Integrated Battery and Hydrogen Energy Storage for Enhanced Grid Power Savings and Green Hydrogen Utilization

Abstract

This study explores the integration and optimization of battery energy storage systems (BESSs) and hydrogen energy storage systems (HESSs) within an energy management system (EMS), using Kangwon National University’s Samcheok campus as a case study. This research focuses on designing BESSs and HESSs with specific technical specifications, such as energy capacities and power ratings, and their integration into the EMS. By employing MATLAB-based simulations, this study analyzes energy dynamics, grid interactions, and load management strategies under various operational scenarios. Real-time data from the campus are utilized to examine energy consumption, renewable energy generation, grid power fluctuations, and pricing dynamics, providing key insights for system optimization. This study finds that a BESS manages energy fluctuations between 0.5 kWh and 3.7 kWh over a 24 h period, with battery power remaining close to 4 W for extended periods. Grid power fluctuates between −5 kW and 75 kW, while grid prices range from 75 to 120 USD/kWh, peaking at 111 USD/kWh. Hydrogen energy storage varies from 1 kWh to 8 kWh, with hydrogen power ranging from −40 kW to 40 kW. Load management keeps power stable at around 35 kW, and PV power integration peaks at 48 kW by the 10th h. The findings highlight that BESSs and HESSs effectively manage energy distribution and storage, improving system efficiency, reducing energy costs by approximately 15%, and enhancing grid stability by 20%. This study underscores the potential of BESSs and HESSs in stabilizing grid operations and integrating renewable energy. Future directions include advancements in storage technologies, enhanced EMS capabilities through artificial intelligence and machine learning, and the development of smart grid infrastructures. Policy recommendations stress the importance of regulatory support and stakeholder collaboration to drive innovation and scale deployment, ensuring a sustainable energy future.

1. Introduction

Modern power networks cannot function without energy storage systems (ESSs), which are vital for the effective control and use of electricity [1,2,3]. The main source of reliable power generation for traditional systems has been fossil fuels. Nonetheless, the importance of ESSs has increased because of the growing use of naturally intermittent renewable energy sources (RESs), such as wind and solar [4,5,6,7]. ESSs can capture extra energy produced during periods of high generation and release it during peak demand or low production, maintaining a consistent power supply [8,9,10]. The two primary forms of energy storage systems (ESSs) are hydrogen energy storage systems (HESSs), which store energy as hydrogen gas produced by electrolysis, and battery energy storage systems (BESSs), which store energy chemically [11,12,13,14,15].

An all-encompassing solution to the drawbacks of utilizing a single storage technology is provided by integrating various storage technologies, such as hydrogen and batteries. Batteries offer high efficiency and rapid response, making them ideal for short-term storage and grid balancing. However, they may not be cost-effective or technically optimal for large-scale, long-term storage [16,17,18]. In addition to being excellent for long-term energy storage, hydrogen storage has many other uses, including industrial processes and transportation. Combining these technologies allows for the strengths of each system to be utilized, enhancing overall grid flexibility, stability, and resilience. This integrated approach is crucial with the increasing use of renewable energy, where balancing supply and demand becomes more complex [19,20,21].

Improving grid power savings through the best possible utilization of combined battery and hydrogen storage systems is one of the main objectives of this research. Effective energy management can significantly reduce the dependence on peaking power plants, which are often costly and less environmentally friendly. It is possible to minimize demand peaks and hence lower the overall cost of generating and distributing electricity by making optimal use of stored energy. Additionally, integrating BESSs and HESSs can help minimize energy losses during transmission and distribution, further contributing to grid power savings. This study aims to show how the strategic integration and optimization of these storage technologies can lead to substantial economic benefits for utility providers and consumers.

This study aims to encourage the utilization of green hydrogen as an eco-friendly and sustainable energy source. Green hydrogen is an environmentally friendly substitute for conventional hydrogen manufacturing techniques that use fossil fuels. It is created through electrolysis with renewable energy. It is possible to develop a more adaptable and sustainable energy system by combining hydrogen storage with battery storage. This integration facilitates the energy sector’s decarbonization and opens up new uses for hydrogen, such as in industrial processes, transportation, and as a source of synthetic fuels. The purpose of this study is to demonstrate how integrated storage systems might help accelerate the shift to a low-carbon economy and promote the wider use of green hydrogen [22,23,24,25].

2. Battery and Hydrogen Energy Storage System

2.1. Battery Energy Storage Systems (BESSs)

Battery energy storage systems (BESSs) store electrical energy using a variety of forms and technologies. Lithium–ion batteries are the most widely used because of their high energy density, high efficiency, and falling costs, which have made them the market leaders [26,27,28]. Lead–acid batteries are also utilized due to their reliability and cost-effectiveness, despite having lower energy density and shorter lifespans. Nickel-based batteries such as nickel–cadmium and nickel–metal hydride offer good performance but are less popular due to higher costs and environmental concerns [29,30,31]. Emerging technologies like solid-state batteries and flow batteries promise advancements such as higher energy densities, longer lifespans, and improved safety, positioning them favorably for future applications. Each type of battery (

Table 1. Types and Technologies.

No	Type	Details
1	Lithium-ion Batteries	High efficiency, high energy density, and declining costs.
2	Lead–acid Batteries	Reliable, cost-effective, lower energy density, shorter lifespan.
3	Nickel-based Batteries	Higher expenses, environmental issues, and good performance (nickel–cadmium, nickel–metal hydride, etc.).
4	Solid-state Batteries	Higher energy density, longer lifespan, improved safety, emerging technology.
5	Flow Batteries	Scalable, long lifespan, emerging technology.

) offers distinct advantages tailored to specific requirements, like energy capacity, discharge rates, and operational longevity [32,33,34,35,36].

BESSs are essential for energy storage, load balancing, and grid stabilization in contemporary grid management (

Table 2. Applications in Grid Management.

No	Application	Details
1	Peak Shaving	Lessens reliance on peaking plants by storing excess energy during periods of low demand and releasing it during periods of peak demand.
2	Frequency Regulation	Quickly adjusts power levels to help maintain grid stability.
3	Renewable Energy Integration	Captures excess energy from solar and wind sources, ensuring a steady supply during low production periods.
4	Backup Power	Supplies a dependable energy source in the event of a grid failure, which is essential for remote and vital infrastructure.

). By storing excess energy during times of low demand and releasing it during peaks, they play a major role in peak shaving by lowering the need for expensive peaking power plants. Furthermore, BESSs are essential for frequency management since they can quickly modify power injectors to keep the grid stable. It is essential that they are able to include intermittent renewable energy sources like wind and solar. By storing surplus energy produced under ideal circumstances and supplying it during unfavorable ones, BESSs guarantee a steady supply of electricity. Furthermore, BESSs are crucial for remote locations and vital infrastructure since they provide a dependable backup power supply during grid disruptions [37,38,39,40,41,42].

Despite their manifold benefits, BESSs encounter challenges that hinder broader adoption. One significant obstacle is the initial high cost, particularly for lithium–ion batteries, which can be prohibitive for large-scale installations. However, ongoing advancements in manufacturing processes and economies of scale are progressively reducing these costs. Another challenge lies in battery lifespan and degradation over time, leading to diminished efficiency and capacity. Continuous research aims to enhance battery longevity and performance. Safety concerns such as thermal runaway and fire risks necessitate improved battery designs and management systems. Recent innovations such as solid-state batteries offer heightened safety and energy densities, while flow batteries provide scalable storage solutions with extended lifespans. These advancements are anticipated to address current challenges and propel (

Table 3. Current Challenges and Advancements.

No	Challenge/Advancement	Details
1	High Initial Costs	Especially significant for lithium–ion batteries, but costs are decreasing due to technological advancements and scale.
2	Limited Lifespan and Degradation	Continuous research is aimed at developing batteries with longer lifespans and improved performance.
3	Safety Concerns	Includes risks like thermal runaway and fires, which are being mitigated through better designs and management systems.
4	Solid-state Batteries	These promise enhanced safety, and higher energy density, and show significant potential for the future.
5	Flow Batteries	Known for scalability and long lifespans; this represents a promising advancement in energy storage.

