Wind Diesel Research Articles

Enhancing Frequency Regulation Support through Several Synthetic Inertial Approaches for WDPS

The aim of this paper is to propose an enhancement to the primary frequency control (PFC) of the San Cristobal Island hybrid wind–diesel power system (WDPS). Naturally, variable speed wind turbines (VSWT) provide negligible inertia. Therefore, various control strategies, i.e., modified synthetic inertial control, droop control and traditional inertial control, if introduced into VSWT, enable them to release hidden inertia. Based on these strategies, a WDPS has been simulated under seven different control strategies, to evaluate the power system performance for frequency regulation (FR). Furthermore, the student psychology-based algorithm (SBPA) methodology is used to optimize the WDPS control. The results show that modified synthetic inertial control is the most suitable approach to provide FR. However, further exhaustive research validates that droop control is a better alternative than modified synthetic inertial control due to the negligible system performance differences. In addition, droop control does not require a frequency derivative function in the control system. Therefore, the hybrid system is more robust. Moreover, it reduces the steady state error, which makes the power system more stable. In addition, a pitch compensation control is introduced in blade pitch angle control (BPAC) to enhance the pitch angle smoothness and to help the power system to return to normal after perturbations. Moreover, to justify the performance of hybrid WDPS, it is tested under certain real-world contingency events, i.e., loss of a wind generator, increased wind speed, fluctuating wind speed, and simultaneously fluctuating load demand and wind speed. The simulation results validate the proposed WDPS control strategy performance.

Optimizing separate and combined grids for cost-effective hybrid renewable energy electrification in Mogadishu, Somalia

Expanding access to affordable, reliable, and sustainable electricity is an urgent priority in Somalia, which suffers from high energy costs and climate vulnerability despite negligible emissions. Therefore, this study employs MATLAB simulation software and three algorithms—particle swarm optimization (PSO), genetic algorithm, and simulated annealing—to determine optimal separate and combined grid designs for a hybrid renewable energy system in Mogadishu, Somalia. Four system configurations are assessed, namely, utilities—diesel-alone, Photovoltaic (PV)–diesel hybrid, wind–diesel hybrid, and PV–wind–diesel hybrid across the grids of three utilities—Benadir Electric Company, Mogadishu Power Supply, and Blue-Sky Energy. The algorithms evaluate technical feasibility, economic viability, and system reliability to identify the most suitable configurations. Forty-eight systems are analyzed. The combined PV/wind/diesel grid optimized with PSO is most effective, reducing the net present cost by 32%–47% and levelized cost of electricity by 41%–60% compared to diesel-only systems while maintaining reliability. Greenhouse gas emissions decrease by 38%–59% with the hybrid system.

Dynamic performance improvement of an isolated wind-diesel system with intelligently controlled supercapacitor energy storage system

This paper aims to develop a supervisory control scheme to enhance the effectiveness and profitability of a small-rating super capacitor energy storage system (SCESS) used in load-frequency-control applications. The proposed approach, which uses one-step-ahead adaptive predictive control (APC), adeptly handles the operational limitations of the SCESS. For the purpose of online estimation of system parameters, the recursive least square (RLS) algorithm has been employed. The system can be characterized as a two input two output system, wherein the real and reactive powers required by the SCESS serve as control signals issued by the controller. The SCESS voltage is subject to constraints to limit energy trade within specific bounds. The proposed control scheme successfully maintains the voltage constraints of the SCESS while significantly reducing frequency and voltage deviations in the presence of two disturbances, viz; load disturbance and wind disturbance. The effectiveness of the proposed scheme is demonstrated through simulation experiments on an isolated hybrid wind diesel power system, which addresses several modeling and design aspects.

