Integration Of Storage Systems Research Articles

Multi-agent modeling for energy storage charging station scheduling strategies in the electricity market: A cooperative learning approach

With integration of an energy storage system (ESS), an energy storage charging station serves as pivotal intermediaries between the smart grid and electric vehicles (EVs). This station utilizes the ESS to enhance grid stability and facilitate energy management. Participation in electricity market transactions offers revenue opportunities for charging stations, but it also introduces operational challenges, due to fluctuating electricity market prices and diverse energy demands and supplies. In this paper, we study the operation strategy optimization problem for the charging station, addressing economic and service challenges influenced by market volatility and energy diversity. The optimization objective considers not only maximizing economic benefits from the electricity market and EV services but also minimizing penalties associated with EV service quality. We propose a model that accounts for the dynamics of the electricity market, uncertainties from EV demands, and disturbances from green power generation, optimizing the power scheduling of the ESS and multiple charging piles (CPs) to determine transaction power in the market. The cooperative scheduling strategies for the ESS and CPs are learned using the proposed heterogeneous Multi-agent Deep Deterministic Policy Gradient method. This approach features distributed agents learning to determine decision variables for both the ESS and CPs, while a joint critic network assesses the station’s overall objectives to guide their cooperative learning. The proposed method was tested against three state-of-the-art benchmark methods, which showed our method achieves better results.

Experimental study on the effects of integrating phase change material with a solar updraft tower

AbstractThe solar updraft tower power plant presents a promising renewable energy solution but faces limitations in thermal efficiency and energy production during nonsunny hours. This study addresses a critical gap in the literature by investigating the integration of latent heat storage systems utilizing paraffin wax as phase change materials (PCMs) to enhance solar updraft tower (SUT) performance. Two identical small‐scale SUTs were constructed, both using the same tank configuration; however, the PCM device was filled with paraffin wax as a PCM, while the non‐PCM device contained only atmospheric air. Three scenarios were explored, featuring varying PCM tank heights of 2, 4, and 6 cm (the full capacity of the PCM tank). Results indicated that, from 3 p.m. until sunset, the PCM‐integrated SUT in Case 3 (with 6 cm of PCM) achieved the best performance, with an average absorber temperature rise of 25°C, compared with 12°C for the non‐PCM device. During the same period, the average air velocity at the tower neck, where a wind turbine could be installed, was 1.21 m/s for the PCM device, versus 0.82 m/s for the non‐PCM device. Notably, the nocturnal operating time extended significantly with PCM use, rising from 90 min for the 2 cm case to 125 min for the 6 cm case. In contrast, the non‐PCM device exhibited no operational time after sunset. This research not only demonstrates the effectiveness of PCM in improving the thermal performance and operational longevity of SUTs but also introduces a novel tank configuration that allows for flexible PCM integration, representing a significant advancement in the development of more efficient SUT systems.

Optimization of solid oxide electrolysis cells using concentrated solar-thermal energy storage: A hybrid deep learning approach

The Solid Oxide Electrolysis Cell (SOEC) represents a cutting-edge solution for the conversion of CO2 and H2O into syngas, offering significant economic and environmental benefits. However, the process requires substantial high-temperature heat inputs, traditionally supplied by electricity. This study introduces a novel approach leveraging concentrated solar radiation as a renewable heat source for SOEC, addressing the challenge of its inherent fluctuations through the integration of Thermal Energy Storage (TES) systems. We propose a hybrid model that combines multi-physics simulation with a deep learning algorithm, enabling rapid optimization of the electrolysis process under real-time direct normal irradiance conditions. Our findings demonstrate that the inclusion of TES within the system architecture results in a remarkable 53 % reduction in temperature variation rate at the SOEC inlet, ensuring operational stability and efficiency. Furthermore, by fine-tuning capacity parameters, we have developed a control strategy that harmonizes efficiency with safety performance. The robustness of our system is underscored by its resilience to step changes, achieving a 75 % reduction in temperature fluctuations. This research contributes a pioneering method for the real-time optimization and control of SOEC systems, harnessing the power of TES to drive sustainable energy conversion with enhanced reliability and economic viability, facilitating precise and swift predictive capabilities even under dynamic operating conditions.

