Renewable Systems Research Articles

Techno-economic evaluation of hybrid renewable hydrogen systems in Saudi Arabia

Techno-economic evaluation of hybrid renewable hydrogen systems in Saudi Arabia

Quantitative assessment and optimization strategy of flexibility supply and demand based on renewable energy high-penetration power system

Quantitative assessment and optimization strategy of flexibility supply and demand based on renewable energy high-penetration power system

Techno-Economic Analysis of Grid-Connected Highway Solar EV Charging Station

AbstractSolar electric vehicle (EV) charging stations offer a promising solution to an environmental issue related to EVs by supplying eco-friendly electricity. Herein, we designed and analyzed a grid-connected highway solar EV charging station for 2022, 2030, and 2050 under two scenarios: Current policy scenario with restricted grid sales and policy mitigation scenario allowing grid sale. Future systems consider changes in EV charging station, grid CO2 emissions, carbon prices, and renewable costs. In 2022, high PV and battery costs led to a grid-only system. By 2030 and 2050, significant reductions in PV costs enabled systems with substantial PV capacity, especially under the policy mitigation scenario. Economic analysis showed that enabling grid sales reduces net present cost (NPC) by 40% in 2030 and 35% in 2050 compared to the current policy scenario, with significantly lower levelized cost of energy. CO2 emissions from EV operation are projected to be 44% and 3% of 2022 levels by 2030 and 2050, respectively. The policy mitigation scenario further reduces CO2 emissions by 22% in 2030 and 25% in 2050 compared to the current policy scenario. Sensitivity analyses reveal that increased grid sale capacity leads to higher renewable penetration and lower NPC but also increased grid congestion, highlighting the need for efficient grid management. Policymakers should consider revising regulations to support higher PV penetration and manage grid congestion. This study supports the transition to renewable systems and underscores the importance of policy measures in achieving sustainable energy goals.

Single-Phase Multilevel Inverter Design with Low Voltage Stress and Optimized Control Model

The research explicitly examines the power control of a single-phase renewable energy sources battery energy storage system (RES-BESS)mixed-distributing network designed for domestic usage. The system utilizes a cascaded H-bridge (CHB) conversion architecture as its grid connection. The CHB uses a hierarchical power management design consisting of a single centralized regulator for the top layer and several dispersed regulators for the bottom layer. The higher stratum produces the reference signals that need to be monitored. Under optimal circumstances, the CHB should operate efficiently with all solar panels at their Maximum Power Point (MPP) and with an electrical factor of 1. However, several functional limitations prevent this from always being feasible, such as limits related to voltage and current, biased shadowing, and State of Charge (SOC) incompatibilities. Hence, a novel optimization technique is introduced to take into account these impacts directly and calculate a collection of reference parameters to be monitored. This approach aims to maximize the long-term viability of the structure while ensuring compliance with the given limitations. The optimization method in this structure incorporates many functional needs, prioritizing them based on the specific operating circumstances. The decentralized management layer utilizes traditional feedback-controlling methods to monitor the best referencing. Experimental findings are conducted to verify the best method under normal conditions for operation and evaluate the efficacy of the suggested CHB arrangement with the complete control technique.

Employing battery energy storage systems for flexible ramping products in a fully renewable energy power grid: A market mechanism and strategy analysis through multi-Agent Markov games

In high-proportion renewable energy power systems, flexible ramping products (FRPs) are critical for mitigating the volatility of renewable energy outputs and enhancing the adaptability of power systems. This paper aims to explore a fully renewable energy power system, with a battery energy storage system (BESS) as the sole provider of FRPs. An innovative market mechanism and new approaches to market equilibrium analysis are introduced. Initially, a common day-ahead (DA) market is established, covering both electricity and ancillary services with FRPs. The setup allows FRP providers to make bidding decisions and get rewarded based on actual ramping mileages. A bi-level multi-agent Markov game (MG) model is formulated. The upper level integrates the proposed strategies of wind power plants (WPP), photovoltaic power plants (PVP), and BESS, while the lower level encompasses the joint market clearing mechanism. An iterative solution algorithm, using reinforcement learning, is also introduced to address the model, effectively circumventing the privacy concerns associated with traditional mathematical programming methods. The proposed solution models and strategies are validated and demonstrated to be effective through two illustrative examples, highlighting their application and relevance in fully renewable energy power systems.

