The worldwide demand for reduction of CO2 pollution, with more penetration of renewable energy sources and an increased number of electric vehicles (EVs), demonstrates the importance of economic dispatch (ED) with taking into account the reduction of CO2 emission. ED is a classical problem in which EVs impose more penetration as a dynamic load, and its impact as vehicle-to-grid (V2G) is the possible future trend with cost minimization. Based on the integration of EVs and hybrid renewable sources concerning both economic dispatch and pollution minimization, the multi-objective function is converted into a single comprehensive objective by using the judgment matrix methodology. In this paper, the investigation involves the minimization of the cost of all three objectives viz. operation cost, pollution cost, and carbon emissions with ED by incorporating V2G technology. The algorithms which include particle swarm optimization, as well as artificial bee colony, are applied under various operation and control strategies. The proposed models are verified and analyzed with different case studies. In terms of operation economics, the simulation results validate the superior performance of EVs based microgrid (MG) model in the coordinated charging and discharging mode. Further, the comparison of both algorithms shows better results with the ABC algorithm in terms of cost minimization of all objectives. ABC is better in V2G based microgrid with coordinated charging and discharging mode while its performance is significant during a large number of EVs (i.e., 700 EVs). Moreover, the load shedding scenarios are integrated which enables the MG system to operate in dual mode (i.e., seamless transition). In this paper, the main contribution involves penetration of EVs as dynamic load and its V2G impact in a coordinated or uncoordinated way, application of ABC algorithm for this particular load problem with improved results, and inclusion of short-term load shedding scenarios.

Microgrids being an important entity in the distribution system, and to get their full advantages by incorporating maximum distributed generation, standalone hybrid renewable energy systems (HRESs), being environmentally-safe and economically-efficient, are considered as the promising solution to electrify remote areas where the grid power is not available. In this work, a techno-economic investigation with an optimal design of HRES is presented to fulfill the domestic electricity need for a residential area of the Sherani district in the Province of Baluchistan, Pakistan. Nine case studies based on PV/wind/diesel/battery are analyzed based on net present cost (NPC), cost of energy (COE), and emission to decide the feasible solution. HOMER tool is utilized to accomplish modeling and simulation for economic analysis and optimal sizing. Simulation results demonstrated that HRES with PV-wind-battery is the most viable option for the specified area, and the optimal sizing of components are also obtained with $ 28,620 NPC and 0.311 $/kWh COE which shows 81.65% reduction in cost and 100% preserving in toxic emission while fulfilling 100% energy demand with 67.3% of excess energy. Furthermore, MATLAB/Simulink modeling for the optimally designed system is built for technical analysis while its effectiveness is proved by keeping dc and ac buses voltage constant, safe operating range of battery state of charge (SOC) with active power balance between HRES components, as well as efficient ac voltage quality, regardless of generation disturbances and load fluctuations. The output signal has total harmonic distortion (THD) of 0.30% as compared to 5.44% with the conventional control scheme. The novelty lies in the sequential application of both HOMER and MATLAB simulations of the proposed HRES model and validation of the proposition for the studied area; by using and implementing model predictive control (MPC) of a reconfigurable inverter.

Wind energy is one of the most attractive sustainable energy resources since it has low operation, maintenance, and production costs and a relatively low impact on the environment. Identifying the optimal sites for installing wind power plants (WPPs) is considered an important challenge of wind energy development which requires careful and combined analyses of numerous criteria. This study introduces a high-resolution wind farms suitability mapping based on Fuzzy Analytical Hierarchy Process (FAHP) and Geographic Information System (GIS) approaches considering technical, environmental, social, and spatial aspects, representing eight different criteria. First, a multi-criteria decision-making analysis based on the FAHP method is employed to assign appropriate weights for the addressed criteria with respect to their relative importance. Since the traditional AHP method, which was found employed in the majority of the relative case-studies, is not efficient in dealing with uncertainty when experts use a basic scale (0 to 1) for their assessments, the FAHP provides more flexible scales through the utilized fuzzy membership functions and the natural linguistic variables. Consequently, this helps to facilitate the assessments made by experts and increases the precision of the obtained results (weights). Next, the high-resolution GIS is used to carry out a spatial analysis and integrate various factors/criteria throughout the proposed index to produce the final suitability map and identify the unsuitable areas. The presented study emphasizes investigating the lightning strike flash rate due to its significant influences on the wind turbine’s safety and operation, yet this crucial factor has been seldomly investigated in previous studies. The obtained findings revealed that the wind speed, the land slope, and the elevation had the highest weighted criteria with 33.1%, 24.8%, and 12.2%, respectively. Besides, the final-developed suitability map revealed that 23.22% and 8.31% of the Sudanese territory are of high and very high suitability, respectively, for wind farms installation which are considered sufficient to cover the electricity needs. The difficulty of acquiring real data and resources for the addressed location was the main challenge of the presented work. The work outlook addresses the suitability mapping of hybrid photovoltaic-wind turbine energy systems, which will require addressing new and significant criteria in the applied methodology.