Local Grid Research Articles

Progressive-Collapse Mechanism of Suspended-Dome Structures Subjected to Sudden Cable Rupture

This article proposes an progressive-collapse mechanism for suspended-dome structures subjected to cable rupture, based on experimental and finite element results. The anti-collapse mechanism can be succinctly described as a node-buckling mechanism: the potential for node buckling in a local arch-like spatial grid centered on unsupported node directly determines whether progressive collapse will occur in the overall structure. Subsequently, based on this anti-collapse mechanism, a node-buckling model is further proposed, and the factors affecting the anti-collapse bearing capacity of suspended domes are quantitatively expressed through the construction of a resistance index, which can be used to judge the sensitivity of hoop cables. Further, using Ribbed and Lamella suspended domes as examples, extensive calculations demonstrate the applicability and accuracy of the node-buckling model and resistance index to other types of suspended domes. Finally, the resistance index is used to analyze two important but easily overlooked factors that affect the anti-collapse bearing capacity of suspended domes. Initial geometric imperfections result in a rise–span ratio too small for the local arch-like spatial grid, while the lack of lateral stiffness at the supports will weaken the axial stiffness of the outermost radial or diagonal members. Both of these factors significantly reduce the stability of the local arch-like spatial grid, making it more likely to trigger progressive collapse in suspended-dome structures.

Fault Control Strategy of Grid‐Forming Converter Considering the Voltage Support of Faulty Phase

AbstractThe grid‐forming converter (GFC) is used to regulate the voltage and frequency of a local grid. However, due to the limited current capacity, the GFC must actively modify its control strategy when a serious external fault occurs, thus to avoid the possible damage caused by overcurrent. This paper proposes a novel voltage reference generation method for GFC based on the external equivalent impedance magnitude (EEIM), which has the following merits: (i) the faulty phase currents and the non‐faulty phase voltage can be controlled within their operational limits. (ii) The voltage reference unbalance factor (VRUF) of the GFC can be adjusted flexibly if necessary. Then, in order to achieve the optimal support effect for the faulty phase voltages, a two‐stage GFC fault control strategy is proposed in this paper. In the first stage, the fault type is judged by computing and comparing the EEIM of each phase. In the second stage, the voltage reference mode is determined according to the fault type, and the VRUF is adjusted to its optimum value through a search algorithm. Simulation results based on Matlab/Simulink verify the effectiveness of the proposed GFC fault control strategy in terms of current limiting and faulty phase voltage support. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Optimal component sizing and operational optimisation of a mobile energy system for decentralised electricity supply

The ambitious legislation driven by climate change, makes it necessary to focus more strongly on previously untapped greenhouse gas saving potentials, such as the mobile supply of renewable electrical energy which can create geographical flexibility. Consumers are supplied with electrical energy by the mobile energy system, whereby the energy can potentially come from the photovoltaic modules (PV), the diesel generator (DG), the fuel cell (FC) or the battery (EES) contained in the overall system. Exemplary customers of the service can be, e.g., road construction sites, festivals or other temporary events or also local distribution grid balancing applications. Given exogenous PV production and load profiles, this study determines the cost-optimal sizing of the system components (FC, DG, and EES) while deriving the optimal operating strategy for the overall system using mixed integer linear programming (MILP). In addition to investment and fuel costs, emission costs are integrated, which primarily occur in the context of DG operation. The model is implemented in Python in the optimisation environment Pyomo and solved by the Gurobi solver. The simulation is based on three scenarios for different combinations of PV production and load profiles as well as various hydrogen and emission price scenarios. It turns out, that the optimal sizes of the FC and the DG are between 0.5 and 2 kW for 60% and 0% demand coverage through PV respectively. For the battery, an optimal size between 1 and 4.8 kWh can be derived analogously.

Microclimate Analysis of the High-Impact Weather for the Power Grid Operation in the Jibei Region of China

