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This comprehensive review article illuminates Morocco's proactive response to climate change challenges over the past decades. Faced with drought episodes akin to other Mediterranean countries, Morocco contends with significant water stress, boasting limited water resources estimated at 20 billion cubic meters and an annual per capita consumption of 700 m3. The country experiences a temperature surge of 0.3–2.5 °C, coupled with decreased precipitation, heightening the impact of climate change on water resources. Morocco plans a 40 % reduction in emissions by 2030 (18.3 % unconditional, 27.2 % conditional on international aid) and an impressive 77 % decrease in emissions by 2050 compared to Business as Usual levels. The study offers a comprehensive, groundbreaking analysis, representing the first comprehensive review of Morocco's low-carbon strategy and energy initiatives. It meticulously examines 155 research papers through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, categorizing solutions into engineering and managerial domains. Covering power, transport, building, industry, and agriculture, the article provides a taxonomy of engineering solutions, including renewable energy, energy auditing, efficiency, sufficiency, and digitalization of management. Simultaneously, managerial solutions, ranging from education to subsidies and policy reforms, are detailed. These solutions contribute to Morocco's standing as a leader in climate action and clean energy transition. Despite these significant contributions, the article acknowledges potential limitations, including reliance on available literature and regional variations in solution applicability. Nonetheless, it serves as a foundational resource for understanding Morocco's endeavors in addressing climate change and promoting sustainable energy practices.

This study conducts a well-to-wheel assessment of alternative fuel vehicles in the Maghreb region, aiming to reduce greenhouse gas emissions from the transport sector. The research employs international standards, ISO 14040–14043, to assess diesel, hybrid-electric, battery-electric, and fuel-cell vehicles and highlights the potential benefits of transitioning to electric and fuel-cell vehicles in the Maghreb, offering energy efficiency and reduced environmental impact.The sensitivity analysis suggests that fuel-cell vehicles are the best alternative for Morocco and Algeria, while battery-electric vehicles are preferable in Tunisia. By 2030, fuel-cell vehicles in Morocco and Algeria would consume 128 ​MJ and 125 ​MJ and emit 7.9 CO2eq and 7.1 CO2eq emissions per 100 ​km, respectively, while in Tunisia, battery-electric vehicles are expected to consume 114 ​MJ and emit 6.55 CO2eq emissions per 100 ​km driven. Ultimately, the right adoption of alternative fuel vehicles in the Maghreb region implies half energy need cut off and 60% less GHG emissions from light-duty vehicles leading to improved environmental conditions, health outcomes, and economic growth.

One-third of all greenhouse gas emissions come from the world's building stock while accounting for 40% of global energy use. There is no way to combat global warming or attain energy independence without addressing the inefficiency of the building sector. This sector is the second consumer of electricity after the industrial sector in Morocco and is ranked third emitter after the energy sector and transportation sector. Using Ifrane as a case study, this paper examines and reviews the city's energy use and the initiatives taken to improve building efficiency. The findings showed that, during the analyzed period, i.e., from 2014 to 2022, Ifrane's annual electricity consumption climbed steadily from 35 to 43 GWh. The government of Morocco has implemented effective laws, guidelines and regulations, as well as publicized ways to reduce energy consumption and increase energy efficiency. However, gathered data and survey results revealed opportunities and challenges for enhancing Ifrane's efficient energy use. The study also evaluates government programs, codes/standards and related actions for the improvement of household energy efficiency. As part of the review, the available literature was analyzed to assess the effectiveness of energy behavior and awareness, the impact of an economical and sustainable building envelope, the impact of building retrofitting programs, the importance of energy-performing devices and appliances, the adoption of smart home energy management systems, the integration of renewable energies for on-site clean energy generation and the role of policies and governance in the building sector in Ifrane. A benchmark evaluation and potential ideas are offered to guide energy policies and improve energy efficiency in Ifrane and other cities within the same climate zone.

