Renewable Energy Based Power System Research Articles

Comparative life cycle assessment of integrated renewable energy-based power systems

Integrated renewable-based power cycles should be employed to produce more sustainable electricity. This is a comparative life cycle assessment (LCA) of three combined power plants, encompassing: case 1 involving combined geothermal and wind, case 2 featuring combined geothermal and solar, and case 3 integrating wind and solar systems. The base case perovskite solar cell (PSC) modelling assumes a 3-year lifespan and a power conversion efficiency of 17 %. However, diverse scenarios are evaluated through a sensitivity assessment involving enhancements in lifetime and efficiency. The base case evaluation emphasizes that the phases with the most significant negative environmental effects which includes the drilling of geothermal wells, construction of wind plants, and manufacturing and installation of PSCs. The midpoint findings indicate that boosting the power conversion efficiency of PSC from 17 % to 35 % yields a notable decrease in environmental impact. Moreover, extending the lifetime from 3 to 15 years led to reduction in CO2 emissions from 0.0373 and 0.0185 kg CO2 eq/kWh to 0.026 and 0.0079 kg CO2 eq/kWh in cases 2 and 3, respectively. Assessing worst and best-case scenarios highlights significant declines in certain impact categories. In case 3, terrestrial ecotoxicity (TE), photochemical oxidant formation (POF), human toxicity (HT), marine ecotoxicity (ME), and marine eutrophication (MU) saw reductions exceeding 88 % compared to worst-case results. The environmental effects observed in cases 2 and 3 stem from toxicity and metal depletion, mainly linked to the PSC. Endpoint results revealed that when considering a PSC lifespan of 10 years or more, the detrimental ecosystem impacts of cases 2 and 3 become less severe than those of case 1. Uncertainty assessment has been done for different cases and impact categories. The study's results are also novel in which it evaluated the innovative PSC technology when integrated with other renewable resources, contrasting it with other integrated plants.

Design and simulation of bidirectional DC-DC converter topology for battery applications

Recently, energy storage has become a significant topic for renewable energy based power system applications. Batteries are one of the most popular energy storage devices adopted by renewable energy sources, electrical vehicles and grid connected systems. In this context, the bidirectional DC-DC converter (BDC) enables bidirectional power flow by controlling the charging and discharging stage of the battery in battery applications. Accordingly, the battery current is regulated through the duty cycle of the BDC considering the state of charge of the battery and current direction. In this study, a non-isolated BDC, has a buck and boost principle of operation, is designed, analysed and simulated under various case studies. In the designed system, BDC controls the bidirectional power flow between the battery and DC link. Specifically, in the charging stage of battery operating in buck mode, DC-link supplies the power to the battery and BDC regulates the battery current using proportional-integral (PI) controller. On the other hand, in the discharging stage of the battery operating in boost mode, when DC source is disconnected, the battery supplies the power to DC load and DC-link voltage is controlled by the BDC via PI controller. The simulation results are presented to show the operation and control of the BDC under different scenarios.

Reducing the Ecological Footprint and charging cost of electric vehicle charging station using renewable energy based power system

Ecological Footprint of electric vehicle (EV) charging stations primarily focuses on three parameters: direct/indirect emissions, manpower and physical land requirement. Electric vehicle charging stations rely on electricity to charge EV batteries, and electricity source can significantly influence their environmental impact. The Ecological Footprints of EV charging station is estimated as 40.69 gha. The potential EF reduction of EV charging station is 89.9 % by using proposed hybrid power system. The Ecological Footprint of EV charging is about 3.1 × 10−4 gha/kWh of batteries charging. However, proposed hybrid system may reduce environmental impact of battery charging as 3.15×10−5 gha/kWh of batteries charging. The lifecycle cost of batteries charging is estimated as 0.168 $/kWh. It may reduce as 0.107 $/kWh of batteries charging with installation of proposed hybrid system. Thus, it is crucial to promote the use of renewable energy sources to power electric vehicle charging stations and minimize their environmental impact.

Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller

The increasing interest in renewable energy-based power systems globally is driven by their abundance and environmentally friendly attributes. Islanded hybrid microgrid systems (IHMS) are a relatively new development in this field and involve the integration of two or more sustainable sources, such as wind turbines, solar photovoltaic (PV) systems, and other forms of renewable energy such as the ocean, wave, and geothermal energy. In order to ensure an uninterrupted power supply for the growing community and industrial sector of Perhentian Island, Malaysia, alternative power sources must be properly synchronized and managed through an energy management system. To this end, the main contribution of this study is the comprehensive analysis of various optimization methods in terms of net present cost (NPC) and convergence rate. The results of the analysis indicate that HOMER proved to be relatively faster in terms of convergence rate, with the NPC recorded as 387,185$ and the Levelized Cost of Energy (LCOE) recorded as 0.64$/kWh, which are the least among the other techniques evaluated. The hybrid energy system was designed to acquire the optimal quantity and size of power-generating modules, including PV systems, wind turbines, batteries, and diesel generators, while also meeting the load requirements. The optimization problem incorporated the LCOE and NPC into the cost function. Various optimization techniques were developed and tested. In addition, an advanced control method, which includes the use of Proportional–integral–derivative (PID) control and Fuzzy Logic Controller (FLC) with automated tuning, was applied to manage voltage and frequency. The control strategy was implemented in MATLAB Simulink, along with a full model of the islanded hybrid microgrid system. The simulation results demonstrate the effectiveness of the proposed FLC in maintaining the voltage and frequency within the acceptable range during various operating conditions. In conclusion, this manuscript provides a comprehensive study on the optimization and control of a solar-wind islanded hybrid microgrid. The proposed approach can be used as a valuable tool for the design and operation of solar-wind islanded hybrid microgrids in remote and islanded communities.

Multi-area load frequency regulation of a stochastic renewable energy-based power system with SMES using enhanced-WOA-tuned PID controller

This paper presents a novel nature-inspired meta-heuristic optimization algorithm known as the Enhanced Whale Optimization Algorithm (EWOA), which imitates humpback whales' social behavior to solve the optimization of multi-area automatic load frequency control (LFC) problems of a stochastic renewable energy-based power system with superconducting magnetic energy storage (SMES). An EWOA algorithm is presented in response to the limitations of the conventional WOA algorithm, including its sluggish convergence time, low accuracy, and propensity to easily enter local optimum. The system model investigated includes some physical constraints such as the time delay (TD), generation rate constraint (GRC), reheat turbine (RT), and the dead band (DB). The impacts of these physical constraints on the dynamic performance of the proposed controller were investigated. The EWOA algorithm is utilized to dynamically optimize the parameters of the PID controller for optimal system performance. The effectiveness and dynamic performance of the proposed controller are compared with the conventional WOA using some performance metrics. The system model also includes superconducting magnetic energy storage (SMES) units in both areas and their impacts on the system performances are also investigated. The effects of the changes of two different parameters of the system (frequency bias parameter, B, and the governor speed regulation, R) on the frequency deviation responses and the controller's robustness are examined. It is evident from the results that the dynamic performance of the proposed controller is better than that of the conventional WOA and it is more robust and stable to changes in system loading, parameters, and step load perturbation.

Survey on Modeling of Temporally and Spatially Interdependent Uncertainties in Renewable Power Systems

Constructing a renewable energy-based power system has become an important development path for the power industry’s low-carbon transformation. However, as the proportion of renewable energy generation (REG) increases, the power grid gradually changes to uncertainty. Technologies to address this issue have been introduced. However, the majority of existing reviews focus on specific uncertainty modeling approaches and applications, lacking the consideration of temporal and spatial interdependence. Therefore, this paper provides a comprehensive review of the uncertainty modeling of temporal and spatial interdependence. It includes the discrete and continuous stochastic process-based methods to address temporal interdependence, the correlation coefficient and copula functions in modeling spatial interdependence, and the Itô process and random fields theory to describe temporal and spatial interdependence. Finally, their applications in power system stability, control, and economic scheduling are summarized.