An overview on building-integrated photovoltaics: technological solutions, modeling, and control

The advancement of renewable and sustainable energy generation technologies has been driven by environment-related issues, energy independence, and high costs of fossil fuels. Building-integrated photovoltaic systems have been demonstrated to be a viable technology for the generation of renewable power, with the potential to assist buildings in meeting their energy demands. This work reviews the current status of novel PV technologies, including bifacial solar cells and semi-transparent solar cells. This review discusses the various constructions of PV technologies, recent advances in these products, the influence of key design factors on electrical and thermal performance, and their potential in the design of energy-efficient smart buildings. The attention is focused on bifacial and semi-transparent PV systems, given the high level of interest of the scientific community in their current and potential applications.Focus is also devoted to the analysis of the electrical, optical, and thermal modeling procedures developed for sizing, designing, and integrating photovoltaics into larger building simulations. The development of these models has a positive impact on the implementation of next-generation smart buildings. The latest innovative developments and key issues in the application of bifacial PV solutions in buildings are also summarized and analyzed. Special attention is paid to rear side electrical performance, which can be evaluated by means of illuminance/optical backside modeling. Finally, energy management and control of PV-equipped buildings via both model-based and data-driven approaches are discussed, as well as the integration of electric storage systems in a multi-building context.

DeepEMS: Multimodal optimal energy management of microgrid systems based on a hybrid multi‐stage machine learning model

AbstractThe effective management of microgrids is important towards transition to sustainable energy paradigm. By optimizing the utilization of different energy sources, such as solar photovoltaic panels and energy storages, it improves the reliability of the grid and develops resiliency in dealing with of challenges of unexpected variations in demand. To this end, the proposed paper presents DeepEMS, a system developed to manage the energy of microgrids through the incorporation of diverse intelligent algorithms. DeepEMS provides dynamic microgrid management through the utilization of Bidirectional Long Short‐Term Memory (BiLSTM) networks, Sliding Linear Programming (SLP), and Random Forest (RF). By implementing these methodologies, DeepEMS can optimize energy consumption throughout the microgrid by dynamically identifying and coordinating the needs of various energy sources. DeepEMS achieves precise multimodal optimization and facilitates integration of storage systems, grid interactions, and renewable energy sources (RES), as demonstrated by simulations and data analytics. DeepEMS presented performance in control, resource allocation, management, and grid utilization. Furthermore, in a comparative analysis with alternative intelligent models including XGBoost, Light GBM, RF, and Decision Trees, DeepEMS consistently demonstrated higher performance as measured by several key performance indicators (KPIs).

A solar-powered multi-functional portable charging device (SPMFPCD) with internet-of-things (IoT)-based real-time monitoring—An innovative scheme towards energy access and management

In the absence of portable charging devices, sectors such as transportation, communication, and emergency services deal with various challenges towards electric power needs while compromising on (1) operational efficiency, (2) insufficient portable charging solutions, and (3) limited versatility. This highlights the critical need for reliable and multi-functional power solutions. To provide a portable charging solution across diverse sectors, this paper proposes an innovative development of a solar-powered multi-functional portable charging device (SPMFPCD) with internet- of-thing (IoT)-based monitoring capabilities. The proposed scheme introduces a comprehensive model integrating advanced technologies which include a highly efficient solar panel, charge controller, sensors, and IoT module. The proposed system facilitates versatile charging solutions for a wide range of power requirements with real-time monitoring and data analysis through the IoT platform. Moreover, the proposed work explores the applications of the SPMFPCD in (1) emergency medical scenarios, (2) outdoor adventures, (3) disaster management, and 4) public spaces. Performance evaluation was made by proposing case studies to validate the (1) economic viability, (2) power management, and (3) environmental impact of widespread deployment of SPMPFCD in public spaces. Furthermore, detailed analysis of battery energy storage system (BESS) and photovoltaic (PV) integration for load management, seasonal dynamics, and renewable energy integration (REI) contribute to a comprehensive understanding of the proposed solution.

