Sustainable Energy Systems: Planning, Integration and Management

The transition to a low carbon society is dependent on renewable energy-based electrification. Nevertheless, energy programs have resulted in growing societal polarization in several regions. Therefore, around the globe, government and legislative authorities at the local, regional, national, and international levels are highly concerned about the environmental impacts and risk factors that influence the energy paradigm. Thus, to minimize and/or limit the environmental insecurity issues, the world needs swift and effective actions to secure the climate for a better tomorrow. Moreover, there is a dire need to look for new energy alternatives, along with reducing the complete dependence on petro-based energy sources. Keeping this burning issue in mind, herein, an effort has been made to present the potential of several renewable energy sources, including wind-based renewable energy, solar-based renewable energy, hydro-based renewable energy, and biomass-based renewable energy. Following a brief introduction of energy-related problems and opportunities, a comparative overview is given to renewable vs. non-renewable energy sources. Then, several renewable energy sources, including wind, solar, hydro, and biomass, along with the worldwide energy capacity of each energy source are given with suitable examples and statistics. Finally, risk factors, concluding remarks, and future guidelines are discussed towards the end.

Importance of implementing smart renewable energy system using heuristic neural decision support system

Maximum Power Point Tracking (MPPT) approaches are used to optimize the design and analysis of a microgrid that integrates wind and photovoltaic (PV) energy sources. The suggested microgrid uses MPPT algorithms to optimize power extraction from PV panels and wind turbines under various climatic circumstances, improving energy efficiency and dependability. The system adapts dynamically to variations in wind speed and sun irradiation, guaranteeing better energy collection and optimal operation. The effectiveness of the MPPT-based control technique in preserving steady grid functioning and optimizing the use of renewable energy sources is assessed through simulation simulations. According to the results, the system can handle the intermittent nature of wind and photovoltaic energy, guaranteeing grid stability and a steady supply of power. In order to improve system resilience, the study also examines the operational and technological difficulties associated with incorporating renewable energy sources into microgrids. The results highlight how MPPT-enabled microgrids can help sustainable energy systems and provide a strong foundation for the incorporation of renewable energy in the future. By offering insights into the design and optimization of hybrid renewable energy systems for dependable and effective power generation, this work advances microgrid technology.

A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea

Investment in renewable energy strengthens economic security by diversifying energy sources, reducing dependence on imports, and fostering sustainable development. The transition to renewable energy sources (RES) is a priority for many countries, ensuring energy independence and mitigating environmental harm. Green investments have gained importance amid global energy instability, climate change, and economic risks. Developing RES requires substantial financial resources, making an attractive investment climate and effective financial mechanisms essential. Global challenges such as the energy crisis, geopolitical tensions, and resource depletion accelerate the search for alternatives. Governments, financial institutions, and private investors play a key role in expanding the sector, but investment levels depend on regulatory policies, tax incentives, and technological advancements that improve efficiency and cost-effectiveness. This article examines investment trends in renewable energy and their impact on economic security. It analyzes global and national investment dynamics, highlighting key drivers and obstacles. The main sources of financing—state subsidies, private capital, international grants, and public-private partnerships—are explored. Special attention is given to investment stimulation mechanisms, such as preferential loans, green bonds, and carbon credit systems. Key factors influencing investment growth, including government policies, tax incentives, and technological innovation, are identified. State support, such as feed-in tariffs and investment guarantees, significantly impacts investor decisions. Advancements in energy storage, smart grids, and hydrogen energy enhance RES attractiveness. The role of financial institutions in sustainable investment, including green funds and ESG criteria, is also discussed. The article examines debt financing in the energy sector and sustainable financial structures. The growing share of green bonds and climate-related financial instruments reflects increasing commitments to renewable energy. The risks and benefits of financing models, such as project financing and venture capital, are assessed. Investing in renewable energy reduces environmental impact while enhancing social security and economic stability. This sector fosters social entrepreneurship, creating jobs and supporting sustainable development through innovation and international cooperation. The findings support strategies to attract investment and strengthen Ukraine’s energy security. Expanding RES and adapting international best practices are crucial for a resilient and sustainable energy system.

