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This paper focuses on the design and use of a control system for a renewable energy production plant based on hydrogen. The proposed control system aims at ensuring the stability and smooth functionality of the plant, which consists of a (i) photovoltaic system connected to an electrolyzer through a battery, (ii) a DC/DC step down transformer, and (iii) an electrolyzer heat exchange system. In this study, solar irradiance is the main system input, and hydrogen production the main output. Since the system utilizes solar energy as input, it depends on the random input of solar irradiance, ambient temperature, and wind flow. Furthermore, the electrolyzer's functionality is subject to several operational variables including cell voltage, current, temperature, and pressure. The electrolyzer heat exchange system operates at specified water temperatures and flow rates. The DC/DC output voltage, and therefore the voltage supplied to the electrolyzer, is regulated by changing its duty cycle. To regulate hydrogen production in the renewable energy production plant, an efficient control system is required. Accordingly, in this work, a control system is designed accounting for three different electrolyzer technologies, alkaline, PEM (proton exchange membrane), and E-TAC (electrochemical - thermally activated chemical water splitting). Subsequently, the effectiveness of the control system is analyzed using Matlab and Simulink models. The main results indicate that the battery is a crucial element in the whole system as it supplies the necessary energy to the electrolyzer. By regulating the appropriate components, the proposed control system proved capable of minimizing power fluctuations and increasing system efficiency up to 20% depending on ambient conditions. Additionally, the results indicate E-TAC and PEM efficiencies 13% and 7% higher than alkaline, respectively. [Display omitted] • Design of a control system for three different electrolyzer technologies. • Use of control systems for electrolyzer voltage and heat exchange. • Photovoltaic system connected to an electrolytic one through a battery. • Proposed control system increases system efficiency up to 20%. [ABSTRACT FROM AUTHOR]

In recent times, the escalating global demand for sustainable and renewable energy sources has catalyzed the exploration and development of innovative technologies, among which floating photovoltaic (FPV) systems emerge as a particularly promising solution. These systems exploit solar energy by deploying PV panels on water surfaces. These systems, offer several advantages, including their independence from land use constraints, enhanced energy efficiency due to the cooling effect of water, and the potential for synergy with various energy sources. Expanding on prior literature reviews, this paper provides a focused review of the latest developments in FPV systems, cutting-edge technologies, challenges faced the FPV in marine settings, extending to an economic analysis for comprehensive feasibility assessment, and market potential from diverse angles. The primary objective is to promote additional research and applications of FPV to guarantee the safety and stability of FPV systems under challenging marine environmental conditions, aiming to enhance overall efficiency, reliability, and the widespread adoption of FPV projects, while concurrently reducing investment costs. Highlighting its importance for energy-deficient African countries, the paper underscores the significance of integrating FPV systems into the continent's energy strategies for widespread adoption, to bolster energy security and environmental sustainability across the continent. [ABSTRACT FROM AUTHOR]

• Assessing solar power technical potential in China with high-resolution data. • Quantifying the gap between actual generation and technical potential at plant level. • Actual solar power generation is only 30% of the technical potential. • Technology, construction, and management factors cause the underperformance. Improving the power output of solar photovoltaic (PV) farms is critical to maximize the potential of PV power and reduce extensive land use in the context of large-scale deployment of renewable energy. In this paper we developed an integrated solar power potential assessment framework to quantify the gap between technical potential and actual generation of solar PV farms on national, provincial, and plant scales, and identify the key factors that cause the underperformance of PV farms. Specifically, to assess technical potential, hourly meteorological reanalysis data is adopted and the power generation-related parameters are calculated (i.e. optimal panel tilt, array spacing, packing factor etc.) with consideration of their spatial variability. For actual power generation, a detailed plant-level dataset is first established by this study which integrates technical, operational, and geospatial information from 145 solar farms across seven provinces in China. Our results show that the actual PV power generation per square meter is only 1/3 of the estimated technical potential. Technological factor is the primary factor, accounting for 48.43% of the underperformance, followed by engineering and management factors, accounting for 38.55% and 13.02%, respectively. The novelty of our study is revealing the underperformance level of solar farms in reality, identifying the causing factors, and highlighting the importance of integrating land-use efficiency indicators into solar power planning and development. [ABSTRACT FROM AUTHOR]

