This study investigates the application of the sliding mode controller (SMC) for induction motor drive variable-displacement pressure-compensated pump (VDPC) system powered by an isolated wind/storage unit. The variable-speed wind turbine (WT) is proposed to drive a permanent magnet synchronous generator (PMSG) which, feeds a storing energy unit and stand-alone dynamic load. Energy storage systems are required for power balance quality in isolated wind power systems. Initially, the holistic model of the entire system is achieved, including the PMSG, the uncontrolled rectifier, the buck converter, the storage system, induction machine and the VDPC pump. The power absorbed by the connected loads can be effectively delivered and supplied by the proposed WT and energy storage systems, subject to sliding mode control. The main purposes are to supply 220 V/50 Hz through a three-phase inverter and adjust the IM speed and VDPC pump flow rate. The performance of the proposed system is compared with the neural network control and the conventional PID control. The simulation results show that the proposed system with the SMC and neural network controllers has good performance and good prediction of the electrical parameter waveforms compared with the case of the conventional PID controller.

Wind energy has been part of the fastest growing renewable energy sources and is clean and pollution-free. Wind energy has been gaining increasing global attention, and wind speed forecasting plays a vital role in the wind energy field. However, such forecasting has been demonstrated to be a challenging task due to the effect of various meteorological factors. This study proposes a hybrid forecasting model that can effectively provide preprocessing for the original data and improve forecasting accuracy. The developed model applies a genetic algorithm-adaptive particle swarm optimisation algorithm to optimise the parameters of the wavelet neural network (WNN) model. The proposed hybrid method is subsequently examined in regard to the wind farms of eastern China. The forecasting performance demonstrates that the developed model is better than some traditional models (for example, back propagation, WNN, fuzzy neural network, and support vector machine), and its applicability is further verified by the paired-sample T tests.

The number of installed photovoltaic (PV) systems has been increasing in an unprecedented rate every year throughout the world. In some situations, the PV systems can provide more power than the demand in certain parts of a network and cause reverse power flow, which the traditional distribution networks are not designed for. Consequently, these instances may result in adverse interactions between PV systems and voltage regulation devices such as step voltage regulators (SVRs). This can potentially drive voltage magnitudes beyond acceptable limits and possibly damage consumers’ appliances. In the literature, such interaction cases with consideration of realistic three-phase four-wire unbalanced networks have not yet been reported. Therefore, this study analyses the interaction between SVR and PV systems in a real-world network by utilising the quasi-static time-series technique for a long-term statistical assessment. This evaluation focuses on examining voltage regulation issues in an unbalanced three-phase four-wire network along with an open-delta SVR configuration, and the corresponding solution is proposed to resolve the concerning issues. The results of this study will provide valuable information on interaction characteristics to academia and utilities for assessing large-scale PV system integration.

The increasing installation of photovoltaic panels in low-voltage grids causes an over voltage problem, especially during high production and low consumption periods. Generally the over voltage problem is overcome by implementing reactive power control methods. The advances in networked control systems theory and practice create new scenarios where reactive power control methods can offer additional features and benefits. To explore these new capabilities, this study presents two new reactive power control methods that exploit the networked approach. These two methods are evaluated in a comparative reference framework that also includes the base-line case where no reactive control method is applied, the conventional droop method approach, and a solution based on a near-optimal location of a high power STATCOM derived from one of the new proposed networked methods. The main merit factors used to compare the control methods are the maximum voltage across the distribution grid, the power factor in the point of common coupling, and the total power losses and economic cost of the installation. With these merit factors, the advantages and limitations of the new and existing control methods are revealed and discussed. A useful discussion for selecting the best control solution is also reported.

The reduction in power depends on module interconnection scheme and shading pattern. Different interconnection schemes are used to reduce the losses caused by partial shading. This study presents a minimum-distance-average-based clustering algorithm for the photovoltaic (PV) arrays that can improve the PV power under different shading conditions. The PV array is configured based on a novel clustering algorithm in wireless sensor networks based on sensor node deployment location coordinates. Various cases such as short narrow, short wide, long narrow and long wide have been analysed and their performances were discussed. The proposed method facilitates maximum power extraction by distributing the effect of shading over the entire array thereby reducing the mismatch losses caused by partial shading conditions. The performance of the system is investigated for different shading conditions. Also Monte Carlo estimator was used to improve the impact of the investigation by varying solar irradiance values and the results are presented to show the successful working of the proposed scheme.