) the future expansion of BESSs in grid management [43,44,45,46].

2.2. Hydrogen Energy Storage Systems (HESSs)

Hydrogen energy storage systems (HESSs) produce hydrogen using a variety of techniques, most notably electrolysis. In this process, water molecules (H₂O) are divided into hydrogen (H₂) and oxygen (O₂) using electricity. Electrolysis is a sustainable method of creating “green” hydrogen since it may make use of renewable electrical sources like solar or wind power. Steam methane reforming (SMR), a different process (

Table 4. Hydrogen Production Methods.

No	Production Method	Details
1	Electrolysis	Water molecules (H2O) are split into hydrogen (H2) and oxygen (O2) using electricity, which is often generated from renewable energy sources like solar and wind power.
2	Steam Methane Reforming (SMR)	Produces carbon dioxide (CO2) as a byproduct when hydrogen is extracted from natural gas; this process is less environmentally friendly than electrolysis.
3	Other Methods	Includes the less popular and effective thermochemical and biomass gasification methods for producing hydrogen on a big scale.

) that also produces hydrogen from natural gas, is less environmentally friendly than electrolysis since it releases carbon dioxide (CO₂) as a byproduct. Thermochemical reactions and biomass gasification are two more less-used techniques. The capacity of electrolysis to produce clean hydrogen makes it unique and compatible with initiatives to attain energy sustainability and lower carbon emissions [47,48,49,50,51,52].

Given its low density and flammability, hydrogen distribution and storage must be performed carefully. Solid-state storage, liquefaction, and compression are examples of storage techniques (

Table 5. Storage Method.

No	Methods	Details
1	Compression	Stores hydrogen gas at high pressures, requiring robust infrastructure but offering flexibility in deployment.
2	Liquefaction	At extremely low temperatures (−253 °C), it transforms hydrogen into liquid, allowing for larger storage densities but necessitating energy-intensive cooling.
3	Solid-state Storage	It absorbs hydrogen into materials like metal hydrides, providing safe storage and potential for high energy density.

). Compression is the process of compressing hydrogen gas at high pressures for storage and transit; it offers deployment flexibility but also requires a strong infrastructure. At extremely low temperatures (−253 °C), liquefaction lowers hydrogen to liquid form, allowing for increased storage densities but necessitating energy-intensive cooling. Solid-state storage, an emerging technology, involves absorbing hydrogen into materials like metal hydrides, offering safe storage and the potential for high energy density. Distribution typically occurs via pipelines or specialized tankers, though infrastructure challenges remain for widespread adoption [53,54,55,56,57].

Because of the adaptability of hydrogen as an energy carrier and its potential to decarbonize the industry, HESSs find a wide range of applications in various sectors. Hydrogen fuel cells provide a clean substitute for fossil fuels in stationary power and transportation by producing electricity and heat with only water vapor as waste. Compared to battery electric vehicles (BEVs), hydrogen fuel cell electric vehicles (FCEVs) have longer ranges and require less time for refueling. In the industrial sector, hydrogen is utilized in refining processes and as a feedstock for the production of compounds like ammonia. In order to improve grid stability, HESSs also help with grid balancing by storing excess renewable energy during off-peak hours and releasing it during peak demand [58,59,60,61,62].

The advantages of HESSs (

Table 6. Applications and Benefits.

No	Application/Benefit	Details
1	Energy Sector	Reduces dependency on fossil fuels by using hydrogen to power fuel cells, which produce only water vapor as a byproduct while producing heat and electricity.
2	Transportation	In comparison to battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs) have longer driving ranges and require less time for refueling.
3	Industry	Uses hydrogen as a raw resource for several refining processes and for the production of compounds like ammonia.

) include improving energy security, lowering reliance on imported fossil fuels, and permitting the integration of renewable energy by providing long-term storage solutions. Because of its high energy density per unit mass, hydrogen can be used in spaces that are constrained. Furthermore, by lowering greenhouse gas emissions, promoting the shift to a low-carbon economy, and enhancing urban air quality, HESSs support environmental sustainability. HESSs are positioned to be a key player in worldwide efforts toward sustainable energy systems as infrastructure and technology grow [63,64,65,66,67].

2.3. Integration of BESSs and HESSs

Combining hydrogen energy storage systems (HESSs) and battery energy storage systems (BESSs) is a smart move that will improve energy efficiency and sustainability in a number of industries. This integration capitalizes on the complementary strengths of both technologies to address individual limitations and optimize overall system performance [68,69].

One conceptual approach involves using BESSs for immediate energy storage and rapid response needs. BESSs are effective in providing instant power support and stabilizing fluctuations in electricity supply and demand. In contrast, HESSs excel in storing larger quantities of energy over longer durations. Combining these capabilities creates hybrid storage systems that offer improved flexibility, resilience, and efficiency in managing renewable energy integration and grid stability [70,71,72,73].

In a different framework (

Table 7. Conceptual Frameworks.

No	Conceptual Framework	Details
1	Hybrid Storage Systems	Combines hydrogen energy storage systems (HESSs) for long-term storage with battery energy storage systems (BESSs) for short-term energy storage and quick reaction. Provides improved resilience, efficiency, and flexibility in handling grid stability and the incorporation of renewable energy.
2	Renewable Energy Utilization	Utilizes surplus renewable energy to charge BESS and produce hydrogen through HESS via electrolysis during low-demand periods. Stored hydrogen is used in fuel cells for electricity generation during peak demand or other applications, optimizing renewable resource utilization and supporting decarbonization efforts.

), excess renewable energy is used to concurrently charge a BESS and make hydrogen by HESS electrolysis when demand is low. After storage, the hydrogen can be used in fuel cells to produce electricity during periods of high demand or for other purposes, encouraging the effective use of renewable resources and aiding in the process of decarbonization [74,75,76,77].

The feasibility and advantages of merging BESSs and HESSs are illustrated by a plethora of case studies and practical implementations. For example, hybrid systems have been implemented to stabilize grids and efficiently manage energy variations in areas where the use of intermittent renewable energy sources, such as solar and wind, is prevalent [78,79,80]. A pilot project integrates a BESS with HESS to optimize renewable energy utilization and grid stability. The BESS manages short-term fluctuations in renewable output, while excess renewable energy is stored as hydrogen through electrolysis. This stored hydrogen is later converted into electricity during peak demand or utilized as a fuel for hydrogen-powered vehicles, showcasing the versatility of integrated storage systems [81,82,83]. In industrial settings such as microgrids or remote applications, integrating BESSs and HESSs provides reliable energy solutions, reducing reliance on diesel generators or grid connections [84,85,86,87]. Global research projects (

Table 8. Case Studies and Existing Implementations.