Learning from nature for healthcare, energy, and environment

Recently, renewable energy (RE) has become popular due to its benefits, such as being inexpensive, low-carbon, ecologically friendly, steady, and reliable. The RE sources are gradually combined with non-renewable energy (NRE) sources into electric grids to satisfy energy demands. Since energy utilization is highly related to national energy policy, energy prediction using artificial intelligence (AI) and deep learning (DL) based models can be employed for energy prediction on RE and NRE power resources. Predicting energy consumption of RE and NRE sources using effective models becomes necessary. With this motivation, this study presents a new multimodal fusion-based predictive tool for energy consumption prediction (MDLFM-ECP) of RE and NRE power sources. Actual data may influence the prediction performance of the results in prediction approaches. The proposed MDLFM-ECP technique involves pre-processing, fusion-based prediction, and hyperparameter optimization. In addition, the MDLFM-ECP technique involves the fusion of four deep learning (DL) models, namely long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), deep belief network (DBN), and gated recurrent unit (GRU). Moreover, the chaotic cat swarm optimization (CCSO) algorithm is applied to tune the hyperparameters of the DL models. The design of the CCSO algorithm for optimal hyperparameter tuning of the DL models, showing the novelty of the work. A series of simulations took place to validate the superior performance of the proposed method, and the simulation outcome emphasized the improved results of the MDLFM-ECP technique over the recent approaches with minimum overall mean absolute percentage error of 3.58%.

Renewable energy (RE) has been identified as an appropriate response to climate change and fossil fuel depletion by many governmental bodies. It has shifted the energy industry towards renewable and sustainable energy systems over the last few decades. This expansion has also increased the demand of specialists for design, installation and maintenance of different RE systems. Most people working in this sector are not well trained or educated enough whereas some of them are not even aware of sustainability. This has shifted towards formulation, model, develop and incorporation of new courses and programmes that would provide sufficient knowledge and skill in the sustainable RE sector. Moreover, the implementation of these new RE courses shouldn’t be limited to engineering level but also focuses on providing basic knowledge to everyone working in this field. Hence, in the present study, two-course structures have been suggested, i.e. general course which would offer basic knowledge and awareness of different RE systems in school level (including primary, elementary, intermediate and secondary) and in the professional programmes (Industrial Training Institute (ITI), diploma, undergraduate, postgraduate and research). Moreover, adequate knowledge would be provided not only in the theoretical field but also in the practical field depending upon the level of programme. Furthermore, undergraduate, postgraduate and research levels students would be provided with a broad knowledge of science, engineering design, planning and implementation of RE systems, while ITI and diploma level would acquire skill development and training in the RE systems.

This paper studies the dc power supply system to combine with the hybrid renewable energy sources. A multi-input power converter (MIPC) which operates in four types: an operation type wherein power is delivered to dc Bus from hybrid renewable energy sources; a single type wherein only one renewable energy source supplies power to the dc Bus; an inverter type wherein power is delivered to dc Bus from ac grid via inverter module, and a battery type wherein power is delivered to dc Bus from batteries without renewable energy source. In this paper, the integration of the dc Bus and a hybrid renewable power supply system is proposed. A hybrid renewable power energy which integrates the solar energy, wind-power, and city power, etc will be exploited to supply the household appliance and loads.

To meet the fast-growing energy demand and manage the distributed resource, an intelligent energy management system plays a vital role in the electric power system. The next-generation electric power system, known as the smart grid, will incorporate a large number of renewable energy resources that fundamentally change the energy management paradigm. To manage efficiently the energy supply and demand in the power grid, further improvement in the reliability and efficiency of electrical grids can be achieved by utilizing dc distribution in microgrid systems. DC microgrid is an attractive technology in the modern electrical grid system because of its natural interface with renewable energy sources, electric loads (e.g. data center load, electrical vehicle charging load, residential dc load), solid state transformer and energy storage systems. In this paper we discussed the functional expectation of the dc microgrid, system architecture, communication structure and distributed grid intelligent system. This paper highlights the recent technology update in dc microgrid system. This paper also discusses benefits and challenges of using dc grid.

