Renewable Energy Microgrids Research Articles

A Novel Real-Time Fuzzy-Based Optimal Control of the Charging Cycle of a Renewable Energy Microgrid Storage System

AbstractAI-based optimal power management and online control of the storage system of the renewable energy microgrid in conjunction with the main grid that can respond instantaneously to any change in the load demand optimally and economically are the main target of this work. A novel online optimal control methodology depending on crossbreeding between the fuzzy logic and a nature-inspired technique has been proposed to determine the optimal time of carrying out the charging or discharging of the microgrid storage system and the required percentage of both of them in addition to the determination of the source of charging and the destination of discharging dynamically and economically at each time step to meet the varying of the load demand with minimum operating costs. A developed mathematical formula has been introduced to control the dynamic operation of the microgrid’s storage system. It has changed relying on the created fuzzy rules which provides outstanding accuracy for this complicated time-varying process. Furthermore, simultaneous optimal power management between the power generation as well as the storage system of the renewable microgrid and the main grid has been accomplished optimally and economically via a meta-heuristic optimizer named hunger games optimizer. The accuracy of the new methodology has been proved via a fair comparison with the previously published methods after implementing them on the same bases.

A MINI REVIEW OF RENEWABLE ENERGY STRATEGIES FOR PULAU PERHENTIAN NET ZERO JOURNEY

Sustainable energy solutions and carbon emissions reduction is imperative in the face of escalating environmental challenges. Pulau Perhentian, a pristine island paradise, serves as a compelling case study for exploring energy transition strategies towards achieving a net zero footprint. This paper review critically assesses existing literature on Pulau Perhentian energy transition initiatives, with a focus on renewable energy integration, microgrid systems, and energy efficiency measures. The review highlights the significance of energy consumption on the island's ecosystem and socio-economic development, emphasizing the urgency of reducing fossil fuel reliance. Microgrid systems emerge as pivotal for localized energy production, resilience, and community engagement. The paper explores energy storage, management strategies, and the challenges of implementing sustainable practices across sectors. By synthesizing existing knowledge, the review informs effective energy transition pathways for Pulau Perhentian and beyond. Insights extend to global policymakers, researchers, and practitioners engaged in similar efforts. Ultimately, this review underscores energy transition's critical role in preserving Pulau Perhentian's natural beauty while fostering sustainability and resilience.

Modelling and Simulation of Pico- and Nano-Grids for Renewable Energy Integration in a Campus Microgrid

Research in renewable energy sources and microgrid systems is critical for the evolving power industry. This paper examines the operational behavior of both pico- and nano-grids during transitions between grid-connected and islanded modes. Simulation results demonstrate that both grids effectively balance the power flow, regulate the state of charge (SOC), and stabilize the voltage during dynamic operational changes. Specific scenarios, including grid disconnection, load sharing, and weather-based energy fluctuations, were tested and validated. This paper models both pico-grids and nano-grids at the Singapore Institute of Technology Punggol Campus, incorporating solar PVs, energy storage systems (ESSs), power electronic converters, and both DC and AC loads, along with utility grid connections. The pico-grid includes a battery storage system, a single-phase inverter linked to a single-phase grid, and DC and AC loads. The nano-grid comprises solar PV panels, a boost converter, a battery storage system, a three-phase inverter connected to a three-phase grid, and AC loads. Both the pico-grid and nano-grid are configurable in standalone or grid-connected modes. This configuration flexibility allows for a detailed operational analysis under various conditions. This study conducted subsystem-level modelling before integrating all components into a simulation environment. MATLAB/Simulink version R2024b was utilized to model, simulate, and analyze the power flow in both the pico-grid and nano-grid under different operating conditions.

Enhancing microgrid renewable energy integration at SEKEM farm

Enhancing microgrid renewable energy integration at SEKEM farm

The role of hybrid hydrogen-battery storage in a grid-connected renewable energy microgrid considering time-of-use electricity tariffs

The role of hybrid hydrogen-battery storage in a grid-connected renewable energy microgrid considering time-of-use electricity tariffs

Feasibility of renewable energy microgrids with vehicle-to-grid technology for smart villages: A case study from India

Feasibility of renewable energy microgrids with vehicle-to-grid technology for smart villages: A case study from India

Efficient voltage control strategy: observability design for multistage DC–DC buck converter