No	Case Study/Implementation	Details	Author/ Year
1	Energy Storage Systems: Technologies and High-Power Applications	This article addresses the issues of efficiency, power quality, and dependability in DC/AC power systems and highlights the critical role that energy storage systems play in today’s energy infrastructure. They are essential to integrating renewable energy sources and preserving grid stability. These systems are also necessary for shipboard systems, electric vehicles, and airplanes. They improve overall dependability and efficiency by economically handling peak load demands. High-power storage technologies including flywheels, supercapacitors, and superconducting magnetic energy storage have been the focus of recent breakthroughs. These technologies are suited for applications that require quick charging and discharging due to their high power density and fast reaction. Multiple energy storage devices and hybrid energy storage systems provide greater resilience and flexibility, making them attractive for a variety of applications, including those with critical loads. This study examines current developments in high-power storage technology, such as lithium-ion batteries, which are renowned for having a high energy density. Moreover, it provides an overview of how hybrid energy storage devices are used in microgrids and in situations with pulse and critical loads. Power, energy, cost, life, and performance technologies are also covered in the research.	Aghmadi, A.; Mohammed, O.A./2024 [88]
2	Recent Advances in Hybrid Energy Storage System Integrated Renewable Power Generation: Configuration, Control, Applications, and Future Directions	This study examines the difficulties that arise from using renewable energy sources (RESs) more frequently and from their erratic power delivery, which affects electricity quality, stability, and reliability. Systems for storing energy (ESSs) are mentioned as a possible remedy for these problems. Although a number of ESS approaches have been put out to solve these issues, the cost, lifespan, power density, energy density, and dynamic response of individual systems are constrained, resulting in trade-offs that impact the overall performance of the system. Combining several energy storage systems (ESSs) to create hybrid energy storage systems (HESSs) has proven to be an efficient way to reduce these trade-offs. Recent research has emphasized the benefits of integrating several ESSs and developed and advocated for various HESS configurations across a range of applications. Although individual techniques have been extensively documented, there hasn’t been a thorough literature evaluation of HESS-integrated RES. Thus, the purpose of this study is to present a comprehensive overview and analysis of the importance and effects of HESSs in relation to sustainable development and renewable energy. It looks at the global trends and situations surrounding HESSs at the moment, contrasts the salient characteristics of various ESS technologies, and talks about the idea, structure, categorization, and in-depth comparisons of HESSs. Along with recent developments in control and optimization techniques related to RESs, the paper also examines the growing functions, advantages, and applications of HESSs, highlighting both positive and negative aspects. In conclusion, it delineates persistent obstacles and novel prospects towards attaining more effective, enduring, and ecologically conscious energy resolutions. The information provided is intended to stimulate more study and development of cutting-edge HESSs in order to maximize the performance of renewable energy sources in the future.	Atawi, I.E.; Al-Shetwi, A.Q.; Magableh, A.M.; Albalawi, O.H./2023 [89]
3	Optimal Capacity Configuration of Wind–Solar Hydrogen Storage Microgrid Based on IDW-PSO	This study discusses the difficulties caused by the unpredictable and sporadic character of new energy sources, which have an impact on the stability of system output power. The study suggests combining a hydrogen energy storage system with solar, wind, and hydrogen energy to lessen these problems. The objectives of this integration are to increase the use of renewable energy, encourage its consumption, and lower the rates at which solar and wind energy are being curtailed. By employing methodologies for charging and discharging storage batteries and hydrogen energy storage, the system maximizes operation cost efficiency, controls power variations, and handles power shortages. In order to set up the ideal combination of wind, solar, and hydrogen capacities, it creates a model for optimizing the capacity allocation of a wind-hydrogen microgrid system. For a wind-hydrogen storage microgrid, the study uses the particle swarm optimization method with dynamic adjustment of inertial weight (IDW-PSO) to find the best allocation scheme and guarantee effective energy storage capacity. With the use of Beijing microgrid system simulations, the efficacy of the suggested method is shown. The strategy improves economic efficiency, increases the system’s ability to consume renewable energy, lessens power fluctuations, lessens power shortages, and speeds up the system’s convergence speed, according to the results.	He, G.; Wang, Z.; Ma, H.; Zhou, X./2023 [90]
4	Energy Storage Systems for Photovoltaic and Wind Systems: A Review	In response to the growing need for low-carbon transportation, the article looks into energy storage methods for wind and photovoltaic systems. The importance of energy storage systems (ESSs) as vital parts of renewable energy systems has recently come to light. The system requirements, financial constraints, and performance attributes all play a role in the technology selection process. For renewable energy sources, ESSs come in a variety of forms. These include electrochemical storage, which includes batteries, hydrogen storage fuel cells, and flow batteries; mechanical storage, which includes flywheels, pumped hydroelectric energy storage (PHES), gravity energy storage (GES), compressed air energy storage (CAES), and supercapacitors; electrical storage, which includes supercapacitors, SMES, and thermal energy storage (TES); and hybrid or multi-storage systems, which combine multiple technologies (e.g., supercapacitors and thermal energy storage or batteries and pumped hydroelectric storage). With the help of these several ESS categories, excess energy from renewable sources may be efficiently stored and released, guaranteeing a steady and reliable supply of energy. Precise system requirements determine which storage technology is best for a given application in solar and wind systems. When choosing an ESS technology, it is critical to consider aspects like power and energy demands, efficiency, cost-effectiveness, scalability, and durability.	Rekioua, D./2023 [91]
5	Energy Storage Management of a Solar Photovoltaic–Biomass Hybrid Power System	The difficulties encountered in isolated locations where it is not feasible to economically extend the electrical grid beyond the maximum breakeven distance are covered in this study. It suggests a workable solution for these areas: an integrated autonomous sustainable energy system. The paper presents a brand-new multi-optimization power management and electrical energy evaluation system designed specifically for microgrid networks. This system interfaces with a hybrid configuration of energy sources, comprising the grid network, downdraft biomass generator, and solar photovoltaic arrays. It includes integrated dispatch, load-following, and cycle-charging algorithms as a control module. In addition, it integrates flywheels, iron flow, lithium, sodium sulfur, and hybrid energy storage technologies with thermal load controller-boiler systems. When combined, these components allow the microgrid to function effectively in off-grid, grid-connected, and island-capable modes, giving it the freedom to cut off from the main grid when necessary. An optimal multitask control technique is used to manage the storage units and modeled power generation sources through the use of the HOMER software application. This strategy reduces energy losses, guarantees efficient storage management, boosts overall system efficiency, and lengthens the microgrid’s operating life. In the end, this integrated energy system may be deployed in both rural and urban settings, providing sustainable energy solutions appropriate for a range of economic and environmental circumstances.	Akinte, O.O.; Plangklang, B.; Prasartkaew, B.; Aina, T.S./2023 [92]
6	Recent Advances in Energy Storage Systems for Renewable Source Grid Integration: A Comprehensive Review	The important goals of lowering greenhouse gas emissions and improving electric energy security are covered in this study. This study looks at the difficulties of incorporating renewable energy sources (RESs) that fluctuate, such as wind and photovoltaic (PV), into current power systems. This is a growing trend over the last ten years. These difficulties include preserving the grid’s ability to operate consistently and dependably in the face of problems with power quality, reactive power support, voltage stability, angular stability, generation uncertainty, and fault ride-through capability. Grid management is made more difficult by the fluctuation in power generation from renewable energy sources (RESs) caused by erratic weather, such as shifting wind and sunshine patterns. Energy storage systems (ESSs) are crucial to reducing these difficulties. When there is a surge in power generation, ESSs store extra energy and release it when needed to stabilize grid operations. This paper provides a comprehensive overview of energy storage systems, emphasizing their main grid integration applications, the various types of storage technologies available (electrochemical, mechanical, electrical, and hybrid systems), and the power converters required to run these technologies effectively. By addressing these issues, the article hopes to help researchers and power utilities choose the most practical and cost-effective energy storage options to improve grid stability and successfully incorporate renewable energy sources.	Worku, M.Y./2022 [93]
7	Optimal Integration of Hydrogen-Based Energy Storage Systems in Photovoltaic Microgrids: A Techno-Economic Assessment	This study looks into the viability and economics of deploying hydrogen-based microgrids using photovoltaic (PV) plants with low energy demand, especially on weekends, in places like public buildings and small- to medium-sized businesses. A model for a hydrogen-based microgrid was created by taking inspiration from Sardegna Ricerche’s Renewable Energy Facility in Italy, which combines a number of energy generation and storage technologies, including hydrogen storage. The model evaluates the microgrid’s expected performance under various load patterns and equipment sizes. An initial economic analysis was carried out to assess the microgrid’s cost-effectiveness. According to the results, the best design approach is to size the PV system 20% larger than the yearly energy consumption and the hydrogen generator 60% larger than the PV system’s nominal power capacity. This arrangement reaches a rate of about 80% self-sufficiency. Furthermore, the levelized cost of energy can be competitive with current Italian electricity prices without the need for public subsidies. This can be achieved together with a significant decrease in initial plant costs, which can range from 25% to 40%, contingent on the load profile.	Serra, F.; Lucariello, M.; Petrollese, M.; Cau, G./2020 [94]

) are still investigating and improving the combination of BESSs and HESSs. In order to optimize advantages across a range of environmental and operational situations, these efforts are concentrated on improving system efficiency, cutting costs, expanding storage capacity, and creating intelligent control techniques [87,88,89,90,91,92,93,94].

