The evolving global landscape for electrical distribution and use created a need area for energy storage systems (ESS), making them among the fastest growing electrical power system products. A key element in any energy storage system is the capability to monitor, control, and optimize performance of an individual or multiple battery modules in an energy storage system and the ability to control the disconnection of the module(s) from the system in the event of abnormal conditions. This management scheme is known as “battery management system (BMS)”, which is one of the essential units in electrical equipment. BMS reacts with external events, as well with as an internal event. It is used to improve the battery performance with proper safety measures within a system. Therefore, a safe BMS is the prerequisite for operating an electrical system. This report analyzes the details of BMS for electric transportation and large-scale (stationary) energy storage. The analysis includes different aspects of BMS covering testing, component, functionalities, topology, operation, architecture, and BMS safety aspects. Additionally, current related standards and codes related to BMS are also reviewed. The report investigates BMS safety aspects, battery technology, regulation needs, and offer recommendations. It further studies current gaps in respect to the safety requirements and performance requirements of BMS by focusing mainly on the electric transportation and stationary application. The report further provides a framework for developing a new standard on BMS, especially on BMS safety and operational risk. In conclusion, four main areas of (1) BMS construction, (2) Operation Parameters, (3) BMS Integration, and (4) Installation for improvement of BMS safety and performance are identified, and detailed recommendations were provided for each area. It is recommended that a technical review of the BMS be performed for transportation electrification and large-scale (stationary) applications. A comprehensive evaluation of the components, architectures, and safety risks applicable to BMS operation is also presented.

Renewable energy sources (RESs) play an indispensable role in sustainable advancement by reducing greenhouse gas (GHG) emissions. Nevertheless, due to the shortcomings of RESs, an energy mix with RESs is required to support the baseload and to avoid the effects of RES variability. Fossil fuel-based thermal generators (FFTGs), like diesel generators, have been used with RESs to support the baseload. However, using FFTGs with RESs is not a good option to reduce GHG emissions. Hence, the small-scale nuclear power plant (NPPs), such as the micro-modular reactor (MMR), have become a modern alternative to FFTGs. In this paper, the authors have investigated five different hybrid energy systems (HES) with combined heat and power (CHP), named ‘conventional small-scale fossil fuel-based thermal energy system,’ ‘small-scale stand-alone RESs-based energy system,’ ‘conventional small-scale fossil fuel-based thermal and RESs-based HES,’ ‘small-scale stand-alone nuclear energy system,’ and ‘nuclear-renewable micro hybrid energy system (N-R MHES),’ respectively, in terms of net present cost (NPC), cost of energy (COE), and GHG emissions. A sensitivity analysis was also conducted to identify the impact of the different variables on the systems. The results reveal that the N-R MHES could be the most suitable scheme for decarbonization and sustainable energy solutions.

To minimize the anticipated shocks to economic, environmental, and social systems for developing and least developed countries, the reduction of Greenhouse Gas (GHG) emissions is mandatory to a large extend. The nuclear-renewable integrated system is proficient in optimal energy distribution to multiple production schemes to reduce GHG emissions and maximize profit. This paper addresses the hybridization of the micronuclear reactor and Renewable Energy Sources (RESs) Energy Sources (RESs) to develop a flexible, cost-effective, sustainable, and resilient off-grid Hybrid Energy System (HES). The paper presents three types of hybridization methods, termed "Direct Coupling," "Single Resource and Multiple products-based Coupling," and "Multiple Resources and Multiple products-based Coupling." The hybridization techniques are used to plan and identify the most efficient Nuclear-Renewable Micro-Hybrid Energy System (N-R MHES). The sizing, performance, and characterization of N-R MHES solely depend on the RES and load characteristics' availability. Based on proposed hybridization techniques, mathematical modeling of N-R MHES's economy is carried out in the MATLAB environment. An artificial intelligence optimization algorithm, namely Particle Swarm Optimization (PSO), is used to minimize the Net Present Cost (NPC) and achieve the optimal system configurations of different N-R MHESs. The simulation results determine that "Multiple Resources and Multiple Products-based N-R MHES" provides around 1.8 times and 1.3 times lower NPC than "Single Resource and Multiple products-based Coupling" and "Multiple Resources and Multiple products-based Coupling," respectively, with an acceptable margin of reliability. A sensitivity analysis has also been conducted in this paper to strengthen the findings of the study.