Analytical model and swapping policy assessment of a vertical lift module – buffer integrated storage system

To meet the rising demands of global trade and e-commerce, efficient warehousing relies on integrated and cooperative material handling systems. This paper investigates the extension of Vertical Lift Module (VLM) storage capability with a Buffer System and assesses the impact of this integration on performance. We developed an analytical model to calculate the expected dual command cycles, forming the basis for evaluating the VLM – Buffer integrated storage system’s performance. Our research emphasises minimising unnecessary swaps between the VLM and the Buffer System to enhance throughput performance. We introduce the Look Ahead Strategy (LAS) to minimise inter-system swaps and develop a Binary Integer Program (BIP) to benchmark its performance. The results indicate that LAS performs on par with BIP, due to its ability to consider product popularity during the final selection of the outbound swapping tote. Through a comprehensive analysis of the analytical model with an empirical correction, utilising Pareto-based order sequences, the results show deviations of less than 1% on average, affirming the analytical model’s accuracy. Our research provides insights on using the VLM-Buffer integrated storage system, emphasising efficient tote swapping policies like LAS for enhanced warehouse operations, and allows managers to assess system performance through scenario-based analyses.

Model predictive control of a grid-scale Thermal Energy Storage system in RELAP5-3D

This research delves into the integration and control of a Thermal Energy Storage (TES) system with a Small Modular Reactor (SMR), specifically the NuScale VOYGR SMR module in RELAP5-3D. The research methodology centered on modeling the NuScale VOYGR SMR, a light water pressurized water reactor (LWR) with a power output capacity of 77 MWe per module. The reactor and plant details were sourced from NuScale's final safety analysis report and supplemented by information from the NuScale website. The SMR plays a crucial role in energy generation, and to manage and dispatch the produced energy effectively, a robust storage system is essential. The proposed solution to this challenge is the implementation of the TES system. The selected TES for this research is a two-tank system. The study also employed Model Predictive Control (MPC) to optimize the operation of the TES system in conjunction with the SMR. Various simulations, including accident scenarios, were conducted to assess the system's response and performance. The research leveraged real energy demand data from the California Independent System Operator (CAISO) database and scaled it to reflect the power generation of a single SMR. The findings suggest that while integrating a TES system with an SMR can enhance the performance compared to a standalone SMR, certain scenarios might exacerbate the total power mismatch. The study provides insights into the potential of integrating TES systems with nuclear reactors and the challenges and considerations involved.

Mitigation of Photovoltaics Penetration Impact upon Networks Using Lithium-Ion Batteries

The paper conducts a comprehensive analysis of the impact of very large-scale photovoltaic generation systems on various aspects of power systems, including voltage profile, frequency, active power, and reactive power. It specifically investigates IEEE 9-bus, 39-bus, and 118-bus test systems, emphasizing the influence of different levels of photovoltaic penetration. Additionally, it explores the effectiveness of battery energy storage systems in enhancing system stability and transient response. The transition to PV generation alters system stability characteristics, impacting frequency response and requiring careful management of PV plant locations and interactions with synchronous generators to maintain system reliability. This study highlights how high penetration of photovoltaic systems can improve steady-state voltage levels but may lead to greater voltage dips in contingency scenarios. It also explores how battery energy storage system integration supports system stability, showing that a balance between battery energy storage system capacity and synchronous generation is essential to avoid instability. In scenarios integrating photovoltaic systems into the grid, voltage levels remained stable at 1 per unit and frequency was tightly controlled between 49.985 Hz and 50.015 Hz. The inclusion of battery energy storage systems further enhanced stability, with 25% and 50% battery energy storage system levels maintaining strong voltage and frequency due to robust grid support and sufficient synchronous generation. At 75% battery energy storage system, minor instabilities arose as asynchronous generation increased, while 100% battery energy storage system led to significant instability and oscillations due to minimal synchronous generation. These findings underline the importance of synchronous generation for grid reliability as battery energy storage system integration increases.