Environmental and economic analysis of cold ironing using renewable hybrid systems

Environmental and economic analysis of cold ironing using renewable hybrid systems

Robust Distributed Load Frequency Control for Multi-Area Power Systems with Photovoltaic and Battery Energy Storage System

The intermittent power generation of renewable energy sources (RESs) interrupts the balance between power generation and demand load due to the increased frequency fluctuation, which challenges the frequency stability analysis and control synthesis of power generation systems. This paper proposes a robust distributed load frequency control (DLFC) scheme for multi-area power systems. Firstly, a multi-area power system is constructed by integrating photovoltaic (PV) and battery energy storage systems (BESSs). Then, by employing the linear matrix inequality (LMI) technique, the sufficient condition capable of ensuring that the proposed controller satisfies H∞ robust performance in the sense of asymptotic stability is derived. Finally, testing is conducted on a four-area renewable power system, and results verify the strong robustness of the proposed controller against load disturbance and intermittence of RESs.

Hybrid Renewable Systems for Small Energy Communities: What Is the Best Solution?

This research developed smart integrated hybrid renewable systems for small energy communities and applied them to a real system to achieve energy self-sufficiency and promote sustainable decentralized energy generation. It compares stand-alone (SA) and grid-connected (GC) configurations using a developed optimized mathematical model and data-driven optimization, with economic analysis of various renewable combinations (PV, Wind, PHS, BESS, and Grid) to search for the optimal solution. Four cases were developed: two stand-alone (SA1: PV + Wind + PHS, SA2: PV + Wind + PHS + BESS) and two grid-connected (GC1: PV + PHS + Grid, GC2: Wind + PHS + Grid). GC2 shows the most economical with stable cash flow (−€123.2 annually), low CO2 costs (€367.2), and 91.7% of grid independence, requiring 125 kW of installed power. While GC options had lower initial investments (between €157k to €205k), the SA configurations provided lower levelized costs of energy (LCOE) ranging from €0.039 to €0.044/kWh. The integration of pumped hydropower storage enhances energy independence, supporting peak loads for up to two days with a storage capacity of 2.17 MWh.

Comprehensive analysis of a novel sustainable photovoltaic/thermal assisted ground source heat pump system with energy storage

The imbalance of soil heat is a significant issue hindering the sustainable operation of ground source heat pump (GSHP) systems, especially under single-mode heating conditions. To address this challenge and develop a more energy-efficient, economical, and sustainable heating system, this paper proposes a novel PV/T-GSHP-PCM (photovoltaic/thermal-ground source heat pump-phase change material) system. A simulation model of the system was developed, and its performance was thoroughly analyzed. Furthermore, the comprehensive performance of four different system coupling configurations was compared. The study concluded that the PV/T-GSHP-PCM system increases energy efficiency by 13 % and reduces operating costs by 32 % compared to conventional GSHP systems. Furthermore, the PV/T-GSHP-PCM system achieves zero energy consumption, zero operational cost, and zero carbon dioxide emissions. After 10 years of continuous operation under single-mode heating, the soil heat imbalance rate stabilized at around 7 %, the heating coefficient of performance of the system decreased by only 0.04. This system demonstrates sustainable and efficient green heating. This study provides valuable insights for advancing research on sustainable and renewable energy-based heating systems.

