermal (PVT) compared to the conventional thermal collector CTH and the photovoltaic panel PV using a mathematical model that is developed in order to predict the performance of the system. The model is based on the equations of the energy balances of each system to see these thermal and electrical performances. The system studied consists of a PV panel welded above the outside face of a thermal system in order to cool the PV cells and increase their electrical efficiency. The results of the experimental study were compared with the theoretical data and the model was validated.

The following article published in IET Renewable Power Generation, Kerdphol, Thongchart; Rahman, Fathin Saifur; Mitani, Yasunori; Watanabe, Masayuki; Hongesombut, Komsan; 'Robust virtual inertia control to support frequency stability of an islanded microgrid', IET Renewable Power Generation, 2017, DOI: 10.1049/iet-rpg.2017.0510 on 7 December 2017 has been retracted due to a breach of the IET’s Policy in Relation to Plagiarism, Infringement of Copyright and Infringement of Moral Rights and Submission to Multiple Publications.