Integrating BESSs and HESSs offers a promising pathway toward achieving sustainable energy objectives by leveraging the synergies between battery and hydrogen technologies. Ongoing advancements and practical deployments underscore the potential of these integrated systems to enhance energy security, stabilize grids, and promote environmental sustainability globally.

2.4. BESS, HESS, and Other Energy Storage Systems

Battery energy storage systems (BESSs) have emerged as a promising technology for addressing challenges in modern power systems, particularly with the increasing integration of renewable energy sources. BESSs offer high efficiency, with round-trip efficiencies exceeding 90%, and rapid response times within milliseconds. These systems are highly scalable, suitable for applications ranging from residential to utility-scale installations. BESSs can mitigate issues associated with solar power generation, such as ramp rate control, frequency regulation, and voltage stability. They also enable energy time-shifting and output leveling, enhancing the economic viability of solar resources. BESSs are considered a key technology for demand-side management and grid flexibility [95,96,97]. Despite their numerous advantages, challenges remain in optimizing BESS deployment, including sizing, operational control, and environmental impact considerations [98].

Battery energy storage systems (BESSs) are crucial for integrating renewable energy sources and improving grid stability. While BESSs deployment is increasing globally, it falls short of projections for a net-zero scenario. BESSs face challenges such as capacity degradation, high initial costs, and environmental concerns regarding raw material extraction and disposal. Optimization of BESS sizing, scheduling, and degradation management is critical for system efficiency and cost-effectiveness. Safety issues, including fire hazards due to heat production, necessitate the development of thermal management systems and adherence to safety standards. Despite these challenges, BESSs remain a promising technology for grid stability, renewable energy integration, and sustainable power solutions. Ongoing research and technological advancements aim to address these issues and promote widespread BESS adoption [99,100,101,102].

Hybrid energy storage systems (HESSs) offer unique advantages for long-term energy storage and have potential applications beyond electricity generation, including in transportation and industrial processes [103]. These systems combine multiple storage technologies, typically pairing high energy density storage with high power storage capabilities. HESSs, particularly hydrogen-based systems, boast high energy density and the ability to store large amounts of energy for extended periods, making them potential replacements for fossil fuel-based energy generation. However, HESSs face challenges such as high costs, technical complexity, and safety concerns, especially regarding hydrogen’s flammability. Ongoing research aims to address these issues and improve system efficiency. HESS applications in photovoltaic power generation demonstrate benefits like improved power quality, flattened intermittence, and enhanced frequency and voltage regulation in microgrid operations [104,105].

Battery energy storage systems (BESSs) have evolved significantly, with various technologies available for different applications. Traditional lead–acid batteries, while reliable and cost-effective, generally have lower energy density, shorter lifespans, and lower efficiency compared to modern alternatives. Lithium–ion batteries (LIBs) have emerged as the current leading technology due to their decreasing costs and high performance, despite safety concerns. Other technologies like vanadium redox flow batteries (VRFBs) offer advantages such as longer lifespans, better high-temperature performance, and lower environmental impact. The selection of battery technology depends on specific application requirements, including peak shaving, load leveling, power reserve, renewable energy integration, and voltage and frequency regulation [106,107]. Ongoing research aims to improve battery efficiency, lower costs, and optimize energy storage for various built environment applications [108].

Mechanical energy storage systems, particularly pumped hydro storage (PHS) and flywheels, play crucial roles in grid stability and renewable energy integration. PHS offers large-scale storage capacity and long operational lifespans, while flywheels excel in high-power, short-duration applications [109]. Flywheels provide advantages such as high cycle life, long operational life, high round-trip efficiency, and low environmental impact [110]. They are suitable for load leveling, frequency regulation, and peak shaving in power systems [111]. PHS and compressed air energy storage (CAES) are preferred for long-duration storage, with PHS offering higher efficiency and CAES providing faster start-up. The choice of mechanical storage system depends on specific application requirements, with a series connection recommended when combining these systems with solar or wind energy to enhance stability and control [112].

In comparing BESSs, HESSs, and other energy storage systems, each offers unique advantages and challenges depending on the application. BESSs stand out for their high efficiency, rapid response times, and scalability, making them ideal for applications such as grid stabilization and renewable energy integration. However, challenges like capacity degradation, high costs, and safety concerns persist. On the other hand, HESSs, particularly hydrogen-based systems, excel in long-term energy storage and offer versatility across various sectors, though they face higher costs and technical complexity. Traditional battery technologies like lead–acid and mechanical systems such as pumped hydro and flywheels provide reliable, cost-effective solutions but are limited by lower energy density and specific geographical or application constraints. Ultimately, the choice of energy storage technology hinges on factors such as efficiency, cost, lifespan, and application requirements, with ongoing research aiming to optimize these technologies for a more resilient and sustainable energy future.

3. Methodology

3.1. System Design and Configuration

In order to create an integrated energy storage system, battery energy storage systems (BESSs) and hydrogen energy storage systems (HESSs) must be combined into a comprehensive framework. This process includes detailing the technical specifications of both BESSs and HESSs, as well as developing an integration architecture that ensures these systems function cohesively within the building’s energy grid. The architecture features advanced control systems equipped with sensors and communication protocols to optimize performance, manage efficient energy storage, facilitate smooth charge/discharge cycles for BESSs, and oversee effective hydrogen production and usage for HESSs. This integrated strategy aims to improve energy management and sustainability for the Engineering 5 Building (Building Number 120) at Kangwon National University (Figure 1):

• Technical Specifications for BESS: Details about the battery energy storage systems (BESSs) used in this research are provided according to their lifespan, energy density, capacity, and charge/discharge efficiency. Typically, lithium–ion batteries are chosen for their high energy density and efficiency. The technical specifications include nominal voltage, capacity (in kWh), maximum discharge rate, and cycle life. These specifications are essential to guarantee that the BESS can supply the energy needed for Kangwon National University’s Engineering 5 Building.
• Technical Specifications of HESS: The hydrogen energy storage systems (HESSs) are defined by their hydrogen production rate, storage capacity, electrolysis efficiency, and fuel cell performance. The system produces hydrogen via electrolysis, stores it, and later converts it back to electricity using fuel cells. The effectiveness of the electrolysis process, storage pressure, hydrogen storage capacity (in kg), and fuel cell power output are important parameters. The successful integration of HESS with the building’s energy management system depends on certain specifics.
• Integration Architecture and Control Systems: Integrating BESS and HESS involves a complex architecture that manages their interaction with the building’s energy grid. The control systems are designed to optimize energy storage and discharge cycles for BESS and manage hydrogen production and utilization for HESS. For real-time monitoring and control, the architecture consists of controllers, sensors, and communication protocols, guaranteeing a smooth integration and optimizing the advantages of both storage technologies.

3.2. Simulation and Modeling

The simulation and modeling phase utilizes sophisticated computational tools to replicate and assess the performance of the integrated BESS and HESS within the building’s energy infrastructure. This step is essential for predicting system behavior under various conditions and optimizing their design and operation. It involves selecting suitable software and tools, defining assumptions and parameters for realistic modeling, and creating different scenarios for analysis. The goal of the project is to simulate these scenarios in order to identify the most effective ways to integrate and manage the energy storage systems, improving the Engineering 5 Building at Kangwon National University’s sustainability and energy efficiency:

• Software and Tools Used: MATLAB software was employed for simulation and modeling due to its powerful computational capabilities and versatility in handling complex energy systems. It provides a robust platform for developing, testing, and validating models of BESS and HESS, allowing for detailed performance analysis and integration studies.
• Assumptions and Parameters: The simulation is based on several assumptions and parameters, including typical energy consumption patterns of the Engineering 5 Building, renewable energy generation profiles, and efficiency metrics for both BESS and HESS. These assumptions create realistic analysis scenarios, ensuring the results are applicable to actual operational conditions.
• Scenarios for Analysis: Various scenarios were analyzed to understand the integrated energy storage systems’ performance under different conditions. These scenarios include different levels of renewable energy availability, varying load demands, and operational strategies for energy storage and utilization. Simulating these scenarios helps identify optimal configurations and strategies for integrating BESS and HESS.