Sustainable hybrid renewable energy management system for a community in island: A model approach utilising Hybrid Optimization of Multiple Energy Resources optimization and priority setting‐based Supervisory Control and Data Acquisition operation

Sustainable hybrid renewable energy management system for a community in island: A model approach utilising Hybrid Optimization of Multiple Energy Resources optimization and priority setting‐based Supervisory Control and Data Acquisition operation

Integration of renewable energy-powered cold storage solutions for reducing post-harvest food waste in rural agricultural areas

Post-harvest food loss remains a critical challenge in rural agricultural areas, exacerbated by inadequate storage facilities and unreliable energy access. This study develops and optimizes an advanced renewable energy-powered cold storage system tailored for rural settings, integrating solar and wind energy with phase change materials (PCMs) for efficient energy storage. The system incorporates Internet of Things (IoT)-based sensors and artificial intelligence (AI)-driven energy management to maintain optimal storage conditions and enhance energy efficiency. Field trials conducted in Lincolnshire, UK, and Appalachian regions of the US demonstrated significant reductions in post-harvest food loss by an average of 43.5%, extensions in produce shelf-life by up to 300%, and increased income for smallholder farmers by approximately 43%. The system also achieved an 80% reduction in greenhouse gas emissions compared to conventional diesel-powered systems. Economic analyses revealed a shorter payback period and higher return on investment, confirming the system's viability. High user satisfaction and adoption rates indicate the system's practicality and potential for widespread implementation. The findings suggest that integrating renewable energy with smart technologies in cold storage solutions offers a scalable and sustainable approach to enhancing food security, promoting economic growth in rural areas, and supporting environmental objectives globally.

Double-pancake superconducting coil integrated with DFIG-based wind power systems under voltage-dip events: Design and performance analysis study

The doubly fed induction generator (DFIG)-based wind turbine provides massive development in power generation. Uncertain power oscillations and voltage-dip events affect the stability of the DFIG. To mitigate the effect of voltage-dips in short period, superconducting magnetic energy storage (SMES), which possess rapid energy exchange and high power density, is integrated with large-scale renewable power systems. SMES is integrated at the DC link of the DFIG to ensure the power balance and fault ride-through (FRT) capability. During this operation, frequent current changes occur in the high-temperature superconducting (HTS) coil, which leads to an increase in AC losses. As a remedy, an additional power converter structure controlled with a model-predictive controller (MPC) is proposed. Firstly, a scale-down HTS double-pancake coil model is designed using a finite element model by which transport current loss and magnetic field formulation are studied. Additionally, the critical coil current is also verified through experimental studies. The effectiveness of the proposed MPC-based SMES integrated DFIG on DC link voltage and grid current under IEC-61000-4-11 standard, symmetrical and asymmetrical voltage-dip cases are investigated. The obtained results demonstrate that the proposed system effectively reduces transients in DC link voltage and improves the FRT capabilities of the grid.

Frequency stabilization of interconnected diverse power systems with integration of renewable energies and energy storage systems

Recent improvements in renewable energy sources (RESs) and their extensive use in the power industry have created significant issues for their operation, security, and management. Due to the ongoing reduction of power system inertia, maintaining operational frequency at its nominal value and minimizing tie-line power variations constitute essential variables for these improvements. A novel improved frequency stabilization approach based on modified fractional order tilt controller is presented for interconnected diverse power systems with integration of sea wave energy, photovoltaic, wind, energy storage system and biodiesel generator. The fractional order tilt integral double derivative (FOTIDD2) is a novel controller that is developed to address the frequency stabilization problems of a hybrid power structure that is integrated with sources of clean energy and devices for storing energy. A recent optimization algorithm inspired by human behavior called mother optimization algorithm (MOA) is applied to adjust the coefficient of the proposed cascaded controller. The FOTIDD2 controller was compared with other control methods in terms of its transient performance, in order to determine its effectiveness. Further, the mother optimization algorithm results are compared with those of sine cosine algorithm (SCA), fox optimization algorithm (FOA), and grey wolf optimization (GWO). FOTIDD2 controller was found to be more effective than PID controller in respect of reducing overshoot (Osh) by 79.31%, 83.78% and 67.99%, improving time settlement by 33.22%, 29.87%, and 22.45% and reducing undershoot (Ush) by 79.13%, 89.34%, and 86.90% for the (∆F1), (∆F2), and (∆Ptie), respectively.

