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The integration of an energy storage system into an integrated energy system (IES) enhances renewable energy penetration while catering to diverse energy loads. In previous studies, the adoption of a battery energy storage (BES) system posed challenges related to installation capacity and capacity loss, impacting the technical and economic performance of the IES. To overcome these challenges, this study introduces a novel design incorporating a compressed CO2 energy storage (CCES) system into an IES. This integration mitigates the capacity loss issues associated with BES systems and offers advantages for configuring large-scale IESs. A mixed integer linear programming problem was formulated to optimize the configuration and operation of the IES. With an energy storage capacity of 267 MWh, the IES integrated with a CCES (IES–CCES) system incurred an investment cost of MUSD 161.9, slightly higher by MUSD 0.5 compared to the IES integrated with a BES (IES–BES) system. When not considering the capacity loss of the BES system, the annual operation cost of the IES–BES system was 0.5 MUSD lower than that of the IES–CCES system, amounting to MUSD 766.6. However, considering the capacity loss of the BES system, this study reveals that the operation cost of the IES–BES system surpassed that of the IES–CCES system beyond the sixth year. Over the 30-year lifespan of the IES, the total cost of the IES–CCES system was MUSD 4.4 lower than the minimum total cost of the IES–BES system.

Energy storage system (ESS) technology is still the logjam for the electric vehicle (EV) industry. Lithium-ion (Li-ion) batteries have attracted considerable attention in the EV industry owing to their high energy density, lifespan, nominal voltage, power density, and cost. In EVs, a smart battery management system (BMS) is one of the essential components; it not only measures the states of battery accurately, but also ensures safe operation and prolongs the battery life. The accurate estimation of the state of charge (SOC) of a Li-ion battery is a very challenging task because the Li-ion battery is a highly time variant, non-linear, and complex electrochemical system. This paper explains the workings of a Li-ion battery, provides the main features of a smart BMS, and comprehensively reviews its SOC estimation methods. These SOC estimation methods have been classified into four main categories depending on their nature. A critical explanation, including their merits, limitations, and their estimation errors from other studies, is provided. Some recommendations depending on the development of technology are suggested to improve the online estimation.

Frequency regulation (FR) using a battery energy storage system (BESS) has been expanding because of the growth of renewable energy. This study introduces the wear density function, which considers battery degradation factors such as the rate of current, temperature, and depth of discharge (DOD) to provide a precise lifespan prediction. Furthermore, an equivalent system model is developed to evaluate the FR performance of the BESS for various operating parameters. Finally, a quantitative tradeoff relationship between performance and battery lifecycle is derived from the analysis using operational data of the actual BESS for FR.

The increased usage of renewable energy sources (RESs) and the intermittent nature of the power they provide lead to several issues related to stability, reliability, and power quality. In such instances, energy storage systems (ESSs) offer a promising solution to such related RES issues. Hence, several ESS techniques were proposed in the literature to solve these issues; however, a single ESS does not fulfill all the requirements for certain operations and has different tradeoffs for overall system performance. This is mainly due to the limited capability of a single ESS and the potency concerning cost, lifespan, power and energy density, and dynamic response. In order to overcome the tradeoff issue resulting from using a single ESS system, a hybrid energy storage system (HESS) consisting of two or more ESSs appears as an effective solution. Many studies have been considered lately to develop and propose different HESSs for different applications showing the great advantages of using multiple ESSs in one combined system. Although these individual methods have been well documented, a comprehensive review of HESS-integrated RE has not been fully investigated in the literature before. Thus, as a novel contribution to the literature, this study aims to review and analyze the importance and impact of HESSs in the presence of renewable energy towards sustainable development that will facilitate this newly emerging topic to researchers in this field. In this regard, the present scenario and recent trend of HESSs in RESs at the global level, including a comparison with main ESS features, are discussed and analyzed along with the concept, design, classifications, and a detailed comparison of HESSs. The emerging role of HESSs in terms of their benefits and applications has been analyzed. Recent control and optimization methods of HESSs associated with RESs and their advantages and disadvantages have been reviewed. Finally, open issues and new challenges toward more efficient, sustainable, and green energy have also been highlighted herein. All the highlighted insights of this review will hopefully lead to increased efforts toward the development of an advanced HESS for future renewable energy optimal operation.