Synthesis of State/Output Feedback Event-Triggered Controllers for Load Frequency Regulation in Hybrid Wind–Diesel Power Systems

Hybrid power systems based on renewable energy sources and diesel generators are efficient solutions for supplying electricity to remote and off-grid locations. One of the most crucial problems in hybrid power systems is frequency regulation, which is established by balancing the supplied power with the load demand using the load frequency control approach. Since most feedback signals are analog and the control setups are digital, the resulting control system is a sampled-data system, which requires careful designs for both the control law and the sampling frequency to guarantee closed-loop stability. This paper is concerned with the state-feedback load frequency regulation for hybrid wind–diesel power systems under event-triggered implementation. It is assumed that the full state measurement is available for feedback and that sensors and controllers communicate over a shared digital network. To mitigate the communication load on the network, an event-triggering mechanism is constructed by emulation, based on the time-regularization principle in the sense that each consecutive triggering instant is speared by a specified minimum dwell time. The closed-loop system is described as a hybrid dynamical system to account for mixed dynamical behaviors naturally arising in networked control systems. By means of appropriate Lyapunov functions, the closed-loop stability is ensured under the proposed triggering rule. Moreover, the enforced dwell time between transmissions ensures that the accumulation of sampling times is prevented, which is crucial for the event-triggering condition to be implementable in practice. The required conditions to apply this technique are derived in terms of a linear matrix inequality. Numerical simulations on an isolated hybrid power system were implemented to demonstrate the efficiency of the proposed method. Comparative simulations with relevant techniques in the literature were carried out, which showed that the proposed approach can produce fewer transmission numbers over the network.

Diesel Governor Tuning for Isolated Hybrid Power Systems

In recent decades, renewable energy sources, such as wind power, have extraordinarily increased their participation in the energy mix throughout the world. This progression has played an important role in lowering the usage of fossil fuels. In addition, it has reduced environmental hazards and increased the emergence of hybrid power systems, mainly in remote areas. In some of these areas, diesel power plants were the only previous source of energy. Irrespective of the benefits, hybrid power systems might face problems such as frequency deviations. To contribute to reducing these problems, this paper presents a methodology to tune diesel engine governors using the Student Psychology-Based Algorithm. This proposed methodology enhances some metrics of controller performance, such as the integral square error, integral absolute error, and number of sign changes in the frequency derivative. This approach has been tested against different perturbations (step, ramp and random). To validate the effectiveness of the proposed approach, it has been simulated in relation to the San Cristobal Island (Ecuador) hybrid wind–diesel power system. The simulation results show that the governor tuned with the proposed approach provides a better system response.

Techno‐economic analysis of PV–wind–diesel–battery hybrid power systems for industrial towns under different climates in Spain

AbstractThis study aimed to provide a techno‐economic analysis of hybrid energy systems, including wind turbines, photovoltaic systems (PV) panels, diesel generators, and batteries, for selected cities in five different climate zones in Spain to meet the load requirements of industrial towns. Homer software was used to determine the most efficient configuration for supplying the average load of the industrial sector, with a value of 1500 kWh/day and a peak load of 114.58 kW, and the residential sector, with a value of 150 kWh/day and a peak load of 27.85 kW. Optimization is carried out to minimize the evaluation parameters of net present cost (NPC) and cost of energy (COE). According to the software outputs, it appears that the system utilizes a variety of renewable energies. The priority is to use all hybrid system components, and the wind–PV–diesel–battery configuration has performed best in all cities. The cities of A Coruña, Bilbao, Ponferrada, Almería, Barcelona, Salamanca, Seville, Zaragoza, and Madrid, respectively, with NPC values of 1.39, 1.67, 1.76, 1.92, 2.23, 2.29, 2.39, 2.55, 2.61 M$ and COE values of 0.199, 0.24, 0.252, 0.276, 0.32, 0.329, 0.343, 0.366, 0.374 $/kWh have economic efficiency from the highest to the lowest. Reducing pollution production is one of the key reasons for approaching hybrid technologies. In this regard, A Coruña has the lowest carbon emissions among the selected cities, with 25,190, and 95.5% of its energy production is renewable. On the other hand, Madrid, which uses 89% renewable energy, has the highest carbon dioxide production with a value of 59,242. The system analysis in different cities of Spain provides insight into the conditions necessary for establishing such systems in different climate zones, which can serve as a road map for other places in the country.