3.3. Data Collection and Analysis

In order to evaluate the operational performance of the combined BESS and HESS, the data collection and analysis part comprises obtaining and carefully examining relevant data. This phase commences with identifying credible data sources, encompassing real-time energy consumption logs, renewable energy generation metrics, and performance indicators from the storage systems. Subsequently, the collected data undergoes processing using diverse statistical and computational methodologies to ensure precision and consistency, facilitating comprehensive analysis. Finally, specific metrics are employed to gauge the efficacy of the energy storage systems, such as energy efficiency, cost-effectiveness, reduction in peak demand, and the percentage of renewable energy utilization. This meticulous analysis is instrumental in comprehending the implications and advantages of integrating BESS and HESS within the infrastructure of the Engineering 5 Building at Kangwon National University:

• Sources of Data: Data for this study were collected from multiple sources, including real-time energy consumption data from the Engineering 5 Building, renewable energy generation data, and performance data from the BESS and HESS. These sources provide the necessary information for accurately modeling and simulating the integrated energy storage systems.
• Data Processing Methods: Collected data were processed using various statistical and computational methods to ensure accuracy and reliability. This involves filtering, normalization, and interpolation to create a consistent dataset for simulation. MATLAB’s data processing capabilities are used to handle large datasets efficiently.
  • Data collection: Involved acquiring real-time (simulation) data from Kangwon National University’s Samcheok campus, focusing on energy consumption patterns, renewable energy generation, grid power fluctuations, and pricing dynamics. Sensors and monitoring devices were strategically placed across the campus to ensure comprehensive data capture. These devices recorded parameters such as electricity usage, solar power output, battery storage levels, and hydrogen production and consumption rates over a continuous 24 h period, capturing daily variations and interactions within the energy management system (EMS).
  • Data cleaning: These outliers were carefully examined to determine if they were errors or valid anomalies. Missing values were handled through imputation techniques or removed if they had negligible impact. Duplicate records were identified and eliminated to avoid skewing the analysis.
  • Data Analysis: Once cleaned, the data underwent thorough analysis using various statistical and computational tools, primarily utilizing MATLAB for simulation and modeling. The data were categorized according to the different components of the EMS, such as battery energy storage systems (BESSs), hydrogen energy storage systems (HESSs), grid power, and renewable energy sources.
    • Battery Energy and Power Analysis: Analyzed storage and discharge patterns throughout the day by calculating total energy stored and used at different times and examining power output to determine efficiency and peak usage times.
    • Grid Power and Price Analysis: Examined fluctuations in power supply and demand, analyzing the impact of external factors like market conditions and demand response strategies on grid stability and pricing dynamics.
    • Hydrogen Energy and Power Analysis: Investigated charging and discharging cycles of the HESS, analyzing power output fluctuations to determine the system’s capability to manage hydrogen production and consumption effectively.
    • Load Analysis: Analyzed variations in power demand throughout the day, identifying peak demand times and assessing the effectiveness of load management strategies in balancing supply and demand.
    • PV Power Integration Analysis: Explored the integration of photovoltaic (PV) power with other energy sources, examining interactions and synergies within the EMS to understand PV power’s contribution to overall energy sustainability and its balance with battery and hydrogen storage systems.
  • Data Visualization: To enhance understanding and interpretation, various visualization techniques were employed. Graphs and charts illustrated energy dynamics, power fluctuations, and pricing changes over the 24 h period. These visualizations provided clear and intuitive representations of the complex interactions within the EMS, facilitating the identification of patterns, trends, and anomalies.
• Metrics for Evaluation: The performance of the integrated BESS and HESS was evaluated using several metrics, such as energy efficiency, cost savings, peak demand reduction, and the proportion of renewable energy utilized. These measurements aid in evaluating the energy storage systems’ performance as well as their influence on the building’s energy management.

4. EMS Optimization

4.1. Battery Energy and Battery Power

Battery energy (Figure 2) demonstrates how battery energy varies over a 24 h period, with time ranging from 0 to 25 h for comprehensive data representation. The scale for battery energy spans from 0 to 8 × 10⁴ kW-h. Starting around 1.8 kW-h, the energy level decreases initially and reaches approximately 0.5 kW-h by the 13th h. Subsequently, it gradually increases to about 3.7 kW-h by the 24th h, reflecting fluctuations in energy storage and discharge throughout the day.

Figure 2 illustrates the variation in battery energy storage (in kW-h) over a 24 h period, showcasing the dynamics of the energy management system (EMS) in response to day–night cycles. The time axis spans from 0 to 24 h, with the vertical axis representing battery energy in increments of 10,410^4104 kW-h.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During this period, solar energy generation is typically at its peak, leading to an increase in battery energy storage. This is reflected in the graph, where a significant rise in battery energy is observed starting around the 10th h and continuing until approximately the 20th h.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): Energy consumption is generally higher during this period, with reduced or no solar energy input. The graph shows relatively stable or decreasing battery energy levels during these hours, indicating the discharge of stored energy to meet nighttime demand.

Figure 2 provides insights into how the EMS manages energy storage, ensuring that sufficient energy is stored during the day for use during nighttime, thereby stabilizing grid operations and enhancing overall system efficiency.

Battery power (Figure 3) illustrates the dynamics of battery power during the same timeframe, with a similar time scale and range as Figure 2. The scale for battery power ranges from 0 to 4 × 10⁴ W. Beginning around 1.9 W, the power quickly ramps up to 4 W within the first hour. Throughout the period, there are instances where power decreases intermittently to 0, 0.5 W, and 1 W but generally remains close to the upper limit of 4 W for extended periods until the 24th h. These fluctuations in battery power indicate adaptive adjustments by the EMS to optimize grid interactions and energy utilization.

Figure 3 shows the power output of the battery (in W) over a 24 h period, capturing the real-time fluctuations managed by the energy management system (EMS). The horizontal axis represents time from 0 to 24 h, while the vertical axis denotes power in increments of 10,410^4104 W.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During daylight hours, the battery power exhibits more frequent fluctuations, reflecting the dynamic charging and discharging processes driven by variable solar energy input and fluctuating demand. Around midday (10 to 15 h), the power output tends to stabilize, indicating periods of high solar generation and reduced need for rapid power adjustments.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): During the night, battery power fluctuates less frequently but still shows noticeable activity as stored energy is dispatched to meet the grid’s demand. These fluctuations likely correspond to load changes and the EMS’s efforts to maintain grid stability without solar input.

Figure 3 emphasizes the EMS’s role in balancing power supply and demand throughout the day, with distinct patterns of battery power fluctuation corresponding to day and night cycles. Understanding these fluctuations is crucial for optimizing battery performance and enhancing the overall efficiency of energy storage systems in managing grid operations.

These figures and their data provide valuable insights into how the EMS manages battery energy and power to meet grid demands effectively. Analyzing these parameters helps refine EMS strategies for maximizing energy efficiency, grid stability, and overall system performance.

4.2. Grid Power and Grid Price

Grid power (Figure 4) displays the variation in grid power over 24 h, with a time scale ranging from 0 to 25 h for comprehensive data representation. The power scale spans from −50 to 100 kW. Starting around 75 kW, the grid power fluctuates throughout the day, peaking at approximately 30 kW and occasionally reaching 75 kW again, before ending around −5 kW at the 24th h. This figure illustrates how grid power supply varies over time, influenced by demand fluctuations and operational adjustments within the power network.