High-impact weather affects the safety and economic operation of power systems. In this study, to provide regional microclimate of high-impact weather for the local power grid system in the northern Heibei province (known as the Jibei region in China), ERA5-Land global reanalysis data during 1981–2020 with a 0.1° grid size (about 9 km) are adopted to analyze the climate statistics and changes of the disastrous weather that affects the power grids. The results show that there have been significant climate changes in the region, including a temperature increase of about 1 °C, evident humidity and precipitation reductions, for the Jibei region and the six sub-regions that concentrated with wind and solar energy development in the 40 years. Due to the differences in terrain, the climate changes differ significantly among the six renewable energy development regions. The main types of high-impact weather that affect the power grid in the region are heavy fog and icing events, followed by cold waves, snowstorms, and rainstorms. In general, with climate changes in the last several decades, the weather disasters in Jibei region have become more frequent. Since most high-impact weather events have a small scale, it is necessary to simulate the weather processes with high-resolution models to accurately quantify the characteristics of the weather processes that affect the power grid. Therefore, a refined regional meteorological model (with grid size of 2 km) based on four-dimensional data assimilation (JB-FDDA) is established for the Jibei region. With one year of model reanalysis data, we found that JB-FDDA can significantly improve the accuracy of the local meteorological fields, and properly depicted the details of severe weather that affect the power grid operation. This study provide an analytical approach for regional electricity meteorological disasters by using reanalysis data.

Trends in Locally Balanced Energy Systems without the Use of Fossil Fuels: A Review

In recent years, the idea of the operation of energy systems (power systems, heating systems) has changed significantly. This paper is an overview of locally balanced energy systems without the use of fossil fuels. The paper justifies the concept of local energy balancing in a new energy system that does not use fossil fuels (coal, natural gas, and crude oil), based on European Union guidelines and formal documents as well as the literature on the subject. In this context, the issue of local energy self-sufficiency, utilizing renewable energy sources, as well as the concept of local smart grids based on innovative market mechanisms are raised. Attention is also paid to technical issues with regard to locally balanced energy systems, in particular photovoltaic sources and energy storage. Challenges related to the use of electrical protection in networks with many sources of energy are described. In such networks, the power flow is not in one direction only. Moreover, the selection of protections is problematic due to the distribution of short-circuit currents. Additionally, earth fault currents in such networks may be distorted, and this negatively affects the operation of residual current devices. The basic nomenclature describing locally balanced systems has been sorted out as well. Finally, possible future research paths in the field of creating locally balanced systems without the use of fossil fuels are presented.

Analysis of Dynamic Capacity Increase Transmission Line Carrying Capacity under Temperature and Electromagnetic Field

This article mainly introduces that, as the proportion of renewable energy to total consumed energy increases further, with the large-scale development and construction of new energy, the local power grid may face the problem of conflicting consumption in the future, and the original transmission lines will no longer meet the power demand. For this reason, dynamic capacity increase technology is used to calculate the load capacity in real-time. Through simulation analysis under temperature and electromagnetic fields to ensure that the conductor has sufficient safety while increasing the load capacity, clear data results are obtained based on the analysis.

Boosted fluctuation responses in power grids with active voltage dynamics

Secure electric energy supply and thus stable operation of power grids fundamentally relies on their capability to cope with fluctuations. Here, we study how active voltage dynamics impacts the collective response dynamics of networked power grids. We find that the systems driven by ongoing fluctuating inputs exhibit a bulk, a resonance, and a localized grid frequency response regime, as for static voltages. However, active voltage dynamics generically weakens the degree of localization in the grid, thereby intensifying and spatially extending the high-frequency responses. An analytic approximation scheme that takes into account shortest signal propagation paths among the voltage, phase angle and frequency variables result in an asymptotic lowest-order expansion that helps understanding the boosted high-frequency responses. These results moreover offer a generic tool to systematically investigate fluctuation response patterns in power grid models with and without active voltage dynamics.

Short-term operation of cascade hydropower system sharing flexibility via high voltage direct current lines for multiple grids peak shaving

The escalating pressure for peak shaving presents a significant challenge for the power grid's operation, particularly with the rapid growth of renewable energies. Huge cascade hydropower stations (CHS) send power to the local power grid and multiple power grids via long-distance high voltage direct current (HVDC) transmission lines, how to share hydropower flexibility for multiple power grids in peak shaving while considering constraints of hydropower and HVDC lines challenges power dispatching management. This study proposed a multiple power grids peak shaving model of cascade hydropower stations with HVDC sharing flexibility for receiving power grids. Firstly, the objective of minimizing the peak-valley difference of multiple power grids is adopted. The model then takes into account the operation constraints of CHSs and HVDC tie-lines to share hydropower flexibility. Finally, the model is transformed into a Mixed-Integer Linear Programming problem through piecewise linearization. The case studies of practical examples in southwest China show that the proposed model reduces peak-valley differences by 23.3%, 46.9%, 99.1% and 19.6%, 34.3%, 99.5% for three receiving power grids in two typical days by sharing hydropower flexibility. Moreover, adjusting the HVDC daily power regulation times and electricity deviation tolerance helps coordinate power grids to improve their peak shaving performance.