During the last few years, greenhouse gas emission especially from electric power generation is a major concern due to the global warming and environmental change, therefore, committing the generating units on minimum cost criterion is shifting toward minimising the cost with minimum emission. Due to the conflicting nature of economic and emission objectives, the generation scheduling becomes a multi-objective problem. In this study, a weighted sum method is applied to convert multi-objective problem to a single-objective problem by linear combination of different objectives as a weighted sum and an efficient hybrid algorithm is presented for aiding unit commitment (UC) decisions in such environments. Due to uncertainty of wind power generation, the UC problem has become complex. To handle uncertainty, scenario generation and reduction techniques are used. The proposed hybrid approach is a combination of weighted improved crazy particle swarm optimisation with pseudo code algorithm, which is enhanced by extended priority list to handle the spinning reserve constraints and a heuristic search algorithm to handle minimum up/down time constraints. Simulation results confirm the potential and effectiveness of proposed approach after comparison with other methods reported in the literature.

Increased penetration level of the wind power generation has brought new issues and challenges of power quality. One of these issues is low-voltage ride through (LVRT). This study proposes an LVRT scheme for the permanent magnet synchronous generator (PMSG) variable speed wind turbine at grid faults. The machine side converter controller is used to control the dc-link voltage using interval type-2 fuzzy logic control taking into account the non-linear relationship between the generator speed and the dc-link voltage. Under grid faults, there is a power mismatch between the generated active power and the active power delivered to the grid. This excess power is stored in the generator inertia to keep the dc-link voltage constant. To validate the proposed control strategy, simulation results for 1.5 MW PMSG-based wind energy conversion system are carried out by MATLAB-Simulink under symmetrical and asymmetrical faults.

Within the Lysekil wave energy research project at the Swedish west coast, more than ten Wave Energy Converters (WECs) prototypes have been developed and installed in an ocean based test site. Since 2006 various experiments have been conducted and the generated electricity was delivered to shore at a nearby island. While experiments are essential for the development of wave energy converters, theoretical studies and simulations are an important complement – not only in the search for advanced designs with higher efficiency, but also for improving the economic viability of the studied concepts. In this paper a WEC model is presented. The model consists of three subsystems: i) the hydrodynamic source, ii) the linear generator model, and iii) the electrical conversion system. After the validation with the experimental results at the research site, the generator model is connected to three passive load strategies – linear resistive load, passive rectification and resonance circuit. The paper focuses on analysing the operation of the model coupled with three load cases. The results prove that the WEC model correctly simulates the linear generator developed in the Lysekil Project. Moreover, the comparison among different load cases is made and discussed. The results gives an indication of the efficiency of energy production as well as the force ripples and resulting mechanical loads on the wave energy converters.

Wastewater treatment plants are distinguished by considerable electricity consumption; on the other hand, organic contents of sewage allow for local energy recovery from, e.g. anaerobic digestion of sludge and subsequent use of resulting biogas in a combined heat and power unit. Supplementary incineration of dehydrated sludge in a local boiler feeding a steam turbine/generator set can provide another quantity of electricity and, at the same time, exonerates from further treatment/deposition of infectious sludge. Waste heat from both steam circuit and combustion engine can contribute to sludge drying, thus significantly increasing its heating value. Furthermore, large expanse and usual location remote of residential areas make sewage plants eligible for harvesting renewable energy. As innovative approach this study exposes that – even if all techniques considered for energy harvest in particular are state-of-the-art – under proper combination/design and intelligent operation of devices and processes, sewage plants can be widely brought towards independence of external energy supply under reasonable economic conditions.