Researchers have found that despite a wide range of renewable energy sources in sub-Saharan Africa (SSA), renewable energy pricing policies have focused extensively on metered electricity energy, an early source of renewable energy. Supply, access, and regulation of price for metered electricity energy is mostly controlled by the governments across SSA. There is an increasing use of other renewable energy sources including portable electricity, solar power, and wind power. However, in SSA, the pricing for domestic renewable domestic renewable power such as portable electricity, rechargeable cookstoves, and portable solar power sources are left to the market to legislate, with energy prices dependent on forces of demand and supply and seldom on clear scientific models. This commercially focused energy market means businesses operating in the energy industry are more interested in profits and set prices relative to their market perceptions. The main problem with the energy market in SSA is the lack of a participatory approach where customers, businesses, the government, and other stakeholders are involved in the pricing for energy. We further note that lack of a participatory approach in energy pricing is a major challenge in uptake and demand for the domestic renewable energy sources. Through a systematic literature review, including a review of peer-reviewed journals, documents from energy utility companies, and published information on the websites for energy companies, this review analyzes the current application of energy price modeling and hypothesizes that mobile technology and a participatory pricing approach can improve pricing for domestic renewable power. Our initial literature review showed that energy price modeling had received little attention in SSA, especially for domestic renewable power energy sources. This paper, therefore, fills this gap by using a systematic literature review to consolidate knowledge on how energy price modeling has been applied in the SSA context. The systematic literature review results reveal four commonly used models: time series, artificial neural network, hybrid iterative reactive adaptive, and hybrid models. These energy pricing models are mainly applied to metered electricity power, the predominant source of energy in SSA. The literature hypothesizes that applying mobile technology to energy pricing and a participatory approach involving the consumers and energy supply businesses can move SSA closer to transitioning to renewable energy. Although other factors have hindered this transition, a participatory energy pricing approach incorporating relevant pricing models and market information creates potential solutions to these challenges. In the discussion, we hypothesize that a participatory approach to price modeling with the incorporation of mobile technology can be used at the household level to improve energy decision-making. For this to work, energy price modeling for domestic renewable sources should be simplified, user-friendly, and accessible to households. In conclusion, we recommend that SSA governments develop a more holistic view of energy price modeling to better harness the potential for domestic renewable energy sources.

This review critically analyzes the design of sustainable energy systems implemented on islands and beyond. It emphasizes the importance of integrating renewable and non-renewable energy sources to enhance energy output in hybrid systems. Due to the Island's unique geographical and environmental characteristics, islands face distinct energy supply and sustainability challenges. The review examines different aspects of sustainable energy system design, such as renewable energy sources, energy storage solutions, grid integration, and policy frameworks. Hence, by synthesizing current research and case studies, this review aims to provide insights into effective strategies for designing sustainable energy systems that are specifically tailored to the needs and constraints of islands. This paper detailed the critical role of renewable energy sources such as solar, wind, hydro, and biomass in driving sustainability in island communities and urges energy stakeholders and policymakers to embrace their potential to effectively energize rural and underprivileged areas

Concept of renewable hybrid energy systems have attracted many utilities and implemented by them too. With such energy systems, customers are not only supplied more economically but also more reliably. Moreover, optimal placements of energy storage systems (ESSs) increase the reliability of such hybrid renewable system up to a great extent. Therefore, this paper presents a new approach for optimal placement and sizing of energy storage systems (ESSs) in hybrid renewable radial distribution system to improve the reliability of such system without violating the system constraints. The cost of energy not supplied (CENS) associated with power service interruption and power shortage is also been considered in the objective function during placement of ESSs. Hence, the proposed optimal placement planning of ESSs is presented with an aim of minimizing the objective function includes cost of energy not supplied (CENS), investment cost and operational cost of ESSs, and power loss in distribution system. It is to be noted that the Particle swarm optimization (PSO) technique is adopted to minimize the objective function. The presented methodology is demonstrated by considering several case studies on 11 kV, 30 bus radial distribution system. Further, a rigorous sensitivity analysis is performed by limiting the number of applied ESSs and varying the maximum capacity of participating ESSs.

Review of fossil fuels and future energy technologies

The existence of sunlight, air, and different resources on Earth must be used wisely for human welfare while also safeguarding the environment and its living creatures. The use of the sunlight and air as a significant source of renewable energy (RE) is already an object of research and development in recent years. The high integration costs of various RE energy sources are a significant hurdle to their development. The RE contributes different energy domains: wind energy, solar energy, geothermal energy, hydro energy, ocean energy, bioenergy, hydrogen energy, and hybrid energy. Nowadays, artificial intelligence (AI) plays an inevitable role in RE, and it could assist in achieving the future goals of the RE. AI approaches in the research and development of the abovementioned RE sources will be comprehensively analyzed. This chapter analyzes and discusses challenges estimating the value creation of AI methods in RE.