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As the integration of distributed energy into the power grid continues to rise, the significance of electricity transactions in promoting renewable energy consumption grows substantially. This necessitates the establishment of a robust electricity trading framework to facilitate reliable and trustworthy transactions for prosumers. This paper introduces an innovative blockchain-based electricity trading framework. Within this framework, we present a decentralized collaborative model training approach aimed at predicting the power generation of distributed photovoltaic power stations. Simultaneously, we propose a graph-based algorithm for efficiently matching producers and consumers. Our experiments, conducted on the Hyperledger Fabric blockchain platform using real-world datasets, demonstrate enhanced prediction accuracy compared to existing models. The framework effectively handles transactions within one second, sustaining a sending rate of up to 200 transactions per second. The outcomes of this study not only surpass the performance of existing prediction models but also provide valuable insights for the development of trading frameworks in actual production environments. The proposed framework stands as a reference point for constructing reliable trading infrastructures, thereby contributing to the acceleration of green electricity trading. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RESs) such as solar photovoltaic (PV) systems are increasingly used as distributed generation for replacing the conventional energy. At the same time, energy storage systems like battery (BAT) must be applied for maintaining the balance between fluctuating energy production and load consumption. BAT's state of charge (SOC) should be maintained within their design limits unaffected by RES intermittency and/or load power variations. This necessitates advanced power control and management methodologies for overcoming challenging conditions. This paper discusses and evaluates an optimal DC bus voltage regulation approach: an intelligent controller using an adaptive fuzzy logic controller (FLC) and a novel supervisory power management strategy for PV systems with BAT. The objectives are to keep a stable power flow in the system and guarantee the continuity of service by ensuring that the system components do not exceed their limits. In this manner, the DC bus voltage regulation of the PV/BAT system can be improved in comparison with conventional regulation. Therefore, the most important contributions of this work are as follows. (1) Development of comprehensive and modular novel energy management system (EMS): its originality is related to the inclusion of the control system limits with faster SOC balancing and smaller DC bus voltage fluctuation. (2) Providing a simple power flow management implementation that considers the optimal energy flow between PV system, BAT system, and load: a balance between minimal energy flow in the connecting line and the least requirements of BAT capacity is kept, reducing component constraints with a very straightforward structure. (3) Furthermore, FLC offers high robustness and smooth performances. FLC is added to the control strategy design requirements to reduce DC bus voltage deviation. (4) Real-time simulation/experimentation-based complete cases utilizing Matlab/Simulink and DSpace are illustrated to testify the effectiveness of the proposed FLC and EMS. [ABSTRACT FROM AUTHOR]

This paper presents a flexible-reliable operation strategy for clean microgrids (MGs) consisting of power sources, energy storage systems (ESSs), and responsive loads. The proposed strategy attempts to provide the minimum expected operating cost for the MG, power sources, predicted pollutant emission, and expected energy not-supplied (EENS) because of an N − 1 event considering different applications. The objective function of the problem is subject to several constraints including AC optimal power flow equations, flexibility and reliability boundaries, and model of power sources and active loads. The Pareto optimization based on the weighted sum method is then incorporated to obtain a single-objective model. Probabilistic programming is also used to model the uncertainties of load, renewable energy, electrical energy price, and MG equipment accessibility. The ant-lion and crow search algorithms are merged to solve the problem and find a reliable optimal solution. A standard MG is employed to test the proposed strategy and indicate its capability in enhancing technical and economic indicators of the MG while ensuring that the MG is clean. [ABSTRACT FROM AUTHOR]