This research presents the first comprehensive model for social assessment of alternative fuel vehicles, covering hybrid-electric, battery-electric, and fuel-cell vehicles, based on their technological, financial, and infrastructure aspects. The model is adaptable to any country and does not require social engagement methods, thus producing more objective results. Indicators are assessed case-by-case and receive a score from zero to five. Lower scores show a greater need for prioritizing the indicator when adopting a specific alternative fuel vehicle. A low score doesn’t mean a low impact, but instead emphasizes the importance of improving the relevant indicator for the particular vehicle technology in the studied region. The case study conducted in Morocco tested the model, highlighting the superior performance of hybrid-electric vehicles based on their score. Although these vehicles offer financial profitability, their successful adoption relies on the government’s provision of more options, reduced purchase costs, and improved secondary road infrastructure. Battery-electric vehicles, while facing challenges in terms of maintenance and charging infrastructure, can be addressed in Morocco by implementing on-site generation in charging stations and enhancing secondary road infrastructure. On the other hand, fuel-cell vehicles have notable social requirements and necessitate more extensive efforts to penetrate the market compared to battery-electric vehicles. Finally, the authors suggest including more alternative fuel vehicles in the model and additional social variables, such as user experience, vehicle size, fuel efficiency, environmental awareness, purchasing behavior, and brand loyalty. The suggestion would allow gaining more insight into social preferences.

This paper introduces a comprehensive approach for sizing grid-connected hybrid renewable energy systems tailored for electric bus fleet operations. The study involves two main steps. First, a mathematical model that optimizes the configuration of such systems by considering daily electric bus consumption, solar irradiance, wind speed, and biomass potential is formulated. The model utilizes Pareto frontier multi-objective optimization to minimize the net present cost, the cost of energy, and greenhouse gas emissions. Second, the model is rigorously applied and tested in a real-world case study in Fez, Morocco, using HOMER Pro; the case study centers on the daily energy requirements of the buses, estimated at 2.5 megawatt hours per day, with a peak demand of 345 kilowatts. Two scenarios are explored, revealing a discernible trade-off dilemma between the full hybrid renewable energy scenario (Scenario 1) and the grid-connected hybrid renewable energy scenario (Scenario 2). In Scenario 2, the grid-connected hybrid renewable energy system demonstrates a notable 42.8% reduction in the net present cost, totaling USD 984,624. Similarly, the levelized cost of energy experiences a significant decrease, reaching approximately 0.08 USD/kWh, marking a 38.1% reduction. However, this apparent economic advantage is juxtaposed with a critical consideration—an increase in greenhouse gas emissions from null to 330,418 kg/year.

This research delves into the intricate landscape of energy scheduling and optimization within microgrid and residential contexts, addressing pivotal aspects such as real-time scheduling systems, challenges in dynamic pricing, and an array of optimization strategies. This paper introduces a cutting-edge scheduling algorithm, harnessing the power of artificial neural networks driven by Long Short-Term Memory Networks, and highlights its exceptional performance, boasting a significantly lower Mean Absolute Error of 5.32 compared to conventional models. This heightened predictive accuracy translates into tangible improvements in both energy efficiency and cost savings. This study underscores the delicate balance between user satisfaction, cost reduction, and efficient scheduling for sustainable energy consumption, showcasing a remarkable 38% enhancement in optimized schedules. Further granularity revealed substantial gains in energy efficiency and cost reduction across different scheduling intensities: 11.11% in light schedules, 20.09% in medium schedules, and an impressive 38.85% in heavy schedules. However, this research does not shy away from highlighting challenges related to data quality, computational demands, and generalizability. Future research trajectories encompass the development of adaptive models tailored to diverse data qualities, enhancements in scalability for and adaptability to various microgrid configurations, the integration of real-time data, the accommodation of user preferences, the exploration of energy storage and renewables, and an imperative focus on enhancing algorithm transparency.

The transport sector is one of the main contributors to global CO2 emissions and the transport sector in the Kingdom of Morocco is no exception. To combat this, two important agreements aimed at reducing greenhouse gas emissions were created, the Paris Agreement and the Nationally Determined Contributions. The adoption of battery electric vehicles is one way of helping to reduce transport-related emissions. However, there are several barriers to the adoption of battery electric vehicles in Morocco. The objective of this paper is to identify these barriers and to propose solutions to overcome them based on a survey of 209 responses that were analyzed using the Smart-PLS 4 approach. The study found that the financial attributes, maintenance, design, social reinforcement, and lack of incentives related to battery electric vehicles are the most significant factors that could cause the hindrance of the adoption of battery electric vehicles. Therefore, more affordable and attractive battery electric vehicles should be made more accessible. Moreover, increased technical training facilities should be mobilized to boost further efforts and increase experience in the field of BEV maintenance in Morocco. By implementing these solutions, Morocco can increase the uptake of battery electric vehicles and reduce its greenhouse gas emissions. This will help Morocco reach its Nationally Determined Contributions and protect the environment as well as the health of its population.