Constructing an accurate and reliable solar photovoltaic (PV) power forecasting system is crucial for smart grid management and dispatch. However, due to the intermittent, non-stationary and random nature of solar energy, current methods cannot effectively capture the dynamic change patterns of PV data, resulting in a forecasting accuracy that cannot satisfy the requirement for stable operation of smart grids. To address this issue, in this paper, a new solar PV power forecasting system is proposed based on a new adaptive mode decomposition method that combines machine learning models. First an adaptive mode decomposition method is proposed for adaptively eliminating high-frequency information of PV data, mitigating the impact of high noise on the forecasting performance. Then the powerful mapping ability of machine learning model is utilized to construct a solar PV power generation combination forecasting system. The system adopts a multi-objective optimization strategy to determine the optimal weights of the combination model, which reduces the volatility of the forecasting results and enhances the stability of the forecasting system. Experimental results demonstrate that the proposed system achieves the best overall performance with online manner on 10 state-of-the-art baselines. Furthermore, the evaluation analysis by Diebold–Mariano test, improvement ratio and sensitivity analysis further show that the stability and accuracy of the proposed system outperforms the comparative baselines. [ABSTRACT FROM AUTHOR]

• A multi-microgrid energy real-time optimal control scheduling strategy is proposed. • Energy storage devices can actively participate in optimal energy scheduling. • Improved resilience and flexibility of energy dispatch for multiple microgrid. • Significantly reduce the number of microgrid connections to the distribution grid. • Maximising the full uptake of renewable energy in multi-microgrid systems. With the increasing prominence of the energy crisis and global climate issues, it has become an important cornerstone of the energy revolution to improve the utilization rate of renewable energy and gradually reduce the use of fossil energy. Nonetheless, the erratic fluctuations and instability of renewable energy sources such as wind and solar energy have presented certain obstacles to the effective utilization of renewable energy. In order to maximize the utilization of renewable energy, enhance its utilization efficiency, and reduce the carbon emission of power supply, this paper first proposes a real-time collaborative optimal energy scheduling and dispatching control model for multi-microgrids. Subsequently, it proposes a real-time optimal control and dispatching strategy for multi-microgrid energy based on storage collaborative. This model considers the energy storage device as an energy management controller, enabling it to participate in the energy collaborative dispatch of multi-microgrid. This enables the energy storage device in the microgrid not only to actively participate in the optimal scheduling of energy, but also to make the energy in the storage device be reasonably distributed in the multi-microgrid system, to maximize the full absorption of renewable energy in the multi-microgrid, thereby reducing the dependence of the microgrid on the distribution network, and significantly improving the elasticity and reliability of the multi-microgrid system. Finally, the feasibility and effectiveness of the proposed optimal control scheduling strategy are verified by simulation. [ABSTRACT FROM AUTHOR]

India's power sector has undergone significant changes in recent years, driven by various policy initiatives aimed at promoting competition, improving efficiency, and increasing the share of renewable energy sources in the country's energy mix. This manuscript provides an overview of the current state of the Indian power sector and their recent developments. The manuscript discusses the structure of India's power sector, including the role of various players such as generation companies, transmission companies, and distribution companies. The manuscript then analyzes policy initiatives aimed at reforming the sector, these include the Electricity Act of 2003, which introduced competition in the generation and retail segments, the Ujwal DISCOM Assurance Yojana program, which aimed at improving the financial health of distribution companies, and, the Revamped Distribution Sector Scheme which has been approved by the Government of India to assist DISCOMs in improving their operational efficiencies and financial sustainability. The manuscript also discusses recent developments in the renewable energy sector in India, including the growth of solar and wind power, the implementation of renewable purchase obligations, and the introduction of competitive bidding for renewable energy projects. Finally, the manuscript examines the impact of recent developments on the performance of India's power sector and the power exchange. It finds that while significant progress has been made in promoting competition and increasing the share of renewable energy, challenges such as the high cost of electricity and the financial health of distribution companies persist. The paper concludes by discussing potential areas for further reform and improvement in the sector. • Overview of the current Indian electricity sector and recent developments. • Government initiatives to improve the Electricity Sector. • Discussion on the usage of renewable energy sources in India. [ABSTRACT FROM AUTHOR]