ALFRED reactor and hybrid systems: A test case

Future electricity generation will likely rely on renewable energy sources with consequent power intermittency and grid instability issues that will need to be compensated for. In this work, a model of a Generation IV small modular reactor has been developed in order to study its capabilities as a grid stabilizer. The plant model has been developed in Dymola and exported in the Simulink environment for the control strategy. The hybrid system considered couples a lead-cooled fast reactor to a desalination plant, an energy storage system, renewable energy farms, a variable electrical load, a local grid, and an external interconnected grid. Different desalination plants have been considered. Reverse osmosis has proven to be the most suitable option when coupled with energy production systems. Different configurations of the hybrid system have been considered showing a higher degree of load-following capabilities for the nuclear plant studied.

A genuine V2V market mechanism aiming for maximum revenue of each EV owner based on non-cooperative game model

As the number of electric vehicles (EVs) surges, EVs are expected to supply auxiliary services for power grid through the vehicle-to-grid (V2G) operation. Specifically, vehicle-to-vehicle (V2V), as a beneficial supplement of V2G, has received increasing attention owing to the capability for flexible EVs deployment and profitable individual interaction. In this paper, a genuine V2V market mechanism aiming for maximum revenue of each EV owner is proposed to construct a distributed electricity market. It reveals the dominance of EV owners from the perspective of market and allows the trade among EV owners in local distribution grid with charging points such as charging stations and auto parks. To this end, the implementation of V2V market mechanism is analyzed in detail, including the electricity price, the process and the integration with the internet of smart charging points (ISCP), a cyber-physical architecture. Then, EVs’ energy dispatching is formulated via the non-cooperative game model, in which each EV owner anticipates maximizing individual revenue by choosing feasible strategies. The existence and uniqueness of Nash Equilibrium (NE) in a non-cooperative game is proved by means of variation inequality (VI) theory. Finally, the ISCP-based optimal algorithm is developed to solve the NE efficiently, thereby maximizing reward of each EV owner. Comprehensive case studies show that the proposed V2V market mechanism can implement distributed dealing among EV owners with reducing individual charging cost and regional load variance effectively. Specially, the costs of EV1, EV8 and EV9 decrease by 31%, 36% and 34%, respectively. And V2V charging demonstrates much lower variance (10.5209) than regular charging (14.1124). Additionally, the convergence of the algorithm is also demonstrated, reaching the NE in less than 30 iterations for each EV.

Integration of Intelligent Neighbourhood Grids to the German Distribution Grid: A Perspective

Renewable energy sources generated locally are becoming increasingly popular in order to achieve carbon neutrality in the near future. Some of these sources are being used in neighbourhood (local, or energy communities) grids to achieve high levels of self-sufficiency. However, the objectives of the local grid and the distribution grid to which it is connected are different and can sometimes conflict with each other. Although the distribution grid allows access to all variable resources, in certain circumstances, such as when its infrastructure is overloaded, redispatch measures need to be implemented. The complexity and uncertainties associated with current and future energy systems make this a challenging bi-level multi-criteria optimisation problem, with the distribution grid representing the upper level and the neighbourhood grid representing the lower level. Solving these problems numerically is not an easy task. However, there are new opportunities to solve these problems with less computational costs if we decompose the flexibility in the lower lever. Therefore, this paper presents a mathematical approach to optimise grid management systems by aggregating flexibility from neighbourhood grids. This mathematical approach can be implemented with centralised or decentralised algorithms to solve congestion problems in distribution grids.

Advancing Simultaneous Localization and Mapping with Multi-Sensor Fusion and Point Cloud De-Distortion

