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Storage systems are deemed to be unable to provide revenue commensurate with the resources invested in them, thus discouraging their incorporation within power networks. In prosumer microgrids, storage systems can provide revenue from reduced grid consumption, energy arbitraging or when serving as back-up power. This study aims to examine stacking these revenue streams with the aim of making storage systems financially viable for inclusion in prosumer microgrids.

With the aim of reducing self-consumption and maximising revenue, the prosumer microgrid incorporating hybrid energy storage systems (HESS) and solar PV power is solved using the CPLEX solver of the Advanced Interactive Multidimensional Modeling Software (AIMMS). The financial analysis of the results is carried out to provide the payback periods of different system configurations of the prosumer microgrid.

The findings reveal that the payback period of the three HESS when minimising grid expenses during self-consumption alone and when compared with stacked revenue streams shows an improvement from 4.8–11.2 years to 2.4–6.6 years. With stacked HESS revenues, the supercapacitor-lithium ion battery HESS gave the shortest payback period of 2.31 years when solar PV power is at 75% penetration level.

Existing literature has considered revenue streams of storage systems at the electrical power transmission and distribution levels, but not for prosumer microgrids in particular. This study has captured these benefits and verified the profitability of stacking revenue from HESS to prosumer microgrids, using a case study.

The purpose of this paper is to provide high-efficiency and high-power hybrid energy source for an urban electric vehicle. A power management strategy based on fuzzy logic has been introduced for battery-ultracapacitor (UC) energy storage.

The paper describes the design and construction of on-board hybrid source. The proposed energy storage system consists of battery, UCs and two DC/DC interleaved converters interfacing both storages. A fuzzy-logic controller (FLC) for the hybrid energy source is developed and discussed. Control structure has been tested using a non-mobile experimental setup.

The hybrid energy storage ensures high-power ability. Flexibility and robustness offered by the FLC give an easy accessible method to provide a power management algorithm extended with additional input information from road infrastructure or other vehicles. In the presented research, it was examined that using information related to the topography of the road in the control structure helps to improve hybrid storage performance.

The proposed control algorithm is about to be validated also in an experimental car.

Exploratory studies have been provided to investigate the benefits of energy storage hybridization for electric vehicle. Simulation and experimental results confirm that the combination of lithium batteries and UCs improves performance and reliability of the energy source. To reduce power impulses drawn from the battery, power management algorithm takes into consideration information on slope of a terrain.

This research introduces an innovation strategy aimed at bolstering the reliability of a renewable energy resource, which is hybrid energy systems, through the application of a metaheuristic algorithm. The growing need for sustainable energy solutions underscores the importance of integrating various energy sources effectively. Concentrating on the intermittent characteristics of renewable sources, this study seeks to create a highly reliable hybrid energy system by combining photovoltaic (PV) and wind power.

To obtain efficient renewable energy resources, system designers aim to enhance the system’s reliability. Generally, for this purpose, the reliability redundancy allocation problem (RRAP) method is utilized. The authors have also introduced a new methodology, named Reliability Redundancy Allocation Problem with Component Mixing (RRAP-CM), for optimizing systems’ reliability. This method incorporates heterogeneous components to create a nonlinear mixed-integer mathematical model, classified as NP-hard problems. We employ specially crafted metaheuristic algorithms as optimization strategies to address these challenges and boost the overall system performance.

The study introduces six newly designed metaheuristic algorithms. Solve the optimization problem. When comparing results between the traditional RRAP method and the innovative RRAP-CM method, enhanced reliability is achieved through the blending of diverse components. The use of metaheuristic algorithms proves advantageous in identifying optimal configurations, ensuring resource efficiency and maximizing energy output in a hybrid energy system.

The study’s findings have significant social implications because they contribute to the renewable energy field. The proposed methodologies offer a flexible and reliable mechanism for enhancing the efficiency of hybrid energy systems. By addressing the intermittent nature of renewable sources, this research promotes the design of highly reliable sustainable energy solutions, potentially influencing global efforts towards a more environmentally friendly and reliable energy landscape.