Solar thermal energy is one of the important sources of renewable energy. The solar thermal energy gives clean energy which can be utilized for industrial applications. Industrial heaters which require heat energy for many industrial uses can be attained using these solar thermal absorbers. The solar thermal absorber is designed using a layer design that consists of material compositions of Titanium (Ti) and Stannic selenide (SnSe 2) for ground and substrate sections respectively. A graphene layer which has the good properties to be used in solar absorbers is added between the Aluminum and SnSe 2 material. A thin graphene section is inserted above the SnSe 2 substrate and below the Ti resonator. To catch the good absorption in the current design, the best four wavelengths (micrometer) have been attached such as 0.22, 0.8, 2.46, and 2.85. This design's contribution can be studied in 4-atm regimes (from UV, V to NIR, and MIR). According to the wavelength and bandwidth ranges, the current absorption explores more than 97% (97.4%) in between 2.4 and 3 μm (600 nm) bandwidth and exceeds 95% (95.2%) from 0.2 to 1 μm (800 nm) respectively. To the overall range of design, it extracts 90.3% for the 2800 nm band between 0.2 and 3 wavelength regime. The flow of the presentation of the proposed paper is (i) Introduction (ii) Design and Parameters, and (iii) Results and Discussions. The explored absorber can be effective in water heating and swimming pool heating for homes. Moreover, it can also be applied in large industries as a solar thermal absorber for heating applications. [ABSTRACT FROM AUTHOR]

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow problem, called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution operator in a single algorithmic framework. Additionally, an adaptive method is proposed to update the number of solutions evolved by each DE operator based on both the diversity of the population and the quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%. • Development of an adaptive method (AM) for optimizing diversity and solution quality. • Innovative constraint handling approach, progressively adding constraints for improved performance. • Incorporation of intermittent renewable energy models for realistic problem solving. • Extensive validation on IEEE 30-bus and IEEE 118-bus networks, outperforming state-of-the-art algorithms in cost, loss, and environmental impact reduction. [ABSTRACT FROM AUTHOR]

Under the worldwide carbon neutralization targets, concentrating solar power (CSP) is arousing great attention. With the thermal energy storage (TES), CSP is friendly to the power system operation by supplying controllable renewable energy. The capacities of its solar field and TES are essential parameters for maximizing the profit of a CSP plant. This paper formulates an explicit expression of the CSP plant's profit instead of using a simulation-based method. Then, an unconstrained optimization model is proposed to calculate its optimal configuration directly. This model provides insights into the optimal configuration of CSP with different penetrations of wind power in the case study. The results show that to obtain a better profit for the CSP plant, large solar multiple (more than 3.0) and TES (more than 13 h) are preferred to collaborate with high penetration of wind and photovoltaic plants. The effectiveness of the proposed method is verified compared to the enumeration searching method. The economy and feasibility of installing an electric heater (EH) in CSP are also demonstrated. Generally, the optimal investment in EH is linearly correlated to the penetration of variable energy resources. [Display omitted] • A flexible operation model of CSP with EH is proposed. • An explicit model of CSP's profit based on the solar radiation curve and prices is constructed. • The configuration of the CSP plant is optimized through the first-order optimality conditions on the profit function. • The optimal configuration of CSP with high renewable energy is provided in the case study. [ABSTRACT FROM AUTHOR]