This study addresses the challenges associated with incomplete or missing information in obstacle detection methods that employ a single sensor. Additionally, it tackles the issue of motion distortion in LiDAR point cloud data during synchronization and mapping in complex environments. The research introduces two significant contributions. Firstly, a novel obstacle detection method, named the point-map fusion (PMF) algorithm, was proposed. This method integrates point cloud data from the LiDAR, camera, and odometer, along with local grid maps. The PMF algorithm consists of two components: the point-fusion (PF) algorithm, which combines LiDAR point cloud data and camera laser-like point cloud data through a point cloud library (PCL) format conversion and concatenation, and selects the most proximate point cloud to the quadruped robot dog as the valid data; and the map-fusion (MF) algorithm, which incorporates local grid maps acquired using the Gmapping and OctoMap algorithms, leveraging Bayesian estimation theory. The local grid maps obtained by the Gmapping and OctoMap algorithms are denoted as map A and map B, respectively. This sophisticated methodology enables seamless map fusion, which significantly enhances the precision and reliability of the approach. Secondly, a motion distortion removal (MDR) method for LiDAR point cloud data based on odometer readings was proposed. The MDR method utilizes legged odometer data for linear data interpolation of the original distorted LiDAR point cloud data, facilitating the determination of the corresponding pose of the quadruped robot dog. Subsequently, the LiDAR point cloud data are then transformed to the quadruped robot dog coordinate system, efficiently mitigating motion distortion. Experimental results demonstrated that the proposed PMF algorithm achieved a 50% improvement in success rate compared to using only LiDAR or the PF algorithm in isolation, while the MDR algorithm enhanced mapping accuracy by 45.9% when motion distortion was taken into account. The effectiveness of the proposed methods was confirmed through rigorous experimentation.

Research on anti-islanding detection technology strategy

In recent years, the conditions and environment of China's economic development have undergone or are about to undergo many major changes. At the same time, China's electricity consumption ranks the first in the world with a huge volume and a considerable annual net increment. It is necessary to dialectically understand the profound impact of the new normal of economic development on the growth of China's electricity demand. Faced with the ever-increasing power demand, the power industry is still heavy to ensure steady supply, and the proportion of power consumption will also gradually increase. The central position of power in the energy field is gradually promoted, and the power security guarantee has gradually become one of the core elements of the new energy security strategy: in the actual operation of the power grid, there will be some unstable operation, and the local power grid accident can easily expand into a large-scale blackout. This will not only threaten the daily consumption of electricity, but also affect the national economy to a certain extent. The proposed distributed generation system solves this problem, but it also brings new problems. The appearance of island effect brings more harm to power grid operation. Aiming at the harm of island effect, this paper puts forward the detection technology strategy of related island effect.

Novel applications of local optimization semi-Cartesian grid for the complex band structure analysis of phononic crystals

In this paper, we propose a finite element method based on the Floquet transform and local optimization semi-Cartesian grid to compute the complex band structure of phononic crystals. Floquet transform is applied to transform the elastic wave equation into a quadratic eigenvalue equation. Value-periodic test function independent of the interface is defined to derive the weak formulation. The local optimization semi-Cartesian grid is proposed to improve the quality of triangular elements near the interface. Our results are in good agreement with ones obtained by other mature methods, and the purely propagative mode coincides with the traditional band diagram. In addition to simple scatterer shapes such as circle or square, the proposed method is able to calculate the complex band structures of phononic crystals with complicated scatterer shapes. Numerical experiments demonstrated the effectiveness of this method in the computation of anisotropic inhomogeneous medium. The complex band structures under different lattice types, scatterer shapes, material properties, rotation angle and modes are obtained, and their effects on the width and number of band gaps are analyzed.

Raising the Resilience of Industrial Manufacturers through Implementing Natural Gas-Fired Distributed Energy Resource Systems with Demand Response

The use of relatively small-scale distributed electric power generation sources is one of the key focus areas in the development of global industry and regional power generation. By integrating distributed generation sources into their on-site energy infrastructure, industrial consumers gain new characteristics and possibilities as entities of the power system that do not only consume power, but in fact can flexibly generate and deliver electricity to local and even centralized grids. This type of entity is called a distributed energy resource system with demand response (Russian: ‘active energy complex’). The purpose of this study is to lay the methodological foundation for the use of distributed energy resource systems with demand response in industrial sites under existing gas and power market conditions and for ensuring the synchronization of parameters that is necessary for managing complex energy consumption. This article provides an empirical study of the principles of the natural gas pricing under the demand volatility of regional markets and the Russian Mercantile Exchange. The article outlines the key drivers, as identified by the authors, that impact gas consumption by a distributed energy resource system, including demand characteristics, limitations and capacity of the gas network and the mode of gas consumption by an industrial enterprise and its generator. Accounting for all of these factors is essential for effective management and proper operational adjustment of a distributed energy resource system with demand response. The result of the study is a proprietary model and a tool for the management of distributed energy resource systems in integration with the gas demand management, which analyze the internal and external parameters of the industrial entity’s operations and its distributed energy resource system, as well as factors existing in the integrated distributed energy system where the consumer is able to buy natural gas in various market segments. The proprietary tool of distributed energy resource system management is based on the centralized control system, which combines performance analytics, operational scheduling of production and the distributed energy resource system, price planning for the wholesale and retail power markets, regional gas markets and exchange, monitoring all elements of the system, and assessment of different active energy management scenarios under various external and internal conditions impacting production and energy demand. Our proprietary tool has been successfully tested in a typical industrial site and was reported to deliver a significant electricity and gas cost-saving effect, which amounted to an 18 percent reduction in the total energy costs of the company, or more than USD 2.6 million per year. The resulting saving effect can recoup the costs of investing in a distributed energy resource system, including construction and installation of the local grid and automation infrastructure, and can be obtained in any country of the world.

