Although the impact of integrating solar and wind sources into the power system has been studied in the past, the chaos caused by wind and solar energy generation has not yet had broader mitigation solutions notwithstanding their rapid deployment. Many research efforts in using prediction models have developed real-time monitoring of variability and machine learning predictive algorithms in contrast to the conventional methods of studying variability. This study focused on the causes and types of variability, challenges, and mitigation strategies used to minimize variability in grids worldwide. A summary of the top ten cases of countries that have successfully managed variability in their electrical power grids has been presented. Review shows that most of the success cases embraced advanced energy storage, grid upgrading, and flexible energy mix as key technological and economic strategies. A seven-point conceptual framework involving all energy stakeholders for managing variability in power system networks and increasing variable renewable energy (VRE)-grid integration has been proposed. Long-duration energy storage, virtual power plants (VPPs), smart grid infrastructure, cross-border interconnection, power-to-X, and grid flexibility are the key takeaways in achieving a reliable, resilient, and stable grid. This review provides a useful summary of up-to-date research information for researchers and industries investing in a renewable energy-intensive grid.

Electric vehicles (EVs) represent a promising green technology for mitigating environmental impacts. However, their widespread adoption has significant implications for management, monitoring, and control of power systems. The integration of renewable energy sources (RESs), commonly referred to as green energy sources or alternative energy sources, into the network infrastructure is a sustainable and effective approach to addressing these matters. This paper provides a comprehensive review of the integration of RESs and EVs into power systems. The bibliographic analysis revealed that IEEE Access had the highest impact among journals. In order to enhance the classification of the reviewed literature, we have provided an analytical summary of the contributions made by each paper. The categorization facilitated the recognition of the primary objectives explored in the reviewed works, including the classification of EVs and RESs, the incorporation of RESs and EVs into power systems with an emphasis on emissions, the establishment of EV charging stations and parking facilities, EV batteries and battery energy storage systems, strategies for managing the integration of RESs with EVs, EV aggregators, and the financial implications. In order to provide researchers with a valuable synopsis of the implementation particulars, the papers were bifurcated into two primary classifications, namely mathematical algorithms and heuristic algorithms. The mixed integer linear programming algorithm and particle swarm optimization algorithm were commonly utilized formulations in optimization. MATLAB/Simulink was the primary platform used for executing a considerable portion of these algorithms, with CPLEX being the dominant optimization tool. Finally, this study offers avenues for further discourse and investigation regarding areas of research that remain unexplored.

Microbial fuel cells (MFCs) have undergone great technological development in the last 20 years, but very little has been done to commercialize them. The simultaneous power production and wastewater treatment are features those greatly increase the interest in the use of MFCs. This kind of distributed power generation is renewable and friendly and can be easily integrated into a smart grid. However, there are some key issues with their commercialization: high construction costs, difficulty in developing high power structures, MFC lifespan, and maintaining a high level of efficiency. The objective of this article is to explore the possibilities of using MFCs in urban wastewater not only regarding the technical criteria of their application, but also mainly from an economic point of view, to determine the conditions through which the viability of the investment is ensured and the possibilities of their integration in a smart grid are identified. Initially, this article explores the implementation/configuration of a power plant with MFCs within an urban wastewater treatment plant on a theoretical basis. In addition, based on the corresponding physical quantities for urban wastewater treatment, the construction and operational costs are determined and the viability of the investment is examined based on classic economic criteria such as net present value, benefit–cost ratio, internal rate of return, and discounted payback period. Furthermore, sensitivity analysis is carried out, concerning both technical parameters, such as the percentage of organic matter removal, power density, sewage residence time, MFC efficiency, etc., and economical parameters, such as the reduction of construction costs due to change of materials, change of interest rate, and lifetime. The advantages and disadvantages of their use in smart grids is also analyzed. The results show that the use of MFCs for power generation cannot be utopian as long as they are integrated into the structure of a central wastewater treatment plant on the condition that the scale-up technical issues of MFCs are successfully addressed.

Energy communities constitute the main collective form for energy consumers to participate in the current energy transition. The purpose of this research paper is to present a tool that assists energy communities to achieve fair and sustainable daily operation. In this context, the proposed algorithm (i) assesses the day-ahead operation cost (or profit) of energy communities, taking into consideration photovoltaic (PV) production, battery energy storage system (BESS), and flexible loads, as well as the potential profit from selling energy to the power system, under the net billing scheme, and (ii) compares the derived cost for each member with the cost for non-cooperative operation, as single prosumers. Taking the aforementioned costs or profits into consideration, the developed algorithm then proposes three cost-sharing options for the members, peer-to-peer (P2P), so that their participation in the community is more beneficial than individual operation. The algorithm is tested on a hypothetical energy community in Greece, highlighting the importance of the cooperation amongst the members of the community for their mutual benefit; for the simulated case of different PV shares, the cooperation can result in a 24.5% cost decrease, while having a BESS can reduce the cost by 25.0%.