Charging Strategies for Electric Vehicles from Renewable Hybrid Systems

Objective: The aim of this study is to analyze charging strategies for electric vehicles (EVs) in a hybrid system connected to the conventional electricity grid, to optimize the use of renewable energies. Theoretical Framework: This paper presents the concepts of hybrid systems, photovoltaic power generation, and electric vehicle energy demand. It emphasizes the importance of integrating renewable energy into the transportation sector to reduce greenhouse gas emissions and promote sustainability. Method: The research was based on obtaining load curves and photovoltaic generation in different climatic conditions. The energy available for charging electric vehicles was calculated, considering the limitations of the hybrid system. Different charging power configurations were studied. Results and Discussion: The results demonstrate the feasibility of recharging EVs with renewable energy and highlight the operational flexibility provided by storage systems. Different climate scenarios affect energy availability for charging, highlighting the importance of adaptive strategies. Research Implications: This research contributes to developing sustainable strategies in the transportation sector by providing insights into integrating electric vehicles and renewable energy. Practical implications include reducing carbon emissions and decreasing dependence on fossil fuels. Originality/Value: This study stands out for its specific analysis of EV charging strategies in a hybrid context, providing new approaches for the efficient use of renewable energy in transportation. The integration of storage systems and adaptation to climatic conditions are innovative aspects that add value to the research.

Energy savings by adapting consumer behavior in grid-connected photovoltaic systems with battery storage

Today, the world faces many energy challenges that make the use of clean energy an obligation and an emergency. These challenges require changes in a wide range of sectors, including transport, industry and residential areas. At present, energy production is responsible for a large amount of greenhouse gas emissions, the main cause of climate change with its various dangerous effects on human life. Therefore, a change towards non-carbon energy is becoming a necessity. Certainly, this evolution has been underway for years and the renewable energy market has developed in a surprisingly efficient way. However, the current situation has reached an alarming state and requires the active participation of all stakeholders, especially consumers. Therefore, the main objective of this paper is to illustrate how consumer behavior can significantly influence and contribute to the optimization of renewable energy systems, especially photovoltaic systems. The paper emphasizes the beneficial integration of batteries and storage systems to achieve energy savings. The results show that with some adjustments in daily behavior, an overall energy saving of 62% can be achieved compared to the normal consumption scenario: the energy obtained from the grid and then the electricity bill is reduced.

Knowledge mapping and evolutionary analysis of energy storage resource management under renewable energy uncertainty: a bibliometric analysis

The research on energy storage resource management is an important measure to cope with the present problem of uncertainty in the use of renewable energy, in order to explore the evolution of the research focus and future trend of energy storage resource management under the uncertainty of renewable energy, this paper adopts the method of bibliometric analysis, and conducts a visual analysis of the relevant 800 documents in the core collection of the Web of Science by using the CiteSpace to draw co-occurrence maps and analyze the collaborative networks of different countries/regions, institutions and authors in this field, and further conducted journal co-citation analysis, literature co-citation analysis and author co-citation analysis. The keyword co-occurrence, emergent analysis, and cluster co-occurrence analysis reveal the current research focus and trend in this field, and summarize and propose four future key focus directions: energy storage technology improvement, energy storage system integration, expansion of business models for energy storage resource management, and intelligent control of energy storage system, which provide new research paths for solving the problem of renewable energy uncertainty in the future.

Assessment of carbon dioxide transcritical cycles for electrothermal energy storage with geological storage in salt cavities

Carbon capture, utilisation, and storage (CCUS) technologies are envisaged as critical actors in the energy transition and climate change mitigation framework. Despite the recent advances in CCUS implementation, there is still significant scope for their growth and improvement. On the other hand, developing new large-scale energy storage systems is a key factor for the massive deployment of renewable energy systems. Technologies such as the electrothermal energy storage system based on carbon dioxide transcritical cycles incorporating geological storage (CEEGS) can contribute to both fields. Preliminary studies have shown that the integrated storage system can operate with roundtrip efficiencies exceeding 50%, injecting over 1 million tons of captured carbon dioxide (CO2) annually. It is an early-stage technology with open challenges for successful development, such as an adequate balance between the high- and low-temperature thermal storage reservoirs or the operation definition between the electrothermal system and the carbon dioxide injection and recovery. Underground pressures will oscillate with the charge/discharge process, with operational implications and constraints. Advancing in the concept requires the definition of optimised operation. This work presents a novel analysis of the adaptation of CO2 transcritical cycles to include injection and production processes with the specific scenario of salt cavities. It considers new modifications to adapt the transcritical cycles in closed-mode operation to the conditions required by the salt cavities injection and production processes. Different case studies are evaluated, evaluating the impact of injection and geological storage, production and surface storage, and reinjection into the geological formation. The analyses show roundtrip efficiencies within the range of 49.1–73.0% when the injection, production, and reinjection processes are executed.