Development of renewable energy-based power system for the irrigation support: case studies

Abstract The development of renewable energy-based applications is nowadays a forced demand of society, for chasing the target set by the governments and the concerned organizations, to reduce or limit the carbon penetration in the environment. Sincere efforts are being made by academics and researchers to create applications based on renewable energy that are reliable and efficient. Green revolutions increase agricultural fields and alter grain production rates, but they also increase energy consumption since agricultural machinery is used more efficiently, mostly for irrigation needs. The purpose of this work is to introduce a hybrid renewable energy system (HRES) that can take the place of the diesel pump often used for time-bound crop irrigation. This HRES system consists of a photovoltaic generator as the main power source supported by a battery energy storage system. For this hybrid system, the development of a Proportional & Integral (PI)-based integrated hybrid controller is proposed to regulate the charge/discharge cycle of the battery energy with maintaining the load demand simultaneously. Controlling of this hybrid system is carried out in the LabVIEW environment.

Designing of robust frequency stabilization using optimized MPC-(1+PIDN) controller for high order interconnected renewable energy based power systems

The challenge of controlling frequency becomes greater as the complexity of a power network increases. The stability of a power system is highly dependent upon the robustness of the controller. This paper presents automatic generation control (AGC) of a four-area interconnected power system along with integrated renewable energy sources of PV and wind energy. The designed model is a challenge given the increased penetration levels of PV and wind along with a thermal-hydropower system. The addition of a hydropower system as a fourth type results in the pole of the open loop system of the hydropower system being located at the right half side of the s-plan. This demands a robust control. A novel MPC-(1 + PIDN) is designed for high-order interconnected areas (HOIA) to stabilize the frequency in a robust way. The salp swarm algorithm is adopted to optimize the parameters of the PIDN controller. The performance of the proposed controller under HOIA is tested in a unbalanced load environment with uncertainty in the power system. The proposed controller can effectively handle the frequency disruption by stabilizing it in 0.86 s for Area-1, 1.08 s for Area-2, 0.81 s for Area-3, and 0.84 s for Area-4 with an average time of 0.89 s for all the areas, whereas the average time for GWO: PI-PD, MPC/PI and GA-PI is 3.48 s, 10.36 s and 18.47 s, respectively. The results demonstrate the effectiveness of the controller when compared to other controllers.

Dynamic modelling and multi-objective optimization of off-grid hybrid energy systems by using battery or hydrogen storage for different climates

The energy storage problem is an essential issue in renewable energy-based power systems. A comprehensive study is performed to evaluate off-grid hybrid renewable energy systems with a battery bank or a hydrogen system employed as the energy storage option. Dynamic modelling is proposed to see daily and seasonally changes in the system. The economic feasibility of the system and its environmental impacts are investigated in three locations. A multi-objective optimization method based on the Taguchi approach is employed to minimize both levelized cost of energy and the CO2 emissions. Various weight factors were assigned to understand the response of different optimization targets. The results highlight that the hybridization of energy resources allows the annual emissions to be cut by 68–78% for battery storage, 84–90% for hydrogen storage, compared to a diesel-only system. Despite having higher costs, the systems with hydrogen storage can store energy in the long term; therefore, they have lower CO2 emissions.

Make your home carbon-free. An open access planning tool to calculate energy-related carbon emissions in districts and dwellings

Reducing the carbon emissions of buildings and whole districts is one of the main objectives of sustainable development goals. Both policymakers and end-users need reliable information to take actions that lead to achieving those goals. For this, an innovative open access planning tool has been developed to assess the effect of energy consumption on the overall carbon emissions of districts, buildings, and house units. When it comes to the end-users, it would help them know the actual environmental impact of their homes and make environmentally and financially sound decisions before investing in new equipment. The tool is meant to be an online planning service for dwelling end-users and policymakers alike; thus responding to a still unresolved demand. For this, firstly, the study focuses on the obtention of a complete catalogue of open-source conversion factors, which convert the different energy sources to carbon dioxide emissions per unit of energy. Secondly, it presents two case studies to illustrate the use of the tool. The first case study explains how an end-user could estimate the energy savings that may result from changing his domestic energy habits, equipment, and sources. The second case study uses actual data from a district in Valencia (Spain) to show how renewable sources would affect the carbon footprint of an apartment block. Both study cases show greenhouse gas emissions savings by replacing the existing equipment with more efficient ones such as heat pumps or renewable energy-based power systems like photovoltaic panels. This study concludes that providing smart tools is pivotal to planning nearly Zero-Energy Districts (nZED).