Feasibility analysis of solar PV system in presence of EV charging with transactive energy management for a community-based residential system

In this world, with enhancing environmental issues of greenhouses and fossil fuels-based systems in societies and assumptions of sustainable solutions includes Renewable Energy Technologies (RET) and Electric Vehicles (EV) are increased in the residential and commercial buildings. Moreover, Renewable Energy Resources (RES) have an exceptional milestone towards the world to supply energy from the energy market to the consumers without any scarcity and the EV charging facilities among the residential building is the most eminent research domain in the developing countries. This paper investigates the feasibility of solar energy for around 320 buildings include residential load with EV charging is considered for the selected location Vistara Residential Enclave at Madurai. Additionally, the optimal solution is performed using HOMER software for the proposed solar Photo Voltaic (PV), Battery Energy Storage System (BESS), grid extension, V2H process for increase the efficient energy management. Instead of, three scenarios are considered for analyse the technical, economic and environmental basis. Moreover, in the first one, off-grid/battery support system for only residential load using solar energy. Then, the second scenario is evaluated with on-grid/battery backup system by solar PV for household loads only. Finally, in the third scenario, on-grid/battery system for residential load as well as EV charging with considered V2H performance. Meanwhile, the multiple houses are confined to a residential site in the consideration of overall load system as well as divided into five zones. Moreover, the following these three scenarios cost and electrical parameters are predicted as with and without Transactive Energy Management System (TEMS) to overcome the peak load challenges. Therefore, the consequences of this study proposed that 36.90 % of Net Present Cost (NPC) is maximized and 51.87 % reduced Operating and Maintenance cost (O&M) between presence and absence of TEMS shows that overall system load with TEMS towards the localized grid is the best effective reliable system in an effective manner than five divided zones without TEMS.

Adaptive Control Strategy for Stationary Electric Battery Storage Systems with Reliable Peak Load Limitation at Maximum Self-Consumption of Locally Generated Energy

Nowadays, stationary battery storage systems are generally used to optimize the self-consumption of electricity generated locally or to limit the peak load of the local grid connection. Self-consumption optimization aims to achieve economic benefits by using more of the self-generated electricity within the local grid. Batteries used for the optimization of self-consumption tend to present low states of charge and, therefore, normally do not contribute to peak load limitation. Peak load limitation is used to minimize the grid connection power to enable more cost-efficient grid connections. However, this function can only be achieved year-round if there is sufficient surplus electricity production or if the battery can be charged from the grid. In the latter case, the batteries are often fully charged and do not significantly optimize the self-consumption. This study presents a new operating strategy that combines all the advantages of the previous operating modes with none of the disadvantages. This can be accomplished by combining the operation modes depending on the particular situation, together with a variable battery charging process. Furthermore, a simulation-based optimization procedure is introduced for the optimal configuration of the parameters. The potential of this operating strategy is demonstrated based on application examples. As a result, the operating strategy enables reliable peak load limitation all year round while simultaneously optimizing self-consumption. The operating strategy can easily be adapted to meet changing requirements such as the increasing charging power demands of electric vehicles. Thanks to a simple process based on common measured variables, the operating strategy can be integrated smoothly into practical applications.