Figure 4 illustrates the grid power variations (in kW) over a 24 h period, as managed by the energy management system (EMS). The horizontal axis indicates time from 0 to 24 h, while the vertical axis shows power in kilowatts (kW), ranging from −50 kW to 100 kW.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During the day, the grid power demonstrates significant fluctuations, with frequent shifts between positive and negative values. These variations are due to the integration of solar energy, which can cause sudden changes in the power supplied to the grid. The EMS works actively during this period to balance the grid by adjusting power levels to match the variable generation and demand.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): At night, the grid power continues to fluctuate but generally within a narrower range. The absence of solar energy input leads to more stable power management, although the EMS still responds to changes in load demand and other grid conditions.

Figure 4 highlights the dynamic nature of grid power management across a 24 h cycle, with distinct patterns corresponding to daylight and nighttime hours. Understanding these fluctuations is essential for optimizing EMS operations, improving grid stability, and ensuring efficient integration of renewable energy sources.

In the context of grid power, negative power values indicate instances where the power flow is reversed, meaning that power is being sent back to the grid instead of being drawn from it. This can happen in systems that incorporate renewable energy sources and energy storage systems, where surplus generated power is exported to the grid. In the described scenario, grid power varies between −50 kW and 100 kW over a 24 h period. Initially, the value is around 75 kW, suggesting that the system is drawing power from the grid. As the day progresses, the amount of power drawn from the grid fluctuates, peaking at approximately 30 kW and occasionally returning to 75 kW. The significant point is the ending value of around −5 kW at the 24th h, indicating that at this point, the system is exporting 5 kW of power back to the grid.

This reverse flow of power can occur for several reasons:

• Excess Renewable Energy Generation: During periods of high renewable energy production, such as peak sunlight hours for solar panels, the generated power may exceed the immediate consumption needs. The surplus power is then fed back into the grid.
• Optimal Energy Management: The energy management system (EMS) may be designed to export excess stored energy from battery energy storage systems (BESSs) or hydrogen energy storage systems (HESSs) when grid prices are high or to balance overall grid demand and supply.
• Demand Response Strategies: Negative power flow can also be part of demand response strategies, where the EMS decides to supply power to the grid at specific times to help stabilize grid operations or take advantage of favorable pricing conditions.

Negative power values in the grid power data reflect times when the system is not drawing power from the grid but instead contributing power to it. This capability is crucial for enhancing grid stability, optimizing energy costs, and making efficient use of renewable energy resources.

Grid price (Figure 5) shows the fluctuation in grid price over the same 24 h period, with a time scale and range matching Figure 4. The grid price scale ranges from 75 to 120 USD/kWh. Beginning at 91 USD/kWh at the eighth hour, the price increases to a peak of 111 USD/kWh around the twenty-second hour, then decreases back to 91 USD/kWh by the twenty-fourth hour, eventually reaching 75 USD/kWh. This figure reflects the dynamic nature of electricity pricing, which is influenced by market conditions, demand patterns, and supply factors throughout the day.

Figure 5 illustrates the variations in grid electricity prices (in USD/kWh) over a 24 h period, reflecting the pricing strategy managed by the energy market. The horizontal axis represents time from 0 to 24 h, while the vertical axis indicates the grid price in increments of USD 10/kWh.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During the daytime, the grid price shows an increase starting around 7:00 AM (7 h) and maintains higher values, peaking between 10:00 AM to 4:00 PM (10 to 16 h). This likely corresponds to increased demand for electricity during working hours, where businesses and households consume more energy, pushing prices higher. The price stabilizes after this period, indicating a balance between supply and demand.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): At night, the grid price drops back to a lower level after 6:00 PM (18 h), reflecting reduced electricity demand as residential and commercial activities decrease. The price remains stable and low throughout the night, aligning with typical lower energy consumption during these hours.

Figure 5 highlights the impact of daily demand cycles on electricity prices, with distinct price patterns emerging during day and night. Understanding these price fluctuations is critical for optimizing the operation of the energy management system (EMS), particularly in deciding when to draw energy from the grid or deploy stored energy to reduce costs.

These numbers offer vital information for examining the effects of price and power supply fluctuations on the battery energy storage systems (BESSs) and hydrogen energy storage systems (HESSs) inside the energy management system (EMS) and their optimization techniques. The development of efficient energy management plans with the goals of lowering expenses, boosting grid stability, and raising overall system efficiency is supported by this analysis.

4.3. Hydrogen Energy and Hydrogen Power

Hydrogen energy (Figure 6) uses a time scale of 0 to 25 h to show how hydrogen energy storage changes over a 24 h period. The hydrogen energy scale ranges from 0 to 8 × 10^4 kW-h. Initially, hydrogen energy starts at 4 kW-h and steadily decreases to 1 kW-h by the 10th h. It then increases back to 4 kW-h, drops again around the 16th h and rises sharply to 8 kW-h by the 18th h. After this peak, hydrogen energy decreases to 4.5 kW-h before increasing again to 8 kW-h at the 24th h. This figure illustrates the fluctuations in hydrogen energy storage, reflecting dynamic charging and discharging processes.

Figure 6 depicts the levels of stored hydrogen energy (in kW-h) over a 24 h period, capturing the variations influenced by the energy management system (EMS). The horizontal axis represents the time from 0 to 24 h, while the vertical axis denotes the stored hydrogen energy, with values in the range of 000 to 8×1048 \times 10^48×104 kW-h.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During the daytime, hydrogen energy levels show some fluctuations, with a notable increase starting around 2:00 PM (14 h). This increase indicates the EMS’s response to higher electricity prices or lower grid availability during peak hours, likely converting surplus energy into stored hydrogen. The fluctuations around midday suggest dynamic management of energy storage as the EMS balances production and consumption needs.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): At night, the stored hydrogen energy levels increase significantly, particularly after 6:00 PM (18 h). This rise may reflect the EMS’s strategy to store energy when grid prices are lower, and electricity demand is reduced. The gradual stabilization towards the end of the period suggests that the EMS has maximized storage capacity or reduced the conversion rate as energy needs diminish.

This Figure 6 emphasizes the EMS’s role in managing energy storage, with clear patterns of hydrogen energy fluctuation corresponding to day and night cycles. Understanding these variations is essential for optimizing the use of hydrogen storage in maintaining grid stability and ensuring efficient energy use.

Hydrogen power (Figure 7) shows the variation in hydrogen power output over the same 24 h period, with a time scale from 0 to 25 h. The power scale ranges from −40 to 40 kW. Throughout the day, the power level mostly stays at 40 kW, especially from the 12th to the 13th h, when it briefly drops to −40 kW before returning to 40 kW. This pattern continues until the 24th h. This figure highlights the rapid and significant fluctuations in hydrogen power output, indicating periods of high activity and the system’s capability to effectively manage hydrogen production and consumption.

Figure 7 shows the power output associated with hydrogen energy storage (in kW) over a 24 h period, highlighting the dynamic management by the energy management system (EMS). The horizontal axis represents time from 0 to 24 h, while the vertical axis denotes power output, ranging from −50 kW to 50 kW.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During the daytime, hydrogen power output displays frequent and rapid fluctuations between positive and negative values. These fluctuations indicate the EMS’s active role in balancing energy storage and release, driven by variable energy generation (like solar) and demand during daylight hours. The transitions between positive and negative values suggest alternating periods of hydrogen production (storing energy) and consumption (releasing energy), particularly in response to peak demand and grid price variations.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): At night, the hydrogen power output continues to fluctuate, although with somewhat reduced intensity compared to the daytime. These fluctuations reflect the EMS’s strategy to manage energy storage during periods of lower electricity demand. The EMS likely prioritizes releasing stored hydrogen energy to meet the grid’s needs when solar input is unavailable, while also possibly storing excess grid energy when prices are low.

Figure 7 underscores the EMS’s crucial role in managing hydrogen power to stabilize the grid, with distinct patterns of power fluctuation aligned with day and night cycles. Understanding these patterns is essential for optimizing hydrogen energy use and ensuring efficient grid operation throughout the day.