This paper emphasizes the significance of implementing an effective control system to enhance the performance of a three-stage DC–DC buck converter (TDDC). Herein, we present the development of an observer controller (OC) for TDDC, where average modeling of the DC–DC converter was employed alongside an observer algorithm for the OC. The primary focus is on the adoption of an observation topology aimed at enhancing system responsiveness under various conditions, including variable input voltages, reference voltage changes, load fluctuations, integration with photovoltaics, and battery charging. This approach ensures improved stability and performance, addressing the dynamic challenges inherent in such systems. A comparative analysis was conducted on two distinct control topologies for the proposed TDDC system, namely proportional–integral (PI) and advanced OC. Simulink software was used to model and simulate the proposed system. The results demonstrate lower rising and settling times of the TDDC for the OC and PI implementations, respectively. Additionally, the system with the OC eliminates 20% of the overshoot, while the system with OC minimizes the output voltage oscillations from 13% to 2% compared to the PI system. The OC was integrated into the TDDC to enhance system stability and improve the control loops, particularly the third loop. These improvements make the TDDC with OC suitable for application to renewable energy systems, microgrids, telecommunication networks, and electric vehicles, where precise control and stability are essential.

Short‐term energy forecasting using deep neural networks: Prospects and challenges

AbstractThis study presents an in‐depth overview of deep neural networks (DNN) and their hybrid applications for short‐term energy forecasting (STEF). It examines DNN‐based STEF from three perspectives: basics, challenges, and prospects. The study compares recent literature using metrics like mean absolute error (MAE), mean average percentage error (MAPE), and root mean square error (RMSE). Findings indicate that combining automated data‐driven models with enhanced DNNs effectively addresses forecasting challenges. It also highlights the role of DNNs in integrating energy prosumers, renewable energy systems, microgrids, big data, and smart grids to improve STEF.

Optimal rule-based energy management and sizing of a grid-connected renewable energy microgrid with hybrid storage using Levy Flight Algorithm

Optimal rule-based energy management and sizing of a grid-connected renewable energy microgrid with hybrid storage using Levy Flight Algorithm

A multi-objective robust dispatch strategy for renewable energy microgrids considering multiple uncertainties

A multi-objective robust dispatch strategy for renewable energy microgrids considering multiple uncertainties

Capacity planning of storage batteries for remote island microgrids with physical energy storage with CO2 phase changes

Capacity planning of storage batteries for remote island microgrids with physical energy storage with CO2 phase changes

Energy management of hybrid AC/DC microgrid considering incentive‐based demand response program

AbstractIncreasing the use of renewable energy in microgrids (MGs) offers environmental and economic benefits. However, the unpredictable and intermittent nature of available resources poses challenges for optimal MG scheduling. Hybrid AC–DC microgrids provide a solution, seamlessly integrating renewables while reducing energy losses and improving power grid reliability. Additionally, incentive‐based demand response programs promote flexible energy consumption, further mitigating the variability of renewable generation and enhancing grid stability. This paper investigates the challenges and potential of high renewable penetration in hybrid AC–DC MGs, analysing the role of demand response programs in system optimization. The microgrid's energy management is modelled using MILP, while a Stackelberg game represents the demand response program. These models are integrated to optimize energy management and demand response jointly. Simulations demonstrate the cost‐saving benefits of this integrated framework, achieved through coordinated flexible resource scheduling and incentive‐based demand response programming.

The Practical Impact of Price-Based Demand-Side Management for Occupants of an Office Building Connected to a Renewable Energy Microgrid

This paper examined the practical impact of price-based demand-side management (DSM) for occupants of an office building connected to a renewable energy microgrid. There has been an absence of studies that have analyzed occupant reactions, in terms of perceived practicality, regarding the implementation of DSM in conjunction with factors including renewable energy generation, load shifting and energy costs. An increased understanding of the practicality of DSM will support future improvements in building energy efficiency and sustainability. Ten occupants of the National Build Energy Retrofit Test-bed (NBERT) were selected as a case study. The electricity consumption pattern of the NBERT occupants was derived over a period of two years. Five unique DSM schedules were developed for each of the NBERT occupants, and a survey was carried out to investigate the practicality of these DSM schedules. A real-time electricity pricing tariff, electricity CO2 intensity, three feed-in tariffs and two microgrid control methods were evaluated to assess the practicality of each DSM schedule on the ten NBERT occupants. The results showed that the incorporation of onsite renewable energy generation with price-based DSM had a positive impact (r = 0.69–0.75) on occupant practicality. Onsite renewable energy generation was able to offset the demand for expensive electricity from the grid during peak hours, which aligned with the occupants’ typical work schedules. However, the introduction of a feed-in tariff with a renewable energy microgrid made price-based DSM less practical (r = 0.15–0.64).