Load Frequency Control (LFC) Strategies in Renewable Energy-Based Hybrid Power Systems: A Review

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in the hybrid power system. Load Frequency Controller (LFC) design ensures the reliable and efficient operation of the power system. The main function of LFC is to maintain the system frequency within safe limits, hence keeping power at a specific range. An LFC should be supported with modern and intelligent control structures for providing the adequate power to the system. This paper presents a comprehensive review of several LFC structures in a diverse configuration of a power system. First of all, an overview of a renewable energy-based power system is provided with a need for the development of LFC. The basic operation was studied in single-area, multi-area and multi-stage power system configurations. Types of controllers developed on different techniques studied with an overview of different control techniques were utilized. The comparative analysis of various controllers and strategies was performed graphically. The future scope of work provided lists the potential areas for conducting further research. Finally, the paper concludes by emphasizing the need for better LFC design in complex power system environments.

Fuzzy‐based frequency security evaluation of wind‐integrated power systems

The transition to renewable energy-based power systems is fast progressing. One of the main challenges in keeping a power system with high operational reliability is to maintain the system frequency. As synchronous generator units are being replaced with power-electronic converters, the rotating mass and the system inertia are decreasing. Virtual synchronous machine (VSM) control is a modern control technique that aims to compensate for the reduction in inertia. The usage of power electronic-based converter units equipped with VSM control has to be managed and scheduled by system operators. An assessment of the operational frequency reliability is used to evaluate different service usages. A method is proposed that allows the comparison of different frequency management strategies. The proposed method uses fuzzy logic to evaluate the system risk for abnormal frequency and the system effort in the form of frequency control usage. This allows to quickly compare different frequency management strategies whilst keeping in mind many different reliability indices. The proposed method is validated with a modified IEEE Reliability Test System with integrated wind power capacity.

Multi-Attribute Decision-Making Approach for a Cost-Effective and Sustainable Energy System Considering Weight Assignment Analysis

The need for inexpensive and sustainable electricity has become an exciting adventure due to the recent rise in the local population and the number of visitors visiting the Banana Islands. Banana Islands is a grid-isolated environment with abundant renewable energy, establishing a hybrid renewable energy-based power system may be a viable solution to the high cost of diesel fuel. This paper describes a dual-flow optimization method for electrifying the Banana Islands, a remote island in Sierra Leone. The study weighs the pros and cons of maintaining the current diesel-based power setup versus introducing a hybrid renewable energy system that takes backup component analysis into account. Hybrid Optimization of Multiple Energy Resources (HOMER) software is used in the first optimization to optimally design the various system configurations based on techno-economic and environmental characteristics. A Multi-Attribute Decision-Making (MADM) Model that takes into account in the second optimization, the Combinative Distance-based Assessment System (CODAS) algorithm, and various methods of assigning weights to the attributes is used to rank the best configuration. The results show that the hybrid renewable energy system is a better option for electrifying the Banana Islands than the current stand-alone system. The Analytical Hierarchy Process (AHP) method of weight assignment was found to be superior to the Entropy method. Biogas generator-assisted hybrid configurations outperformed diesel generator-assisted hybrid configurations. With an optimum design of 101 kW PV, 1 wind turbine, 50 kW biogas, 86 batteries, and a 37.8 kW converter, the PV-wind-biogas-battery system is rated as the best configuration. It has a net present cost (NPC) of $487,247, a cost of energy (COE) of $0.211/kWh, and CO2 emission of 17.5 kg/year. Sensitivity analyses reveal that changes in the rate of inflation and the cost of storage have a significant effect on the overall cost of the configuration.

Electrification and renewable energy nexus in developing countries; an overarching analysis of hydrogen production and electric vehicles integrality in renewable energy penetration