In the context of hydrogen power, negative power values represent periods when the hydrogen energy storage system (HESS) is using power rather than generating it. This typically happens during hydrogen production, where electricity is utilized for electrolysis to split water into hydrogen and oxygen. In the described scenario, hydrogen power ranges from −40 kW to 40 kW over a 24 h period. For the majority of the day, the power level is at 40 kW, indicating that the HESS is generating or discharging hydrogen power to meet energy needs. However, there is a brief period between the 12th and 13th h when the power level drops to −40 kW. This negative power value means that, during this time, the HESS is consuming 40 kW of power, likely for hydrogen production through electrolysis.

This pattern of fluctuating power levels highlights several key aspects of HESS operation:

• Dynamic Energy Management: The system can switch between consuming power for hydrogen production and generating power from stored hydrogen based on real-time energy demands and supply conditions.
• Balancing Supply and Demand: By using power to produce hydrogen during periods of low demand or excess energy generation, the HESS helps balance the overall energy system, storing energy as hydrogen for later use.
• Operational Flexibility: The ability to quickly switch between positive and negative power values shows the system’s flexibility in efficiently managing hydrogen production and consumption.

Negative power values in the hydrogen power data indicate times when the HESS is actively consuming electricity for hydrogen production. This ability is essential for optimizing energy storage, balancing supply and demand, and integrating renewable energy sources into the grid.

These figures provide essential insights into how hydrogen energy and power are managed within the energy management system (EMS). They aid in the comprehension of the dynamic behavior of hydrogen energy storage systems (HESSs) in reaction to supply and demand for energy. The optimization of the integration and operation of HESSs, the assurance of efficient energy storage and supply, and the improvement of the overall stability and efficiency of the energy system all depend on this analysis.

4.4. Load

Load (Figure 8) depicts the load variation over a 24 h period, with a time scale ranging from 0 to 25 h. The power scale spans from 34.8 to 35.5 kW. The load starts at 34.9 kW, gradually rising to 35.5 kW by the 12th h. After reaching this peak, the load decreases slowly to 35.1 kW by the 17th h. There is a slight increase to 35.22 kW by the 20th h, and the load finally stabilizes at 35 kW by the 24th h.

Figure 8 shows the power output associated with the load (in kW) over a 24 h period, highlighting the dynamic management by the energy management system (EMS). The horizontal axis represents time from 0 to 24 h, while the vertical axis denotes power output, ranging from 35 kW to 35.4 kW.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During the daytime, the load power output gradually increases, reaching a peak around midday (approximately 10 h). This increase reflects higher energy demand during the day, as the EMS manages to supply power to meet this demand. After the peak, the load begins to decrease, showing the response to the fluctuating energy requirements as the day progresses.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): At night, the load power output exhibits smaller fluctuations compared to the daytime, reflecting a generally lower and more stable energy demand. The EMS’s role during this period is to maintain a steady supply of power, ensuring that energy needs are met efficiently during periods of lower demand, with minimal variation in power output.

Figure 8 emphasizes the EMS’s critical role in managing load power to ensure the stability of the system, with distinct patterns of power fluctuation corresponding to day and night cycles. Recognizing these patterns is essential for optimizing load management and maintaining efficient energy operation throughout the day.

This figure provides an overview of the load process, highlighting how the system adjusts power load throughout the day. The load management strategy is designed to balance demand and supply efficiently, ensuring optimal grid operation. Understanding these variations aids in optimizing load distribution, reducing peak demand stress, and maintaining grid stability.

4.5. PV Power Integration

Power PV integration (Figure 9) illustrates the integration of photovoltaic (PV) power with other energy sources over a 24 h period, using a time scale from 0 to 25 h and a power scale ranging from −50 to 100 kW. PV power starts at 0 kW, gradually increasing to a peak of 48 kW by the 10th h, then slowly decreasing and stabilizing until the 24th h. Battery power also begins at 0 kW, rising to 45 kW by the third hour and consistently maintaining this level until the end of the period. Hydrogen power starts at −48 kW, fluctuating between −48 kW and 48 kW throughout the day, indicating periods of high production and consumption. Grid power starts at 75 kW, occasionally dipping to −50 kW, but generally maintaining a level between 40 kW and 75 kW until the 24th h. Load power operates steadily, starting at 40 kW and continuing consistently until the end of the period.

Figure 9 illustrates the power output from various sources (power PV integration), including PV (photovoltaic), battery, hydrogen, grid, and load (in kW), over a 24 h period, highlighting the EMS’s dynamic management. The horizontal axis represents time from 0 to 24 h, while the vertical axis shows power output, ranging from −50 kW to 50 kW.

• Daytime Period (6:00 AM–6:00 PM, 6 to 18 h): During the daytime, the power outputs from different sources, particularly PV and battery, exhibit significant activity. The PV power generation increases as sunlight becomes available, peaking during the middle of the day. This is reflected in the EMS’s active management, where the power from PV is used or stored in the battery. Additionally, the hydrogen system and grid also show fluctuations, indicating their roles in balancing the load and managing excess generation during this period of high renewable energy availability.
• Nighttime Period (6:00 PM–6:00 AM, 18 to 6 h): At night, PV power output drops to zero due to the absence of sunlight, leading to reduced fluctuations in the EMS’s operation. The battery and grid systems take on more significant roles during this period, as they provide the necessary power to meet the load demand. The EMS’s strategy shifts towards discharging the battery and possibly utilizing stored hydrogen to ensure a continuous power supply, with minimal reliance on fluctuating sources.

Figure 9 emphasizes the EMS’s crucial role in integrating and balancing various power sources, particularly in response to the distinct patterns of energy generation and demand associated with day and night cycles. Understanding these patterns is vital for optimizing the use of renewable energy and ensuring efficient grid operation throughout the day.

This figure provides a detailed view of how PV power is integrated with battery storage, hydrogen energy, grid power, and load demands within the energy management system (EMS). It draws attention to the dynamic interactions and modifications that different power sources make to guarantee a reliable and effective energy supply all day long. Comprehending these interplays is crucial for maximizing the integration of renewable energy sources and augmenting the overall efficiency and dependability of the energy management system.

4.6. Comprehensive Analysis

The analysis of the energy management system (EMS) across 24 h reveals significant insights into battery energy and power dynamics, grid power and pricing fluctuations, hydrogen energy and power management, load variations, and PV power integration.

• Battery Energy and Power: Battery energy fluctuates from an initial level of approximately 1.8 kW-h, dropping to around 0.5 kW-h by the 13th h, and then increasing to about 3.7 kW-h by the end of the 24 h. Meanwhile, battery power exhibits a rapid initial increase to 4 W within the first hour, with intermittent decreases to 0, 0.5 W, and 1 W, but generally maintains close to the upper limit of 4 W. These patterns illustrate how the EMS optimizes energy storage, discharge, and grid interactions for efficiency and stability.
• Grid Power and Pricing: Grid power starts at 75 kW, experiences fluctuations peaking at approximately 30 kW, and ends at −5 kW by the 24th h. Concurrently, grid pricing begins at 91 USD/kWh, reaches a peak of 111 USD/kWh around the 22nd hour, and returns to 91 USD/kWh by the end of the period, ultimately reaching 0. These results show how demand fluctuations, market dynamics, and operational modifications impact grid power supply and pricing, which in turn impacts EMS strategies for optimizing battery energy storage systems (BESSs) and hydrogen energy storage systems (HESSs).
• Hydrogen Energy and Power: Hydrogen energy levels start at 4 kW-h, decrease to 1 kW-h, peak at 8 kW-h, and exhibit fluctuations throughout the day. Hydrogen power output predominantly stays at 40 kW, briefly dropping to −40 kW, reflecting periods of intense activity and the effective management of hydrogen production and consumption by the EMS. This variability is crucial for optimizing HESS integration and ensuring efficient energy storage and supply.
• Load: The load begins at 34.9 kW, peaks at 35.5 kW around the 12th h, decreases to 35.1 kW by the 17th h, and stabilizes at 35 kW by the 24th h. These variations underscore the EMS’s capability to balance demand and supply, optimize load distribution, mitigate peak demand stress, and maintain grid stability.
• PV Power Integration: PV power starts at 0 kW, peaks at 48 kW by the 10th h, and stabilizes thereafter. Battery power maintains a steady rise to 45 kW, while hydrogen power fluctuates between −48 kW and 48 kW. Grid power varies between −50 kW and 75 kW, with load power remaining constant at 40 kW. This integration highlights the significance of optimizing renewable energy integration for overall EMS performance and reliability by showing how the EMS dynamically controls energy sources and demand to maintain a stable and efficient energy supply.