Real-Time Optimization of Ancillary Service Allocation in Renewable Energy Microgrids Using Virtual Load

The stability of global economies relies heavily on power systems (PS) that have sufficient operating reserves. When these reserves are insufficient, power systems become vulnerable to issues such as load shedding or complete blackouts. Maintaining grid stability becomes even more challenging with a high penetration of renewable energy sources (RES). However, RES, connected through power electronic devices, offer significant potential as ancillary service (AS) sources. Renewable energy-based microgrids (MG), which aggregate various RES resources and have substantial load control potential, further enhance the capability of AS provision from RES. The presence of diverse AS resources raises the question of how to dispatch ancillary service signals optimally to all resources. Most of the previous research work related to AS allocation relied on single-bus MG models. This paper proposes a detailed MG model for the optimal dispatching of ASs among the resources using Virtual Load, along with an optimization procedure to achieve the best results. The model incorporates voltage profiles and power losses for AS dispatching, and a comparative analysis is conducted to quantify the significance of grid modeling. The model and proposed procedure are tested using the CIGRE microgrid benchmark model. The results indicate that detailed modeling of MG can impact the results by 11%, compared to single-bus modeling, which qualifies detailed MG modeling for all future research work and shows the impact that modeling can have on technical and economic indicators of MG operation.

Analysis and Design of Frequency Regulation Controllers with Considering Communication Delays and Environmental Effects of Renewable Energy Microgrids

Analysis and Design of Frequency Regulation Controllers with Considering Communication Delays and Environmental Effects of Renewable Energy Microgrids

Policy and regulatory framework supporting renewable energy microgrids and energy storage systems

Policy and regulatory framework supporting renewable energy microgrids and energy storage systems

Hybrid energy-based electric vehicles charging station integrated with INVELOX wind turbine: A case study of Kermanshah

Hybrid energy-based electric vehicles charging station integrated with INVELOX wind turbine: A case study of Kermanshah

Integration of Renewable Energy in Microgrids and Smart Grids in Deregulated Power Systems: A Comparative Exploration

In recent years, the importance of deregulated power systems has grown significantly, resulting in positive effects on stability, reliability, innovation, and investment in new energy grid technology. The competitive landscape among energy providers and distributors has empowered consumers to not only save money on their energy bills but also incorporate sustainable energy sources into the grid. To efficiently manage electricity distribution, deregulated power systems must include a smart grid and microgrid (MG). Herein, the potential for sustainable expansion of these systems, as well as their economic and environmental implications, are examined. A comprehensive grid system that integrates smart grids and MGs can offer a complete solution, catering to the evolving energy needs of communities and businesses. The advantages of establishing such a system, including improved grid stability, reliability, and increased utilization of renewable energy sources (RES), are highlighted. Furthermore, the integration of MGs and smart grids enhances the management of distributed generation, allowing power companies to optimize system operations for profitability and efficiency. By following these suggestions, businesses and stakeholders in the power sector can enhance the efficiency and responsibility of their systems, resulting in benefits for both the economy and the environment.

Digital twin technology for renewable energy microgrids

Digital twin technology for renewable energy microgrids

Leveraging media for demand control in an optimal network of renewable microgrids with hydrogen facilities in South Korea

Abstract In pursuit of a sustainable 2030 strategy in the Republic of Korea, this study addresses the oversight in recent optimal renewable energy microgrid designs, which, despite encompassing all feasible renewable sources, neglected the pivotal role of hydrogen as an energy carrier. This research explores the feasibility of reprogramming media platforms to dynamically shape energy consumption during peak intervals. It further proposes the retrofitting of microgrids with industrial hydrogen production and storage facilities, aligning with controlled electricity demand. A comprehensive social survey investigates the impact of media content on energy-conscious behaviour and cooperation, specifically targeting energy savings during peak hours. Utilizing a probabilistic model, the study quantifies responses from the surveyed sample and decomposes the energy demand time series to reveal three new consumption patterns: demand reduction by lowering residential electricity consumption at peak intervals without shifts, intense demand shifting by redistributing electricity consumption from peaks to valleys without human intervention, and moderate demand shifting achieved through cooperation with consumers. With these novel energy demand patterns in hand, the study optimally designs renewable microgrids in 17 sites in South Korea, comparing two strategies: Plan A, involving electrolysis-based hydrogen production and storage tanks, and Plan B, which excludes hydrogen facilities. Comparative results demonstrate that media content contributes to a 10.28% and 16.11% reduction in peak electricity consumption, with and without human intervention, respectively. In Plan B, a demand cut saves 937.3 MWh/yr, resulting in a 12.88% reduction in the levelized costs of electricity (LCOE) and a 4.67% reduction in net present costs (NPC) of optimal renewable microgrids in Korea. Conversely, in Plan A, intense demand reduction exhibits superior performance, leading to $981K less NPC, 1,046 MWh/yr less excess electricity, and a 3.76% smaller LCOE. The study recommends the implementation of smart gadgets to control residential electricity consumption, producing industrial hydrogen at Korean sites based on consumer attention and agreement with specific media content. However, it underscores the importance of studying the socio-psychological effects of this plan in future research.