When compared with conventional point-to-point high-voltage direct current (HVDC) systems, multiterminal HVDC (MTDC) systems are more economical and flexible. MTDC systems can tie distributed high power renewable energy sources (such as offshore wind energy and high-power photovoltaic systems) into AC grid(s). To save in the required infrastructure for DC line installations, existing high-voltage alternating current (HVAC) lines can be converted into DC links. The bipole HVDC concept can be used easily for converting the HVAC lines into DC links, but with a limited transmission capacity. Alternatively, three-wire bipole structure (TWBS) can be used, yet it requires a power electronics-based converter connected in series with one of the wires (modulating wire), which affects the system reliability and adds more complexity. In this study, a new configuration is proposed for converting the HVAC lines into DC links with enhanced power capability compared with the two-wire bipole HVDC system. The proposed approach provides a lower power enhancement compared with that provided by TWBS. However, a higher reliability can be guaranteed as it avoids the series-connected converters. Analytical and simulation studies using Matlab/Simulink platform have been presented in this study to validate the proposed concept.

This study quantifies the increase in the peak power demand, net of non-dispatchable generation, that may be required by widespread adoption of heat pumps. Electrification of heating could reduce emissions but also cause a challenging increase in peak power demand. This study expands on previous studies by quantifying the increase in greater detail; considering a wider range of scenarios, the characteristics of heat pumps and the interaction between wind generation and demand side management (DSM). A model was developed with dynamic simulations of individual heat pumps and dwellings. The increase in peak net-demand is highly sensitive to assumptions regarding the heat pumps, their installation, building fabric and the characteristics of the grid. If 80% of dwellings in the UK use heat pumps, peak net-demand could increase by around 100% (54 GW) but this increase could be mitigated to 30% (16 GW) by favourable conditions. DSM could reduce this increase to 20%, or 15% if used with extensive thermal storage. If 60% of dwellings use heat pumps, the increase in peak net-demand could be as low as 5.5 GW. High-performance heat pumps, appropriate installation and better insulated dwellings could make the increase in peak net-demand due to the electrification of heating more manageable.

Fuel cells (FCs) are considered as one of the most promising sources of electrical energy that can meet environmental constraints. One of the important steps to ensure clean energy is seamless power transfer from the FC to the grid. In this study, the behaviour of the FC under AC load and grid connection of FC system is simulated. Required interface for FCs' grid connection is performed with PSCAD software. For this purpose, polymer electrolyte membrane (PEM) FC model is developed in PSCAD software. Power converter units are designed to supply DC and AC loads. Control structures are developed for DC–DC converter and DC–AC inverter models in PSCAD. Power conditioning units are separately controlled by proportional–integral controller. The electrical behaviour and control of FCs are investigated and simulated using PSCAD software. Then a developed PEM FC system model is tested for AC load conditions. The PEM FC system is connected to grid and the behaviours of grid connected FC system are examined.

Maximising the power production of offshore wind farms using proper control strategy has become an important issue for wind farm operators. However, the power transmitted to the onshore substation is not only related to the power production of each wind turbine but also the power losses which are related to electrical system topology. This study proposed an optimised power dispatch strategy for minimising the levelised production cost of a wind farm. Particle swarm optimisation (PSO) is employed to obtain final solution for the optimisation problem. Both regular shape and irregular shape wind farm are chosen for the case study. The proposed dispatch strategy is compared with two other control strategies. The simulation results show the effectiveness of the proposed strategy.

This study deals with the overvoltage problems caused by the increased photovoltaic (PV) penetration in typical rural radial distribution systems, where small PV systems and household consumers are connected. For this study, the authors used an iterative algorithm to solve the power flow problem in radial grids and considered three methods for the correction of unacceptable overvoltages, which are based on different principles. The system under consideration is an almost symmetrical three phase, low-voltage radial network, consisting of nine PV and consumer connection points. The system was simulated for a whole year with a sample time of 15 min, taking into account the variations of the solar radiation and loads. The results verified that the control of reactive power on the line can successfully manage overvoltage issues. The additional demand of reactive power and consequent line losses are used to evaluate various correction methods.

The rapid growth rate of wind energy coupled with the increasing sizes of individual wind turbines strengthens the need for optimised wind energy capture. This study utilises the unknown input observer to track the variation of the maximal value of wind turbines’ power coefficient to tune the control law. The proposed observer identifies variations in the power coefficient surface over time due to the effect of the environment on the rotor blades. Simulations for both open- and closed-loop operations are shown. The proposed technique shows the potential to alleviate the performance degradation during the lifetime of wind turbines operating in hostile environments.