Design of reliable standalone utility-scale pumped hydroelectric storage powered by PV/Wind hybrid renewable system

With a target of 35 % renewable energy in the country’s energy mix by 2030, the goal of this research is to support the Libyan government’s plan to maximize the use of environmentally friendly and sustainable energy sources. This will be accomplished by making effective use of the region’s plentiful natural resources. The feasibility of wind and solar energy has been established by local research, and the presence of highlands that can store pumped hydropower (PHS) makes hybrid renewable energy systems (HRES) even more feasible. These systems might offer a sizable edge over competitors in the regional energy market. In this study, PHS was utilized to stabilize electricity production in addition to storing energy. A hydropower turbine provides electricity to the load, and the PHS system is powered by a PV/wind supply. By lowering the volatility of wind and photovoltaic power generation, the suggested system could offer a more dependable renewable energy source without requiring complicated control mechanisms. This strategy could encourage a wider adoption of renewable energy, which could be especially advantageous for developing nations. Under particular load and climate conditions, the energy production of different solar PV array and wind turbine farm configurations was estimated using the System Advisor Model (SAM) software. The ideal HRES configuration consists of a 290 MW wind farm, a 154 MW solar PV field, and a 508 MW PHS system. This configuration will provide 100 % of the annual electrical demand of 513 GWh, plus a 20 % safety margin. The levelized cost of energy (LCOE), estimated at $211.65/MWh, is reduced by this configuration. It is anticipated that the $929.02 million initial investment will be recovered in 11 years, and the system will turn a profit in the following 9 years. Also, the planned HRES will stop 532.17 tons of CO2 emissions from being released each year.

Addressing extreme weather events for the renewable power-water-heating sectors in Neom, Saudi Arabia

A renewable energy design optimization model is proposed to plan investments in power, water, and heat technologies. The intermittent nature of renewables requires that these models capture the variability and complementarity of resources at high spatial and temporal resolutions. However, most planning models use time-series reduction methods that, while capturing data variance, often smooth out extreme weather or demand patterns. To account for extreme patterns and design reliable energy systems, we propose a clustering-optimization framework that considers extreme weather days. This framework is applied to design an integrated multi-sector energy system for the Neom region in Saudi Arabia. Our results show that fully renewable systems designed without considering extreme days could not meet demands and instead required external power or water supplies during a post-optimization simulation. Once extreme days were considered in the optimization, system reliability increased at the expense of larger generation and storage capacity investments.

Mixed Thermal and Renewable Energy Generation Optimization in Non-Interconnected Regions via Boolean Mapping

Global efforts aiming to shift towards renewable energy and smart grid configurations require accurate unit commitment schedules to guarantee power balance and ensure feasible operation under different complex constraints. Intelligent systems utilizing hybrid and high-level techniques have arisen as promising solutions to provide optimum exploration–exploitation trade-offs at the expense of computational complexity. To ameliorate this requirement, which is extremely expensive in non-interconnected renewable systems, radically different approaches based on enhanced priority schemes and Boolean encoding/decoding have to take place. This compilation encompasses various mappings that convert multi-valued clausal forms into Boolean expressions with equivalent satisfiability. Avoiding any need to introduce prior parameter settings, the solution utilizes state-of-the-art advancements in the field of artificial intelligence models, namely Boolean mapping. It allows for the efficient identification of the optimal configuration of a non-convex system with binary and discontinuous dynamics in the fewest possible trials, providing impressive performance. In this way, Boolean mapping becomes capable of providing global optimum solutions to unit commitment utilizing fully tractable procedures without deteriorating the computational time. The results, considering a non-interconnected power system, show that the proposed model based on artificial intelligence presents advantageous performance in terms of generating cost and complexity. This is particularly important in isolated networks, where even a-not-so great deviation between production and consumption may reflect as a major disturbance in terms of frequency and voltage.