A bidirectional isolated DC‐DC converter with low voltage stresses for energy storage systems integration

AbstractHerein, a bidirectional isolated DC‐DC converter with low voltage stress is introduced to utilise in energy storage frameworks. Two sets of coupled inductors (CI) and a transformer are utilized on the low‐voltage side to increase voltage gain. Through the series connection of the secondary windings of the CIs with the primary windings of the transformer, the concluded voltage gain is improved by the multiplication of the turns ratios of CI and transformer. As a result, the voltage gains as well as the voltage stresses in both directions can be flexibly improved through three degrees of freedom, which are the turns ratios of the CIs, transformer and duty cycle. Clamp capacitors accomplish active clamping, and the energy saved within the leakage inductance is recycled. Additionally, some switches are performed with soft‐switching and partially diminished switching losses. The steady‐state analysis and extensive performance comparison of the proposed converter prove that the proposed converter outperforms the similar previous converters in the state‐of‐the‐art. An 800 W 48 V/380 V prototype is developed to prove the performance of the proposed converter. The peak efficiency amounts of the proposed system in the high step‐down and high step‐up modes are 95.8% and 96.2%, respectively.

Design, analysis, and operation optimisation of a shipborne absorption refrigeration–ice thermal storage system based on waste-heat utilization

The integration of waste-driven absorption refrigeration technology into marine applications is recognized as a promising low-carbon solution. Nonetheless, its practical application does not inherently outperform electric compression technology, primarily due to the absorption system’s inherent thermal inertia and limited adjustability. This characteristic renders the system less responsive to the dynamic refrigeration requirements typically encountered on board vessels. In this study, a shipborne ammonia absorption refrigeration–ice storage system is proposed to balance the cooling load between supply and demand. To evaluate the efficiency of the integrated system for ice storage and cooling during ship sailing, key operational variables including refrigeration temperature, cooling water temperature, and generation temperature are analyzed to assess the thermal cycle performance of the system. A typical shipping route is considered for cooling operation optimisation of the absorption refrigeration–ice storage system. This paper explores four typical cooling-supply strategies and determines the operation modes for the ice storage period and the cooling period based on considerations of energy consumption, energy utilization, and economic factors. The final optimisation results indicate that the combined system has significant advantages based on energy consumption and operation cost. In comparison to compression and absorption refrigeration systems, the proposed system exhibits 52.4% and 8.31% reductions in energy consumption, respectively. Additionally, the operation costs are decreased by 12.27% and 27.41%, respectively, and the life cycle costs are lowered by 11.51% and 32.35%, respectively. The findings of this combined system can provide a technical reference for the design and operation of a ship waste-heat refrigeration system.

Inventory model having preservation technology with fix lifetime under two level trade credit policy

Supply-chain management involves moving storage supplies from origin to consumption, with manufacturers running production based on quadratic demand, distributors and retailers monitoring inventory. When a new product is released, demand often rises linearly and then declines dramatically when an alternative becomes available. Shortages are not allowed. Players' inventory will decrease at a rate of (1/(1+m-t)), where m is fixed lifetime, greater than the replenishment time. Deteriorating goods experience constant mass loss or usefulness, but preservation technology can help the damaged item to be consumed. Retailers with direct customer relationships can reduce stock spoilage through good warehouses. Manufacturers' storage systems have a higher deterioration rate. Two-tier trade credit financing is examined in this model. Distributors offer specific credit terms to stores, while manufacturers provide a grace period for invoicing. Distributors and retailers must pay interest on unsold inventories if invoices aren't settled on time. An integrated storage system reduces costs by minimizing costs through multiple shipments from manufacturers to distributors and retailers, and by adjusting replenishment times for each player. The resolution process is designed so that the supply chain operator gets the best possible decision. Therefore, results are authorized using mathematical examples for different scenarios. Management decisions are suggested.