An emerging problem associated with the increased global demand for electric vehicles (EVs) is the post-use of lithium-ion batteries installed in them. Discarded batteries maintain 70–80% of their performance; thus, they are highly valuable recycling resources. Accordingly, technologies that complement the intermittency of renewable energy by integrating discarded EV batteries into battery energy storage systems (BESSs) are receiving attention. Here, the economic feasibility of a residential solar photovoltaic (PV) + reused BESS (RBESS) integrated system in three emerging countries (Philippines, Indonesia, and Vietnam) was analyzed by comparing its performance with that of diesel power generation and central grid-supplied power. The proposed system had a higher economic feasibility than diesel power generation (55.9% lower LCOE) but a lower economic feasibility than the central grid-supplied power (282.7% higher LCOE) in all three countries. Additionally, we conducted a sensitivity analysis by incorporating the investment cost, government subsidy, and social cost of greenhouse gas emissions. In conclusion, the Philippines is the best country for grid parity with the integrated system, following Indonesia and Vietnam. This study examined both the economic and social benefits of the proposed system as a countermeasure to climate change and the virtuous resource cycle.

Renewable generation and energy storage systems are technologies which evoke the future energy paradigm. While these technologies have reached their technological maturity, the way they are integrated and operated in the future smart grids still presents several challenges. Microgrids appear as a key technology to pave the path towards the integration and optimized operation in smart grids. However, the optimization of microgrids considered as a set of subsystems introduces a high degree of complexity in the associated control problem. Model Predictive Control (MPC) is a control methodology which has been satisfactorily applied to solve complex control problems in the industry and also currently it is widely researched and adopted in the research community. This paper reviews the application of MPC to microgrids from the point of view of their main functionalities, describing the design methodology and the main current advances. Finally, challenges and future perspectives of MPC and its applications in microgrids are described and summarized.

The hybrid energy storage system (HESS) that combines battery with hydrogen storage exploits complementary power/energy characteristics, but most studies optimize capacity and operation separately, leading to suboptimal overall performance. To address this issue, this paper proposes a bi-level co-optimization framework that integrates deep reinforcement learning (DRL) and mixed integer programming (MIP). The outer layer employs the TD3 algorithm for capacity configuration, while the inner layer uses the Gurobi solver for optimal operation under constraints. On a standalone PV–wind–load-HESS system, the method attains near-optimal quality at dramatically lower runtime. Relative to GA + Gurobi and PSO + Gurobi, the cost is lower by 4.67% and 1.31%, while requiring only 0.52% and 0.58% of their runtime; compared with a direct Gurobi solve, the cost remains comparable while runtime decreases to 0.07%. Sensitivity analysis further validates the model’s robustness under various cost parameters and renewable energy penetration levels. These results indicate that the proposed DRL–MIP cooperation achieves near-optimal solutions with orders of magnitude speedups. This study provides a new DRL–MIP paradigm for efficiently solving strongly coupled bi-level optimization problems in energy systems.