Robust Control of Electrical Machines in Renewable Energy Systems: Challenges and Solutions

The increasing global demand for energy driven by population growth necessitates a shift towards renewable energy sources to address sustainability and environmental concerns. Renewable energy sources and how they function in tandem with electrical equipment to generate power are covered extensively in this study. Renewable sources like solar-thermal, hydro, wind, wave, tidal, geothermal, and biomass-thermal utilize electric machines to convert various forms of stored energy into electricity. The paper classifies these machines based on their design and application in renewable systems, highlighting the most common types, including DC, induction, and synchronous machines. It also evaluates their performance according to efficiency, power density, and cost-effectiveness. A primary focus is on the challenges associated with controlling electrical machines in renewable energy systems, including issues related to intermittency, grid integration, nonlinear dynamics, fault tolerance, harmonics, efficiency optimization, thermal management, scalability, real-time control, and cost constraints. The paper concludes by discussing the need for advanced control strategies and solutions to address these challenges, aiming to enhance a reliability, efficiency, and performance of renewable energy systems.

Simulation of 1 MWe hybrid solar power plant by the use of nano-fluid with eccentric backup system.

In past years, concentrated solar power (CSP) with an energy backup system has been a unique renewable energy utilization system among intermittent renewable energy systems. It could allow a CSP plant to operate as a base load system in the future. This paper simulates a solar power plant for 1 MWe. Parabolic trough collector (PTC) array and linear Fresnel reflector (LFR) field attached consecutively to produce superheated steam at 40MPa. The Rankine cycle has been used to run the steam turbine and an electricity generator is attached to a steam turbine to convert mechanical energy into electrical energy. Maximum temperature attained at the turbine inlet is 418.13 ˚C in 12:00-13:00 time slot in the month of January. Results show that solar power plant is feasible to produce 1 MWe. The minimum value of the power produced by the generator is 1.01 MWe in November in the 10:00-11:00 time slot whereas the maximum value of generated power is 1.57 MWe in December in the 11:00-12:00 time slot. The overall efficiency of power generated by the Rankine cycle is 21.25% in January in the 10:00-11:00 time slot. An energy storage system is attached to the system to work at night hours or in cloudy weather conditions.

Comparison of pyrolysis and anaerobic digestion processes for wheat straw biomass

Due to the growing interest in using biomass as a renewable energy source, this study presents a comparative analysis between two prominent biomass conversion technologies—anaerobic digestion and biomass pyrolysis—focused on wheat straw biomass. The objective of this study is to evaluate and compare the efficiency, energy output, and environmental impact. Anaerobic digestion was performed under mesophilic conditions (35 ± 0.5 °C) using the biochemical methanogenic potential (BMP) methodology. Pyrolysis was conducted through thermogravimetric analysis (TGA) to determine the thermal behaviour and kinetic parameters of the biomass. Biogas production led to better energetic results as high methane yields of over 11 mL CH₄ g⁻¹ VS were obtained. Additionally, the integration of both processes was considered by subjecting digestate from anaerobic digestion to pyrolysis process. Key findings demonstrate that the activation energy (Ea) for wheat straw ranged from 166.49 to 176.42 kJ·mol−1 across different kinetic methods, indicating its suitability for pyrolysis. In contrast, digestates exhibited significantly lower activation energies, with 1-week, 2-weeks, and 3-weeks digestates showing ranges of 53.27–60.79 kJ·mol−1, 38.69–46.86 kJ·mol−1, and 46.29–72.34 kJ·mol−1, respectively. These results suggest that anaerobic digestion not only produces biogas but also yields a byproduct with potential for efficient pyrolytic conversion suggesting opportunities for integrated waste management and renewable energy production systems.

Renewable sources-based efficient electric vehicle charging system through power forecasting and charge scheduling

Renewable sources-based efficient electric vehicle charging system through power forecasting and charge scheduling