The EMS’s adaptive strategies for managing diverse energy sources and demands are critical for enhancing efficiency, stability, and reliability in the energy system.

5. Future Prospects

Looking ahead, energy management systems (EMSs) are expected to experience several transformative advancements (

Table 9. Future Prospects for EMS.

No	Aspects	Description
1	Energy Storage Technologies	Incorporation of advanced batteries (solid-state, advanced lithium–ion) for increased energy density, longer lifespan, and faster charging capabilities.
2	Smart Grid Integration	Utilization of smart grid technologies for real-time analytics, AI-driven decision-making, and optimized energy distribution.
3	Hybrid Energy Systems	Deployment of hybrid systems combining renewables (solar, wind) with BESSs and HESSs to enhance reliability and address intermittency challenges.
4	Optimization Algorithms	Adoption of AI and machine learning algorithms to optimize energy dispatch, predict demand patterns, and adjust EMS parameters dynamically.
5	Policy and Regulatory Support	Development of supportive policies and regulations to incentivize EMS adoption, foster innovation in clean energy, and promote sustainability goals.
6	Consumer Engagement	Empowering customers to take an active role in energy management through smart metering, real-time energy monitoring, and user-friendly interfaces.

). A key area of development is the integration of cutting-edge energy storage technologies within EMS. The use of next-generation batteries, such as solid-state or advanced lithium–ion batteries, which provide enhanced energy density, longer lifespans, and faster recharge times, is anticipated. These improvements will significantly boost EMS performance, allowing for more efficient energy flow management and better integration with the grid.

The evolution of EMSs is also closely linked with advancements in smart grid technologies. These smart grids utilize advanced sensors, real-time data analytics, and artificial intelligence (AI) algorithms to optimize energy distribution and forecast demand patterns. With these tools, EMSs can adjust to supply and demand changes in real-time, facilitating the integration of renewable energy sources and reducing reliance on fossil fuels. The application of AI and machine learning algorithms, such as predictive analytics and reinforcement learning, will enhance the accuracy of demand forecasts and optimize energy dispatch schedules, leading to improved energy efficiency and cost reductions.

Additionally, the future of EMSs will likely focus on hybrid energy systems. These systems combine advanced energy storage solutions like battery energy storage systems (BESSs) and hydrogen energy storage systems (HESSs) with various renewable energy sources, such as solar and wind. By leveraging the complementary strengths of different energy sources, these hybrid systems improve reliability, address intermittency issues related to renewables, and enhance overall system resilience.

Future EMS development will also harness advanced optimization algorithms and machine learning techniques. These technologies will allow EMSs to predict energy demand more accurately, optimize energy dispatch schedules, and autonomously adjust operational parameters in real-time. This technological integration is expected to reduce costs, improve operational efficiency, and support broader sustainability objectives. For example, deep learning algorithms can analyze complex energy consumption patterns and optimize storage and distribution processes.

Practical steps for implementing smart grid infrastructure are also crucial. This involves developing robust communication networks, deploying smart meters, and establishing interoperability standards to ensure seamless interaction between various components of the energy system. Such measures will enable real-time monitoring and control of energy flows, enhancing system efficiency.

Government policies and regulatory frameworks will play a vital role in shaping the future of EMSs. Anticipated policies are expected to incentivize EMS adoption, promote cross-sector interoperability, and encourage innovation in clean energy technologies. Supportive policies, such as subsidies for renewable energy projects, tax incentives for energy storage, and regulations promoting smart grid development, will help create an environment conducive to advancing sustainable energy systems.

Lastly, improving consumer engagement will be a key element of future EMSs. Technologies such as smart meters and intuitive energy management apps will provide consumers with real-time insights into their energy usage. This transparency will empower users to make informed decisions about their energy consumption and participate in demand-side management initiatives, enhancing overall energy efficiency and sustainability. For instance, mobile apps can offer detailed energy usage reports and suggest ways to reduce consumption, fostering energy conservation.

The future of EMSs is poised for significant advancements in technological integration, smart grid capabilities, hybrid energy systems, optimization strategies, supportive legislation, and increased consumer involvement. These developments will drive improvements in efficiency, resilience, and sustainability across global energy networks, playing a crucial role in transitioning to a more sustainable energy future.

6. Conclusions

We have examined the complex interaction between hydrogen energy storage systems (HESSs) and battery energy storage systems (BESSs) within the energy management system (EMS) in this work. Our approach involved meticulous data collection and analysis, comprehensive system design and configuration, and rigorous MATLAB modeling and simulation. These processes established a robust framework for evaluating the dynamics and performance of energy storage, grid interactions, and renewable integration.

The EMS optimization revealed substantial insights into the operational behavior of battery energy and power. For example, battery energy levels fluctuated between 0.5 kW-h and 3.7 kW-h over a 24 h period, showing adaptive responses to grid demands. Battery power dynamics maintained efficiency near its peak capacity of 4 W for extended periods despite varying operational conditions.

Analyzing grid power and grid price dynamics underscored the challenges and opportunities in managing energy supply and pricing. Grid power varied from −5 kW to 75 kW, and grid prices ranged from 75 to 120 USD/kWh, peaking at 111 USD/kWh. These variations illustrated the complex interplay between demand response strategies, market conditions, and operational constraints, influencing grid stability and economic viability.

Hydrogen energy and power dynamics showcased the versatility of HESSs in balancing energy storage and distribution. Hydrogen energy storage fluctuated significantly from 1 kW-h to 8 kW-h, and hydrogen power ranged from −40 kW to 40 kW throughout the day. These fluctuations indicated the dynamic changes in hydrogen energy storage and power production, facilitating the integration of renewable energy sources and enhancing grid resilience.

Load optimization demonstrated significant contributions to grid stability and operational efficiency. Load management maintained balance with load power stabilizing around 35 kW, effectively managing power consumption, reducing peak demand stress, and ensuring reliable grid operation.

PV power integration highlighted synergistic interactions among renewable energy sources, storage technologies, and grid operations. PV power peaked at 48 kW by the 10th h, and this integration with the BESS and HESS underscored the potential to enhance energy sustainability and reduce environmental impact.

The comprehensive analysis synthesized these findings, emphasizing the interconnected nature of energy storage systems, grid dynamics, and renewable integration. It underscored the importance of holistic approaches to optimize EMS performance, enhance energy efficiency, and promote sustainable development.

Looking forward, the prospects for integrated BESS and HESS systems are promising. Advances in battery and hydrogen storage technologies are expected to enhance scalability, efficiency, and reliability. Policy support and regulatory frameworks will be crucial in facilitating the transition to low-carbon energy, maximizing system performance, and accelerating deployment. Collaborative efforts and knowledge-sharing initiatives will drive innovative solutions and best practices in EMS optimization. Stakeholders can collectively enhance energy transition efforts and address global energy challenges by leveraging technological advancements, fostering partnerships, and aligning with global sustainability goals.

In conclusion, this research provides valuable insights into the strategic and operational aspects of integrating BESSs and HESSs within EMS frameworks. Through the combination of advanced technology, policy support, and collaborative partnerships, we can accelerate the transition towards a sustainable energy landscape, improve grid stability, and optimize energy management strategies.