Super-twisting sliding mode control of a static synchronous compensator: An application in a wind–diesel hybrid system

The dynamic nature of load and wind power could lead to reactive power imbalance, and hence the voltage deviations in a wind–diesel power system. These deviations, if not controlled, may drive the system to operate in an unstable manner. Therefore, in this paper, a static synchronous compensator (STATCOM) is interconnected to the system to achieve reactive power balancing and minimize voltage deviations. To improve the dynamic performance of STATCOM and achieve the effective operation of the system, an optimized sliding mode controller (SMC) is designed. With the help of the design of a first-order switching manifold, an SMC is designed, which generates a control law to control the converter firing angle, and hence the reactive power output of the STATCOM. To eliminate the chattering drawback of SMC and improve the convergence characteristics, a second-order super-twisting sliding mode controller (STSMC) is proposed. The asymptotic stability of the proposed controller is guaranteed through the Lyapunov stability analysis. Particle swarm optimization (PSO) is employed to fine-tune controller parameters and achieve optimal performance. Validation of the improved performance of the system through this proposed scheme has been carried out in the MATLAB/Simulink environment and presented in the simulation studies.

Techno-economic analysis of ground source heat pump powered by hybrid photovoltaic–wind–diesel systems in a temperate climate region

Techno-economic analysis of ground source heat pump powered by hybrid photovoltaic–wind–diesel systems in a temperate climate region

Modeling and performance assessment of an isolated wind-diesel system with flywheel energy storage system

This paper proposes incorporation of a flywheel energy storage system (FESS) into hybrid wind-diesel power plant for system frequency and voltage response improvement. The impact of hybrid wind-diesel energy storage systems under various forms of disturbances, such as load disturbance, wind disturbance, wind park disconnection, and step variations in wind is presented and analyzed. The standard IEEE models for different components of hybrid wind diesel power system are considered. Simulations in the time domain are carried out in order to test the performance of proposed system. The positive impact of FESS used in wind-diesel hybrid power system is demonstrated through a series of simulation cases carried for various types of disturbances.

Techno-Economic and Environmental Analysis of Renewable Mix Hybrid Energy System for Sustainable Electrification of Al-Dhafrat Rural Area in Oman

Affordable and clean energy for any rural community is crucial for the sustainable development of the community and the nation at large. The utilization of diesel-based power generation is one of the barriers to the sustainable development of these communities. Such generations require fuel that has a volatile market price and emits massive greenhouse gas emissions. This paper presents the design, modeling, and simulation of a hybrid power system for a rural area in the Sultanate of Oman that aims to reduce daily consumption of diesel fuel and greenhouse gas emissions. Hybrid Optimization of Multiple Energy Resources (HOMER) is utilized to model multiple energy mix hybrid systems and to propose the best optimal energy mix system for a selected community. In addition, Electrical Transient Analyzer Program (ETAP) software is employed to assess hybrid system operational performances, such as bus voltage profiles and active and reactive power losses. This study revealed that the PV–wind–diesel system is the optimal energy mix hybrid microgrid for the Al-Dhafrat rural area in Oman, with a net present cost of USD 14.09 million. Compared to the currently operating diesel-based system, the deployment of this microgrid can reduce the levelized cost of energy, diesel fuel consumption, and greenhouse gas emissions per year by 54.56%, 70.44%, and 70.40%, respectively. This study confirms that the Sultanate of Oman has a substantial opportunity to install a hybrid microgrid system for rural diesel-based communities to achieve sustainable development in the country.

Review of Efficiency Improvement Technologies of Wind Diesel Hybrid Systems for Decreasing Fuel Consumption

The article contains current information on the development of energy-efficient technologies of wind–diesel hybrid systems (WDHS) for decreasing organic fuel consumption. As a result of the review, three research directions are identified: WDHS design optimization, the main equipment and control system improvements. A comparison of their effectiveness is presented. The methods of selecting WDHS configuration, equipment capacities and location, the optimization algorithms and objective functions used are described and WDHS project feasibility calculation results are presented. The methods to improve energy efficiency of WDHS major units’ (diesel generator (DG) and wind turbine (WT)) are considered. The methods to decrease diesel fuel consumption using special devices and energy storage system are presented. Special attention is paid to WDHS operating modes’ control methods and strategies, as well as to algorithms providing the efficient system operation. As a result, recommendations for the design of both isolated and on-grid WDHS are formulated.