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Resilient operation of medium/large scale off-grid energy systems, which is a key challenge for energy crisis solutions, requires continuous and sustainable energy resources. Conventionally, micro energy grids (MEGs) are adopted to supply electricity and thermal energy simultaneously. Fossil-fired gensets, such as diesel generators, are indispensable components for off-grid MEGs due to the intermittent nature of renewable energy sources (RESs). However, fossil-fired gensets emit a significant amount of greenhouse gases (GHGs). Therefore, this study investigates an alternative source as an economical and environmental replacement for diesel gensets that can reduce GHG emissions and ensure system reliability. A MEG is developed in this paper to support a considerably large-scale electric and thermal demand at Ontario Tech University (UOIT). Different sizes of diesel gensets and RESs, such as solar, wind, hydro, and biomass, are combined in the MEG for off-grid applications. To evaluate diesel gensets’ competency, the diesel genset is substituted by an emission-free generation source named microreactor (MR). The fossil-fired MEG and MR-based MEG are optimized by an intelligent optimization technique, namely particle swarm optimization (PSO). The objective of the PSO is to minimize the net present cost (NPC). The simulation results show that MR-based MEG could be an excellent replacement for a diesel genset in terms of NPC and selected key performance indicators (KPIs). A comprehensive sensitivity analysis is also carried out to validate the simulation results.

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Ocean-going ships are one of the primary sources of Greenhouse Gas (GHG) emissions. Several actions are being taken to reduce the GHG emissions from maritime vessels, and integration of Renewable Energy Sources (RESs) is one of them. Ocean-going marine ships need a large amount of reliable energy to support the propulsive load. Intermittency is one of the drawbacks of RESs, and penetration of RESs in maritime vessels is limited by the cargo carrying capacity and usable area of that ship. Other types of reliable energy sources need to be incorporated in ships to overcome these shortcomings of RESs. Some researchers proposed to integrate fossil fuel-based generators like diesel generators and renewable energy in marine vessels to reduce GHG emissions. As the penetration of RESs in marine ships is limited, fossil fuel-based generators provide most of the energy. Therefore, renewable and fossil fuel-based hybrid energy systems in maritime vessels can not reduce GHG emissions to the desired level. Fossil fuel-based generators need to be replaced by emissions-free energy sources to make marine ships free from emissions. Nuclear energy is emissions-free energy, and small-scale nuclear reactors like Microreactors (MRs) are competent to replace fossil fuel-based generators. In this paper, the technical, environmental, and economic competitiveness of Nuclear-Renewable Hybrid Energy Systems (N-R HES) in marine ships are assessed. The lifecycle cost of MR, reliability of the proposed system, and limitations of integrating renewable energy in maritime vessels are considered in this study. The proposed N-R HES is compared with three different energy systems, namely ‘Standalone Fossil Fuel-based Energy Systems’, ‘Renewable and Fossil Fuel-based Hybrid Energy Systems’, and ‘Standalone Nuclear Energy System’. The cost modeling of each energy system is carried out in MATLAB simulator. Each energy system is optimized by using the Differential Evolution Algorithm (DEA), an artificial intelligence algorithm, to find out the optimal configuration of the system components in terms of Net Present Cost (NPC). The results determine that N-R HES has the lowest NPC compared to the other three energy systems. The performance of the DE algorithm is compared with another widely accepted artificial intelligence optimization technique called ‘Particle Swarm Optimization (PSO)’ to validate the findings of the DE algorithm. The impact of control parameters in the DE algorithm is assessed by employing the Adaptive Differential Evolution (ADE) algorithm. A sensitivity analysis is carried out to assess the impact of different system parameters on this study’s findings.