This research article presents a comprehensive investigation into the design, optimization, and performance analysis of a hybrid stand-alone microgrid for an industrial facility in Iraq at coordinates 36.51 and 43.99. The system consists of photovoltaic (PV) modules, inverters, a battery energy storage system (BESS), a generator, and AC loads. Leveraging the capabilities of PVsyst version 7.3.1, HOMER Pro version 3.14.2 and SAM version 2022.11.21 software tools, this study assesses the feasibility and functionality of the hybrid stand-alone microgrid. In this study, PVsyst software is used for detailed designing and analysis of a PV plant, and the PVsyst design file is then used in HOMER Pro software to optimize and design the proposed hybrid stand-alone microgrid, and for detailed performance analysis SAM software is employed. This paper also investigates the impact of ground clearance and ground albedo on the annual generation of bifacial PV modules at various tilt angles. Key findings include a promising normalized production rate of 4.53 kWh/kWp/day with a performance ratio of 0.815 and annual energy production estimates of 84.31 MWh (P50), 79.57 MWh (P90), and 78.24 MWh (P95) for monofacial PV modules, highlighting the system’s potential for renewable energy generation. Notably, this research demonstrates the hybrid stand-alone microgrid’s capacity to significantly reduce CO2 emissions, saving approximately 1811.6 tons over a 30-year period, thus contributing to sustainability and environmental conservation goals. Additionally, this study reveals operational challenges during the winter months, necessitating generator support to meet load demands. The successful installation and experimental validation of the hybrid stand-alone microgrid underscore its practical viability and its role in advancing clean energy solutions. This research provides valuable insights into hybrid stand-alone microgrid design, emphasizing its importance in ensuring reliable power supply and environmental stewardship.

Purpose: Lithium-ion (Li-ion) battery packs recovered from end-of-life electric vehicles (EV) present potential technological, economic and environmental opportunities for improving energy systems and material efficiency. Battery packs can be reused in stationary applications as part of a “smart grid”, for example to provide energy storage systems (ESS) for load leveling, residential or commercial power. Previous work on EV battery reuse has demonstrated technical viability and shown energy efficiency benefits in energy storage systems modeled under commercial scenarios. The current analysis performs a life cycle assessment (LCA) study on a Li-ion battery pack used in an EV and then reused in a stationary ESS. Methods: A complex functional unit is used to combine energy delivered by the battery pack from the mobility function and the stationary ESS. Various scenarios of cascaded “EV mobility plus reuse in stationary clean electric power scenarios” are contrasted with “conventional system mobility with internal combustion engine vehicles plus natural gas peaking power.” Eight years are assumed for first use; with 10 years for reuse in the stationary application. Operational scenarios and environmental data are based on real time-of-day and time-of-year power use. Additional data from LCA databases are utilized. Ontario, Canada, is used as the geographic baseline; analysis includes sensitivity to the electricity mix and battery degradation. Seven environmental categories are assessed using ReCiPe. Results and discussion: Results indicate that the manufacturing phase of the Li-ion battery will still dominate environmental impacts across the extended life cycle of the pack (first use in vehicle plus reuse in stationary application). For most impact categories, the cascaded use system appears significantly beneficial compared to the conventional system. By consuming clean energy sources for both use and reuse, global and local environmental stress reductions can be supported. Greenhouse gas advantages of vehicle electrification can be doubled by extending the life of the EV batteries, and enabling better use of off-peak low-cost clean electricity or intermittent renewable capacity. However, questions remain concerning implications of long-duration use of raw material resources employed before potential recycling. Conclusions: Li-ion battery packs present opportunities for powering both mobility and stationary applications in the necessary transition to cleaner energy. Battery state-of-health is a considerable determinant in the life cycle performance of a Li-ion battery pack. The use of a complex functional unit was demonstrated in studying a component system with multiple uses in a cascaded application.

Energy storage systems (ESS) provide a means for improving the efficiency of electrical systems when there are imbalances between supply and demand. Additionally, they are a key element for improving the stability and quality of electrical networks. They add flexibility into the electrical system by mitigating the supply intermittency, recently made worse by an increased penetration of renewable generation. One energy storage technology now arousing great interest is the flywheel energy storage systems (FESS), since this technology can offer many advantages as an energy storage solution over the alternatives. Flywheels have attributes of a high cycle life, long operational life, high round-trip efficiency, high power density, low environmental impact, and can store megajoule (MJ) levels of energy with no upper limit when configured in banks. This paper presents a critical review of FESS in regards to its main components and applications, an approach not captured in earlier reviews. Additionally, earlier reviews do not include the most recent literature in this fast-moving field. A description of the flywheel structure and its main components is provided, and different types of electric machines, power electronics converter topologies, and bearing systems for use in flywheel storage systems are discussed. The main applications of FESS are explained and commercially available flywheel prototypes for each application are described. The paper concludes with recommendations for future research.