As the world continues to fight against climate change, renewables have emerged as an imminent solution, however, a model that can help (developing) countries to effectively migrate to a renewable energy-based power sector is limited in literature. In this study, a comprehensive electricity generation analysis based on an hourly time-step is done in a bid to solve to electrification crisis in developing countries. This study aims to present the feasible pathways with which sustainable electrification can be achieved. This is done by considering the financial feasibility, environmental sustainability, and technical viability of different technological combinations. In comparison to existing literature, this study is novel as the integration of both renewable energy sources and a fossil fuel source is analyzed. With Nigeria being the study area, the integration of five renewable energy-based technologies namely; offshore wind power plant, onshore wind power plant, solar photovoltaic system, concentrated solar power plant, and hydropower plant as well as pumped hydro storage system is considered within the scope of this study. Based on the results of the analysis, out of the ninety-nine different combinatory scenarios modeled, the most viable solution with the use of renewables and natural gas is the combination of natural gas power plants, on-shore wind power plants, and solar photovoltaic systems. This requires a large capacity installation (32,500 MW of natural gas power plant, 12,000 MW of solar photovoltaic plant, and 7000 MW of on-shore wind power plant) as well as a total annual cost and an investment cost of $ 22B and $ 48.7B. Furthermore, solving the poised problem based on renewable energy technologies will only require the combination of on-shore wind power plants, hydropower plants, solar photovoltaic system, and pumped hydro storage system. The integration of plug-in battery electric vehicles and hydrogen production will help maximize the electricity produced from the renewable energy-based power systems. This will also reduce the overall carbon emission from the country at large. Beyond providing feasible scenarios and plans to tackle the existing electricity production, guidelines on steps (not to take) to tackle the electrification problem are embedded in this study.

Prospects of Hybrid Renewable Energy-Based Power System: A Case Study, Post Analysis of Chipendeke Micro-Hydro, Zimbabwe

Fossil fuel-based energy sources are the major contributors to greenhouse gas (GHG) emission and thus the use of renewable energy (RE) is becoming the best alternative to cater for the increasing energy demand in both developing and developed nations. Chipendeke is a rural community in Zimbabwe, in which electricity demand is partially served by the only micro-hydro plant and hence, load shedding is a regular practice to keep essential services running. This study explored a suitable opportunity to identify a feasible system with different energy sources that can fulfill the current and projected future load demand of the community. A techno-economic feasibility study for a hybrid RE based power system (REPS) is examined considering various energy sources and cost functions. Six different system configurations have been designed with different sizing combinations to identify the most optimum solution for the locality considering techno-economic and environmental viability. The performance metrics considered to evaluate the best suitable model are; Net Present Cost (NPC), Cost of Energy (COE), Renewable Fraction (RF), excess energy and seasonal load variations. In-depth, sensitivity analyses have been performed to investigate the variations of the studied models with a little variation of input variables. Of the studied configurations, an off-grid hybrid Hydro/PV/DG/Battery system was found to be the most economically feasible compared to other configurations. This system had the lowest NPC and COE of $ \$ $ 307,657 and $ \$ $ 0.165/kWh respectively and the highest RF of 87.5%. The proposed hybrid system could apply to any other remote areas in the region and anywhere worldwide.

Optimized Tilt Fractional Order Cooperative Controllers for Preserving Frequency Stability in Renewable Energy-Based Power Systems

The low system inertia and the high sensitivity to load and generation fluctuations represent the main challenges for future ambitious plans of modern power systems accompanied by high penetrations levels of the renewable energy sources (RESs). Therefore, this article presents a new approach for solving the load frequency control (LFC) in addition to the virtual inertia control (VIC) in interconnected RESs penetrated power systems using cooperative tilt-based controllers and a hybrid modified particle swarm optimization with genetic algorithm (MPSOGA). The VIC system is adopted using superconducting magnetic energy storage (SMES) to provide sufficient inertial energy for system stability. Two tilt-based controllers are employed in each area using the tilt-integral-derivative (TID) controller for the SMES and TID with filter (TIDF) for the LFC function. The cooperative optimum design of the TID/TIDF controllers leads to the enhancement of frequency stability in studied two-area power systems. The formulated optimization process aims to minimize the frequency nadir settling time during abrupt changes of RESs and/or load changes, considering the cooperative control of LFC and VIC. The proposed approach has been applied to a case study consisting of two-area power systems, connected via hybrid high voltage DC/AC (hybrid HVAC/HVDC) tie-line, integrated with distributed conventional generations, photovoltaic (PV), and wind generation systems. Performance analysis has been conducted to demonstrate the effectiveness of the proposed method is compared to the genetic algorithm (GA) and particle-swarm optimization (PSO) using high fluctuations of renewable generations under extreme changes in loading conditions and physical parameters variation. The obtained results show the superiority of MPSOGA approach on the other competitive optimization techniques.