Enhanced Frequency Containment Reserve provision from battery hybridized hydropower plants: Theory and experimental validation

This paper presents a solution to address wear and tear of Run-of-River (RoR) Hydropower Plants (HPPs) providing enhanced Frequency Containment Reserve (FCR). In this respect, the study proposes the integration of a Battery Energy Storage System (BESS) with RoR HPPs controlled by a double-layer Model Predictive Control (MPC). The upper layer MPC acts as a state of energy manager for the BESS, employing a forecast of the required regulating energy for the next hour. The lower-layer MPC optimally allocates the power set-point between the turbine and the BESS. Reduced-scale experiments are performed on a one-of-a-kind testing platform to validate the proposed MPC-based control considering a comparison with different control strategies and different BESS sizes. The results demonstrate superior performance of the proposed framework, compared to simpler techniques like dead-band control or to the standalone RoR scenario, leading to improved FCR provision, reduced servomechanism stress, and extended hydropower asset lifespan.

LoadNet: enhancing energy storage system integration in power system operation using temporal convolutional and recurrent models with self-attention

Introduction: In the context of the evolving energy landscape, the efficient integration of energy storage systems (ESS) has become essential for optimizing power system operation and accommodating renewable energy sources.Methods: This study introduces LoadNet, an innovative approach that combines the fusion of Temporal Convolutional Network (TCN) and Gated Recurrent Unit (GRU) models, along with a self-attention mechanism, to address the challenges associated with ESS integration in power system operation. LoadNet aims to enhance the management and utilization of ESS by effectively capturing the complex temporal dependencies present in time-series data. The fusion architecture of TCN-GRU in LoadNet enables the modeling of both short-term and long-term dependencies, allowing for accurate representation of dynamic power system behaviors. Additionally, the incorporation of a self-attention mechanism enables LoadNet to focus on relevant information, facilitating informed decision-making for optimal ESS operation. To assess the efficacy of LoadNet, comprehensive experiments were conducted using real-world power system datasets.Results and Discussion: The results demonstrate that LoadNet significantly improves the efficiency and reliability of power system operation with ESS. By effectively managing the integration of ESS, LoadNet enhances grid stability and reliability, while promoting the seamless integration of renewable energy sources. This contributes to the development of a more sustainable and resilient power system. The proposed LoadNet model represents a significant advancement in power system management. Its ability to optimize power system operation by integrating ESS using the TCN-GRU fusion and self-attention mechanism holds great promise for future power system planning and operation. Ultimately, LoadNet can pave the way for a more sustainable and efficient power grid, supporting the transition to a clean and renewable energy future.

BESS Revolutionizes Renewable Stability in Indonesia

This study examines the integration of Battery Energy Storage Systems (BESS) with Solar Power Plants (PLTS) to enhance electrical grid stability in Indonesia, where 90% of electricity is from fossil fuels. The intermittent nature of PLTS often destabilizes the network, causing frequency hunting or blackouts. Using Etap 12.6 software, simulations showed that adding BESS to hybrid PLTS-PLTD systems significantly mitigates these issues. For instance, a 50% drop in PLTS power without BESS required a 55% increase in PLTD power, but with BESS, this increase was only 34%. Thus, BESS is crucial for stabilizing renewable energy integration and supporting Indonesia’s Net-Zero Emissions goal. Highlights: BESS Stabilizes Power: Reduces impact of PLTS power fluctuations on PLTD. Simulation Insight: 50% PLTS drop increases PLTD by 34% with BESS. Net-Zero Goal: BESS supports Indonesia’s renewable energy and emission targets. Keywords: Renewable Energy, Solar Power, Battery Storage, Electrical Grid Stability, Indonesia

Optimised linear active disturbance rejection control of multiport-isolated DC-DC converter for hydrogen energy storage system integration

Hydrogen energy storage systems are becoming increasingly accepted owing to their environmental friendliness. The efficiency and performance of these systems largely depend on the attributes of their power electronic interface systems. Among the promising solutions is a multiport-isolated DC-DC converter with characteristics of reduced component count, fewer conversion stages, and galvanic isolation. However, this system presents a challenge due to its inherent cross-coupling effect, complicating precise control. To address this, linear active disturbance rejection control (LADRC) is a viable option, leveraging dynamic/disturbance properties observed by linear extended state observers. LADRC serves as a decoupling controller, mitigating the cross-coupling effect. However, LADRC has several gains, and selecting them can be a difficult task, often requiring manual tuning. To streamline this process, this paper proposes utilising particle swarm optimisation to determine the optimum gains of LADRC. By employing this approach, the implementation of LADRC is facilitated with reduced design efforts while ensuring effective decoupling control within the system. Simulations are conducted to validate the performance of the optimised gain LADRC.