Complete Transitions of Hybrid Wind-Diesel Systems with Clutch and Flywheel-Based Energy Storage

A Wind Diesel Hybrid System (WDHS) is an isolated power system that combines Diesel Generators (DGs) and Wind Turbines (WTGs). The WDHS has three operation modes: Diesel Only (DO), Wind Diesel (WD) and Wind Only (WO). The latter mode is the only one resulting in substantial savings, as the DG consumes fuel even with no load. Moreover, adding an energy storage system (ESS) can significantly reduce the start/stop cycles in the DG. The FESS is robust, immune to deep discharges and its state of charge (SOC) is simple to monitor. The WDHS considered in this article uses a friction clutch to disengage the diesel engine (DE) from the synchronous generator (SG) in WO mode. The AVR regulates the voltage amplitude and the frequency regulation results from balancing the power produced by the DG and WT with the power consumed by the load and dump load along with the FESS utilisation. The control algorithms of the different elements present in the WHDS are explained, as well as the general control. The FESS always has priority over the DL for the maximum harnessing of the wind power. Simulations assess the proposed solutions for the different operation modes in the WDHS.

Adaptive fractional-order sliding-mode disturbance observer-based robust theoretical frequency controller applied to hybrid wind–diesel power system

This work presents design and theoretical analysis of an adaptive fractional-order sliding-mode disturbance observer (FO-SM-DOB)-aided fractional-order robust controller for frequency regulation of a hybrid wind–diesel based power system, considering endogenous/exogenous system disturbances. Adaptive FO-SM-DOB is designed to estimate unknown/uncertain lumped system disturbances, including parametric uncertainty and exogenous disturbances. Afterwards, an improved fractional-order sliding mode controller (FOSMC) augmented with the estimated output of FO-SM-DOB is designed and applied to accelerate system dynamics with minimum chattering in the control effort. The Mittag-Leffler stability theorem affirms the finite-time convergence of disturbance estimation error. Moreover, the closed-loop asymptotic stability of the overall control system has been guaranteed by applying Lyapunov argument. The effectiveness of the suggested resilient fractional-order nonlinear frequency controller is theoretically validated by performing an extensive comparative study with SMC, FOSMC (without DOB), state observer-based SMC (SOB-SMC), second-order SMC (without DOB), and conventional integer/fractional-order controllers. Simulation results establish the supremacy of the proposed resilient fractional-order nonlinear frequency controller over its other counterparts concerning fast disturbance rejection, weaker chattering, and a high degree of robustness against unknown lumped system disturbances. Further, to demonstrate the practicability and validate the effectiveness of the proposed control strategy, magnetic levitation system and IEEE 39-bus New England power system are considered and successfully tested on MATLAB platform.

Adaptive Neuro Sliding Mode Control of Superconducting Magnetic Energy Storage System

ABSTRACT In this paper, an adaptive RBF neural network-based sliding mode controller is developed for superconducting magnetic energy storage (SMES) installed in a wind–diesel power system. Due to sudden load and wind power variations in a wind–diesel power system, power imbalances may force the system frequency to deviate from its nominal value and drive the system to operate in an unstable mode. Therefore, in a wind–diesel power system using a converter interface, a fast-acting and high power density SMES device is interconnected to carry the required power exchange whenever power imbalances occur. Based on switching manifold design, a sliding mode controller is developed to control the charging and discharging operations of SMES coil as per the power requirements, and the same is achieved by controlling the converter. A neural network using a radial basis function (RBF) is developed to estimate the unknown function of the system. Lyapunov stability analysis is conducted to guarantee the asymptotic stability of the system. MATLAB simulations are carried out and are presented to show the improved performance with the system exposed to disturbances in load and wind power.

Decentralized Model-Predictive Control of a Coupled Wind Turbine and Diesel Engine Generator System

It is highly critical that renewable energy-based power generation units provide continuous and high-quality electricity. This requirement is even more pronounced in standalone wind–diesel systems where the wind power is not always constant or available. Moreover, it is desired that the extracted power be maximized in such a way that less fuel is consumed from the diesel engine. This paper proposes a novel method to design decentralized model-predictive controllers to control the frequency and power of a single standalone generation system, which consists of a wind turbine subsystem mechanically coupled with a diesel engine generator subsystem. Two decentralized model-predictive controllers are designed to regulate the frequency and active power, while the mechanical coupling between the two subsystems is considered, and no communication links exist between the two controllers. Simulation results show that the proposed decentralized controllers outperform the benchmark decentralized linear-quadratic Gaussian (LQG) controllers in terms of eliminating the disturbances from the wind and load power changes. Furthermore, it is demonstrated that the proposed control strategy has an acceptable robust performance against the concurrent variations in all parameters of the system as compared to the LQG controllers.