The research provides practical insights by delivering a comprehensive analysis of a hybrid energy system incorporating both PV and wind components. Also, the use of metaheuristic algorithms aids in identifying optimal configurations, promoting resource efficiency and maximizing reliability. These practical insights contribute to advancing sustainable energy solutions and designing efficient, reliable hybrid energy systems.

This work is original as it combines the RRAP-CM methodology with six new robust metaheuristics, involving the integration of diverse components to enhance system reliability. The formulation of a nonlinear mixed-integer mathematical model adds complexity, categorizing it as an NP-hard problem. We have developed six new metaheuristic algorithms. Designed specifically for optimization in hybrid energy systems, this further highlights the uniqueness of this approach to research.

A standalone microgrid (MG) is able to use local renewable resources and reduce the loss in long distance transmission. But the single-phase device in a standalone MG can cause the voltage unbalance condition and additional power loss that reduces the cycle life of battery. This paper proposes an energy management strategy for the battery/supercapacitor (SC) hybrid energy storage system (HESS) to improve the transient performance of bus voltage under unbalanced load condition in a standalone AC microgrid (MG).

The SC has high power density and much more cycling times than battery and thus to be controlled to absorb the transient and unbalanced active power as well as the reactive power under unbalanced condition. Under the proposed energy management design, the battery only needs to generate balanced power to balance the steady state power demand. The energy management strategy for battery/SC HESS in a standalone AC MG is validated in simulation study using PSCAD/EMTDC.

The results show that the energy management strategy of HESS maintains the bus voltage and eliminates the unbalance condition under single-phase load. In addition, with the SC to absorb the reactive power and unbalanced active power, the unnecessary power loss in battery is reduced with shown less accumulate depth of discharge and higher average efficiency.

With this technology, the service life of the HESS can be extended and the total cost can be reduced.

The wind speed is very fluctuant and contains a significant energy. Taking into account the turbulent component in the energy management would increase the profitability of the wind‐diesel hybrid system. Sometimes, a diesel generator is used to compensate the requested energy but the storage devices are required to prevent disturbances induced by the wind generator current on the DC‐bus. The purpose of this paper is to show how the battery and flywheel (or ultracapacitors (UCs)) are used to mitigate the fluctuations of the wind generator current. The proposed method is based on the filtering of the wind generator current. The high power density sources (flywheel and UCs) are used in aims to improve the batteries' lifetime, which is estimated, in this paper, by using the rainflow cycles counting method. Spectral studies are made and the simulation and experimental results are analyzed.

This study is organized according to the following main and sub‐topics: wind speed characteristics, hybrid system energy management, behavioral simulations results, spectral analysis and batteries' lifetime estimation and experimental setup and results.

The simulations results highlight the interest in using a second‐order filter. The experimental results show that the fluctuations induced by the wind generator current are effectively mitigated by the storage devices.

The spectral analysis of the current for different filters parameters is realized and the application of the rainflow cycles counting method, in this context, is presented. This paper is interesting for the experimental hybrid system design according to the method proposed to control the DC‐DC converters.

The purpose of this paper is to propose and compare two energy management strategies (EMSs). First, a classic method based on frequency separation with fixed limits on fuel cell (FC) power is presented and tested. Then, the improvement of the classic strategy is developed and implemented when the main enhancements are its ease of implementation, hydrogen economy and extending hybrid source lifetime.

The proposed EMS is developed using an online variable power limitation of the FC depending on the battery state of charge while ensuring that the energy of batteries remains in its operating depth of discharge (DOD) range.

In the objective to show the benefits of the developed strategy, a comparative analysis was conducted between two strategies. The simulation and experimental results show the effectiveness and gains obtained by the improved energy management system (IEMS) in terms of fuel economy (13 per cent) and decreasing the applied stress on the FC (22 per cent) which leads to a longer life span of the whole system.