State of the Art on Modeling and Optimization of Smart Electricity Networks

The increase in population and industrialization has increased the consumption of electricity. Currently, it is impossible to live without electricity. Indeed, it is necessary for the economic, social and industrial progress in all the countries of the world. This is why we are always asked to develop all types of energy to produce clean and safe to improve energy efficiency. Indeed, the use of new renewable energy sources helps to mitigate greenhouse gas emissions and dependence on centralized energy sickles. The difficulties of renewable energy-based power systems lie in their production, which is not controllable and may not meet the increase in energy demand.

Cooperative Optimization of Networked Microgrids for Supporting Grid Flexibility Services Using Model Predictive Control

The transition towards fully renewable energy-based power systems will require to increase the number of reserves at the System Operators' (SOs) disposal to provide flexibility on the energy management process. The microgrid's ability of integrating distributed energy resources, loads and energy storage systems (ESS) appears as a powerful flexibility tool. Nevertheless, the associated control problem of microgrids increases with the number of connected devices. A structuration of the distribution grids in networks of microgrids is proposed, focusing on their ability to provide flexibility services. The complexity of the associated optimization algorithm is faced using Distributed Model Predictive Control (MPC). The algorithm is divided in two steps. The first one is applied to the cooperative participation of microgrids in the day-ahead market. The second step covers the interaction with the SO offering flexibility services in exchange for a financial benefit. The financial benefit is optimally shared between the networked microgrids to satisfy the power profile requested by the SO at the lowest cost. As the proposed control algorithm presents both continuous and binary variables, its associated optimization problem is formulated using the Mixed Logic Dynamic (MLD) framework, which results in a Mixed Integer Quadratic Programming problem (MIQP).

An enhanced full‐feedforward strategy to mitigate output current harmonics in grid‐tied inverters

The grid-tied inverters are the most vital components in renewable energy-based power systems. Hence, maintaining the power quality of a grid-tied inverter output within the standard range is an ongoing challenge in the power system. The appeared individual harmonics at inverter output current caused by grid voltage harmonics depend on the inverter output equivalent admittance. This consists of a combination of admittance seen from the point of common coupling and the phase-locked loop path. Therefore, the precise calculation of the aforementioned admittance is an inevitable requirement to design a harmonic mitigation strategy. By adding a virtual admittance to the system through modifications in the inverter control loop, the output equivalent admittance can be removed. For this purpose, in this paper, a novel full-feedforward harmonic suppression scheme is proposed which can effectively eliminate individual harmonics injected from the grid. Consequently, the individual output current harmonics of the inverter will be effectively suppressed. Simulation and experimental results have been carried out for a typical single-phase grid-tied inverter to verify the efficiency of the proposed scheme against emitted harmonics from the grid.

Optimal planning and electricity sharing strategy of hybrid energy system for remote communities in Nigeria

In recent times, renewable energy-based power systems are being used to address energy poverty or shortage that is experienced in developing countries. To improve these systems’ applicability, they are used to design a hybrid energy system. It is against this backdrop that this paper focuses on how hybrid energy systems can be designed optimally to address electricity sharing between domestic and productive use in remote communities. This paper, therefore, proposes a mixed-integer multi-objective optimization model for electricity sharing between domestic and productive use in remote communities. The model considered the number of solar photovoltaic (PV) systems acquisition, the total cost of energy utilized, and the cost of CO2 emissions avoided. A genetic algorithm was used to optimize these decision variables. The proposed model evaluation was carried out using data from three remote communities in South-West Nigeria. The results obtained from the model show that the number of installed solar PV systems in the first, second, and third communities is 74, 76 and 73 solar PV systems, respectively. For 25 years planning period, the first community required 29,554.05 kWh, the second community required 28,280.20 kWh, and the third community required 28,608.70 kWh. The average values for productive use of electricity from the conventional energy sources for the first community was 0.358, for the second community was 0.338, and for the third community was 0.348. In terms of the maximum productive use of electricity from the solar PV system, the first and second communities had the same value (0.39), while the third community's maximum had a value of 0.40. The developed model will be useful for evaluating the expected number of functional solar PV systems required, managing the quantity of electricity supply from the national grid and the generators, and planning electricity sharing for domestic and productive use within the selected communities.