Wind Diesel Hybrid System with Pitch Angle Controller

A wind diesel hybrid system is an autonomous electricity generating system using wind turbines with diesel generators to obtain a maximum contribution by the intermittent wind resource to the total power produced, while providing continuous high quality electric power. The main goal is to control load frequency and reduce fuel consumption enabling reduced system operating costs and environmental impacts. Frequency control in a power system is done to maintain an adequate balance between the consumed and generated active powers, so that the frequency remains within acceptable limits around the nominal frequency. Load–frequency control (LFC) is of importance in electric power system design and operation. The objective of the LFC in an interconnected power system is to maintain the frequency of each area within limits and to keep tie-line power flows within some pre-specified tolerances by adjusting the MW outputs of the generators so as to accommodate fluctuating load demands.

Modeling, Simulation and Control of Wind Diesel Power Systems

Wind diesel power systems (WDPS) are isolated microgrids which combine diesel generators (DGs) with wind turbine generators (WTGs) [...]

Semi-Markov and hidden Markov models of autonomous wind diesel complex functioning

Semi-Markov and hidden Markov models of autonomous wind diesel complex functioning

Optimization of synchronized frequency and voltage control for a distributed generation system using the Black Widow Optimization algorithm

Abstract A distributed generation network could be a hybrid power system that includes wind–diesel power generation based on induction generators (IGs) and synchronous generators (SGs). The main advantage of these systems is the possibility of using renewable energy in their structures. The most important challenge is to design the voltage-control loop with the frequency-control loop to obtain optimal responses for voltage and frequency deviations. In this work, the voltage-control loop is designed by an automatic voltage regulator. A linear model of the hybrid system has also been developed with coordinated voltage and frequency control. Dynamic frequency response and voltage deviations are compared for different load disturbances and different reactive loads. The gains of the SG and the static volt-ampere reactive compensator (SVC) controllers in the IG terminal are calculated using the Black Widow Optimization (BWO) algorithm to insure low frequency and voltage deviations. The BWO optimization algorithm is one of the newest and most powerful optimization methods to have been introduced so far. The results showed that the BWO algorithm has a good speed in solving the proposed objective function. A 22% improvement in time adjustment was observed in the use of an optimal SVC. Also, an 18% improvement was observed in the transitory values.

A Comparative Study of the Optimal Sizing and Management of Off-Grid Solar/Wind/Diesel and Battery Energy Systems for Remote Areas

Electrification in rural areas is relatively costly compared to urban areas. Therefore, the aim of this research is to identify the best combination of hybrid renewable energy systems (HRESs) to satisfy the load demand in a sustainable and cost-efficient way. The techno-economic study of stand-alone hybrid photovoltaic–wind turbine–diesel–battery-converter energy systems based on the hybrid optimization model for electric renewable (HOMER) simulation has been analyzed for various locations in the Tamil Nadu state, India. Various combinations of the systems have been compared and analyzed based on the performance of their technical parameters, costs, the electrical power production of each source, and unmet load. The findings indicated that the off-grid solar–wind–diesel–battery configuration is the most economical for all the sites among other system configurations. Comparing with conventional diesel generators among all the locations, a combination of solar/wind/diesel/battery is the economically best design for Thoothukudi, with the least and most reliable solution in terms of net present cost and cost of energy. Also, the impact of intermittent variables becomes significant, so sensitivity analysis for the various parameters has been carried out. The study finds that the least cost of electricity and the net present cost of electricity for Thoothukudi are achieved at 0.266 $/kWh and 138,197 $, respectively. This is economical compared to a stand-alone diesel system where the obtained COE is $1.88 and the NPC is $977523. In the stand-alone diesel operating mode, 41854 kg of CO2is produced, which is higher than CO2emissions associated with any other renewable energy systems. According to the results, the Kanyakumari location outperforms in terms of producing environmental pollutants with emission of 1,020 kg/y CO2at their best. Moreover, the results of the proposed study imply that the proposed renewable energy system in remote sites could be a more economical measure.