GridNetOpt: Fast Full-Chip EM-Aware Power Grid Optimization Accelerated by Deep Neural Networks

This article presents a fast full-chip electromigration (EM) aware IR drop constrained optimization framework, named GridNetOpt, for on-chip power grid networks accelerated by deep neural networks (DNN). Compared to the existing linear programming-based methods, the new method employs more flexible conjugate gradient-based optimization to size the wire width of the power grids. To mitigate the high cost of sensitivity calculation of the adjoint network using full-chip IR drop analysis at every iteration step, the sensitivity is computed via a trained conditional generative adversarial network (CGAN). The new method exploits the differentiable characteristics of DNNs for fast sensitivity computation. The sensitivity, which is the node voltage with respect to wire resistance, will guide the search direction during the optimization process. In order to consider more accurate EM failure effects, the training data is obtained from the power grids under different wire widths and current loads analyzed by a state-of-the-art full-chip multi-physics-based coupled EM-IR drop analysis tool. This is in contrast with the existing linear programming-based methods, in which only immortal wires or wires with non-zero resistance can be dealt with. Numerical results on a number of synthesized power grid benchmarks from ARM Cortex-M0 processor designs show that the proposed GridNetOpt can lead to at least an order of magnitude speedup over the conjugate gradient-based method using the traditional adjoint network method. Compared to the previous localized power grid fixing work with GridNet, GridNetOpt leads to smaller area overhead for all the benchmarks we tested. It can also reduce IR drops for power grid circuits with immortal wires, which is not possible with the localized GridNet method.

COMPARATIVE ANALYSIS OF THE IMPLEMENTATION OF BUSINESS MODELS OF PROSUMERS WITH RENEWABLE ENERGY SOURCES

The review of current models of renewable energy promoters in Ukraine focuses on consumer groups that use renewable energy sources, new business models and modern approaches to market regulation, which further affect the modernization of infrastructure in accordance with the requirements of the European Union and energy policy. The author analyzes the formation of tariff policy according to each business model and describes the impact of preferential tariffs in the functioning of the models. This article examines the impact of energy cooperatives and community energy communities, what value they bring to the transition to alternative energy sources, and how they can be developed through energy policy and regulatory frameworks. It has been shown that the management of energy cooperatives and communities during peak consumption periods can influence the balancing of the energy system. It has been found that business models of collective consumption in market relations expand the definition of self-consumption in many ways. The Tenant's Electricity business model involves some form of independent consumption of solar energy from photovoltaic installations in apartment buildings. The Private Grid or Microgrid model allows consumers and prosumers to experiment with different energy technologies that simultaneously maximize their own consumption and offer services to grid operators. It also shows a mechanism for covering electricity shortages through collective self-consumption, in which the local grid operator provides careful management of consumer meter data.
 The presented 15 business models of prosumerism allow us to explore the ways in which some models can be advantageous compared to others by avoiding various components in the formation of retail energy prices, and by generating new revenues through flexibility. The possibility of schemes with the ability to "aggregate" the flexibility of consumers and use the flexibility of many small energy systems to meet the large needs of power system operators is identified. Examples of business models for collective consumers that benefit from energy efficiency and decarbonization of other energy sources, such as heat and transport, are presented. The paper also considers possible business models of prosumerism and schemes for the provision of energy services between the owners of renewable generation and the distribution system operator, transmission system operator, and other market participants. It is proposed to solve the problem of expanding prosumerism by conducting a comparative analysis of business models.

AEM-electrolyzer based hydrogen integrated renewable energy system optimisation model for distributed communities

The development of sustainable and renewable energy technologies has received significant attention to realize Net-Zero CO2 equivalent emission goals and meet the growing energy demand. Hydrogen is a promising energy carrier that can facilitate the large-scale deployment of renewable energy sources and assist in the replacement of fossil fuels and to reduce the impact of global warming. The objective of this research is to present an advanced hydrogen-integrated renewable energy system model to meet the energy demand of a distributed community and produce green hydrogen from excess/curtailed renewable energy. The study employs an anion exchange membrane water electrolyzer (AEM) for producing hydrogen. An optimization model of the renewable energy system and a mathematical model of the electrolyzer are developed to achieve this objective. The model uses an energy maximisation approach and optimally combines wind system, biogas plant, and solar PV system to meet the residential and commercial load demands. To increase the system stability, the model is interconnected with the local grid station for energy exchange. Moreover, an uncertainty analysis is also performed to analyse the system response under random variation in load demand. The study results show that a significant amount of clean energy (15,025 MWh/year) is produced by the system at the lowest levelized cost of 0.084 €/kWh and a reduction of 6,078 tons of CO2 emission during the first year of operation is obtained. The electrolyzer produces 63 kg/hr of hydrogen, while the cell performance remains stable at 60 °C and the cell voltage reaches 2.019 V at 2.415 A/cm2 current density.