The heavy reliance on petroleum-based fuels in the road transport industry, especially public transportation, results in substantial emissions of greenhouse gases. A significant obstacle on the path to a more sustainable public transportation sector is the employment of alternative fuels with lower environmental implications. Although there are several in-depth well-to-wheel studies for developed countries, extrapolating those results to gasoline markets in developing countries presents challenges because of significant differences in local fuel conditions and vehicle engine technologies. Notably, this study provides a national-level environmental life cycle assessment of alternative buses in Morocco and compares current diesel buses to potential hybrid diesel-electric buses, battery-electric buses, and fuel-cell buses from a well-to-wheel perspective. The model and approach used in this study applies to other countries with developing economies. Total energy consumption broken out by fuel type, greenhouse gas emissions, and criterion air pollutants is the primary outcome of this investigation. Findings highlight an energy cut of 44.7% from battery-electric buses, 36.3% from fuel-cell buses, and 31.7% from hybrid buses with regard to the current diesel buses. Additionally, alternative fuel buses proved to be less polluting in terms of greenhouse gas emissions with 50.8% less from battery-electric buses, 46.7% less from fuel-cell buses, and 26.8% less from hybrid buses; consequently, this would lead to reduced climate change, air pollution, acidification, and eutrophication, given the Egalitarian Environmental Impact Assessment. Ultimately, Morocco will have to tackle technological, financial, and institutional barriers to fully implement the change by 2030.

This paper proposes a home energy management system able to achieve optimized load scheduling for the operation of appliances within a given household. The system, based on the genetic algorithm, provides recommendations for the user to improve the way the energy needs of the home are handled. These recommendations not only take into account the dynamic pricing of electricity, but also the optimization for solar energy usage as well as user comfort. Historical data regarding the times at which the appliances have been used is leveraged through a statistical method to integrate the user’s preference into the algorithm. Based on real life appliance consumption data collected from a household in Morocco, three scenarios are established to assess the performance of the proposed system with each scenario having different parameters. Running the scenarios on the developed MATLAB script shows a cost saving of up to 63.48% as compared to a base scenario for a specific day. These results demonstrate that significant cost saving can be achieved while maintaining user comfort. The addition of supplementary shiftable loads (i.e., an electric vehicle) to the household as well as the limitations of such home energy management systems are discussed. The main contribution of this paper is the real data and including the user comfort as a metric in in the home energy management scheme.

Electric vehicles (EVs) are becoming more commonplace as they cut down on both fossil fuel use and pollution caused by the transportation sector. However, there are a number of major issues that have arisen as a result of the rapid expansion of electric vehicles, including an inadequate number of charging stations, uneven distribution, and excessive cost. The purpose of this study is to enable EV drivers to find charging stations within optimal distances while also taking into account economic, practical, geographical, and atmospheric considerations. This paper uses the Fez-Meknes region in Morocco as a case study to investigate potential solutions to the issues raised above. The scorching, arid climate of the region could be a deterrent to the widespread use of electric vehicles there. This article first attempts to construct a model of an EV battery on MATLAB/Simulink in order to create battery autonomy of the most widely used EV car in Morocco, taking into account weather, driving style, infrastructure, and traffic. Secondly, collected data from the region and simulation results were then employed to visualize the impact of ambient temperature on EV charging station location planning, and a genetic algorithm-based model for optimizing the placement of charging stations was developed in this research. With this method, EV charging station locations were initially generated under the influence of gas station locations, population and parking areas, and traffic, and eventually through mutation, the generated initial placements were optimized within the bounds of optimal cost, road width, power availability, and autonomy range and influence. The results are displayed to readers in a node-link network to help visually represent the impact of ambient temperatures on EV charging station location optimization and then are displayed in interactive GIS maps. Finally, conclusions and research prospects were provided.