The proposed approach is developed and tested by simulation. To confirm it, a test bench has been assembled as hardware in the loop (HIL) real-time system. The presented experimental results confirm the efficiency and show the providing gains of the IEMS.

This paper aims to deal with the integration of energy storage devices (ultracapacitors) in wind energy applications to absorb the short terms fluctuations. The originality of this contribution is focused on energy management related to wind power frequency distribution between the hybrid sources. The robust and simplified control strategies are proposed and applied to DC‐DC converters without AC signals measurements. A novel MPPT method is introduced to operate the wind generator at the maximum power regardless of the wind speed variations. The fluctuating part of this power is mitigated by using a UC. The reference current of this last is obtained from a low pass filter. An innovative limitation algorithm of the UC voltage is proposed with aims to ensure optimal operation of the system. The control algorithms are implemented in a PIC18F4431 microcontroller. Some experimental results from this new approach are presented and analyzed.

This study is organized according to the following main and sub‐topics after introduction: frequency distribution principle; wind energy generation; short‐term fluctuations storage system; and experimental setup and results.

The simulations results highlight the interest of using ultracapacitors in a wind‐diesel system. The experimental results show that the short term fluctuations induced by the wind generator current are effectively mitigated by the ultracapacitors.

In this paper, an interesting MPPT method is presented. The fluctuations mitigation is realised by using the frequency distribution according to ultracapacitors dynamics. The ultracapacitors voltage control method is proposed with the aim of maintaining optimal operation conditions, and is validated by experimental tests.

This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions.

The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems.

The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints.

The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs.

This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.

The purpose of studying the low voltage direct current (DC) microgrid, which uses computerised control system techniques, an orderly coordination control stratagem considering optimisation of a hybrid energy storage system (HESS) was projected in this paper.

The projected control stratagem was divided into three levels: topmost power dispatch level, transitional bus voltage regulation level and bottommost converter control level.

At the topmost power dispatch level, the cost of system stability was introduced, which is related with state of charge and discharging power of HESS.

Furthermore, the cost of system stability and HESS depreciation was compared with commercial price, and HESS switches its operating mode to discharge more at higher price or charge more at lower price to ensure the DC microgrid in economic operation. At the transitional bus voltage regulation level, DC bus gesturing is used as a control signal to achieve an autonomous decentralised operation of DC microgrid. The Matlab/Simulink simulation inveterate that the economical and autonomous decentralised operation can be achieved through the control stratagem.

The purpose of the paper is to develop high accurate and unified maximum power point tracking technique that tracks the maximum power from both the photovoltaic (PV) array and wind energy conversion system, (an unified maximum power point tracking technique implemented for both wind and solar sources to track maximum power with higher accuracy).

In recent times, multi-input Direct Current- Direct Current (DC-DC) converter has attracted attentiveness, to conserve more energy and to achieve more efficiency. The kinetic energy of the vehicle is converted to electrical energy and further stored into the battery, during the regenerative braking (moreover, the battery gets charged during the regenerative braking process by converting the kinetic energy of the vehicle into electrical energy). During such a process, only the pulse width modulation schemes of the inverter are changed. To charge electric vehicles (EVs), two renewable resources as solar and wind are combined to produce electric power. Therefore, it was conveyed that the EV will be continuously getting power without interruption using various sources and regenerated power.

The performance and effectiveness of the proposed system are studied by extensive simulations and (are) validated using a prototype of the system. The results prove that the proposed system achieves an efficiency of 95.2%, which is higher than that of the multi-input DC-DC converters existing in the literature.

A novel multi-input DC-DC landsman converter for powering plug-in hybrid electric vehicles (HEVs) is proposed in the research. This method proposes a new cost effective and efficient technique for HEVs with brushless DC motors. Wind power, battery and PV panel are used as the input sources for the proposed converter.