This paper proposes the planning of hybrid micro-hydro and solar photovoltaic system for rural areas of Central Java, Indonesia. The Indonesian government has paid great attention to the development of renewable energy sources, especially solar and hydropower. One area that has a high potential for both types of energy is the province of Central Java, located on the island of Java, Indonesia. In this research, we conduct field research to determine the ideal capacity of solar and micro-hydro hybrid power plants, electricity load analysis, and optimal design of hybrid power plants. Data on the potential of micro-hydro plants are obtained by direct measurement on the Ancol Bligo irrigation channel located in Bligo village, Ngluwar district, Magelang regency, Central Java province, Indonesia. Data on solar power potential were obtained from NASA's database for solar radiation in the Central Java region. Hydropower potential data include channel length, debit, heads, and power potential in irrigation channels originating from rivers. These data are used to design an optimal hybrid power plant. The method used to obtain the optimal design of a hybrid power plant system is based on the analysis of capital costs, grid sales, cost of energy, and net present cost. Based on the parameters of the analysis, the composition of the optimal generator for the on-grid scheme to the distribution network can be determined. The results showed that hybrid power plants were able to meet the needs of electrical energy in the villages around the power plant and that the excess energy could be sold to national electricity providers. [ABSTRACT FROM AUTHOR]

In order to mitigate the negative influence of geographical dispersity of modern power system and the penetration of renewable energy, a system compensation based model predictive AGC method is proposed in this paper. A compensation unit is introduced in AGC system to reduce the influence of PV power output fluctuation. Furthermore, because the distributed power system is geographically dispersed, which leads to some defects such as time delay and packet dropouts, a selection and optimization algorithm is presented to obtain the appropriate variable when delays exist. Finally, a two-area interconnected power grid with PV systems is shown as an example to testify the feasibility and effectiveness of the proposed method. The simulation results indicate that the system controlled by the proposed method has the expected dynamic performance. [ABSTRACT FROM AUTHOR]

During the last fewyears generation from renewable energy sources (RESs) has grown considerably in European electrical networks. Transmission system operators are greatly concerned about the impact of RESs on the operational security and efficiency of their networks and more in general of the ENTSO-E interconnected system. Grid codes are to be revised in order to harmonise the rules regarding the connection of RES power plants. A main issue concerns frequency control: frequency is greatly affected by RESs intermittency and its deviationsmust be limited asmuch as possible in order to guarantee a suitable level of power quality. To improve frequency stability, in the future, Grid codes could extend frequency control requirements also to RES units, whereas today they are applied only to conventional power plants. Energy storage systems can be a possible solution to increase the flexibility and performance of RES power plants: they allow generators to modulate their power injections without wasting renewable energy. In this paper, the authors studied the suitability of extending frequency control to RES units integrating them with energy storage systems. In particular, the paper focuses on the impact of frequency control on the storage lifetime by analysing the power charge/discharge in response to real frequency oscillations. [ABSTRACT FROM AUTHOR]

The smart grid and distributed generation based on renewable energy applications often involve the use of information and communication technology (ICT) coupled with advanced control and monitoring algorithms to improve the efficiency and reliability of the electrical grid and renewable generation systems. Photovoltaic (PV) systems have been recently applied with success in the fields of distributed generation due to their lower environmental impact where the electrical energy generation is related to the amount of solar irradiation and thus the angle of incident ray of the sun on the surface of the modules. This paper introduces an integration of ICTs in order to achieve the maximum power point tracking (MPPT) using a biaxial solar tracking system for PV power applications. To generate the references for the digital control of azimuth and elevation angles a Global Positioning System (GPS) by satellites is used which enables acquiring the geographic coordinates of the sun in real-time. As a total integration of the system a communication platform based on the 802.15.4 protocol for the wireless sensor networks (WSNs) is adopted for supervising and monitoring the PV plant. A 2.4 kW prototype system is implemented to validate the proposed control scheme performance. [ABSTRACT FROM AUTHOR]

Large amount of such renewable energy generations as wind/photovoltaic generations directly connected to grid acting as distributed generations will cause control, protection, security, and safety problems. Microgrid, which has advantages in usage and control of distributed generations, is a promising approach to coordinate the conflict between distributed generations and the grid. Regarded as mobile power storages, batteries of electric vehicles can depress the fluctuation of power through the point of common coupling of microgrid. This paper presents a control strategy for microgrid containing renewable energy generations and electric vehicles. The control strategy uses current control for renewable energy generations under parallel-to-grid mode, and uses master-slave control under islanding mode. Simulations and laboratory experiments prove that the control strategy works well for microgrid containing renewable energy generations and electric vehicles and providesmaximum power output of renewable energy and a stable and sustainable running under islanding mode. [ABSTRACT FROM AUTHOR]