The emerging blockchain technology has injected new vitality into the energy market, especially the peer-to-peer power trading of microgrid systems. However, with the increase of energy blockchain projects, the difficulty of data communication and value islands between blockchain networks have become open issues. Thus, in this paper, we propose a dynamic adaptive cross-chain trading mode for multi-microgrid joint operation. The novelty is to design a proof of credit threshold consensus mechanism to achieve effective information verification. This consensus mechanism can ensure the adaptive consistency of cross-chain information without changing the existing blockchain architecture of each system. At the same time, we design a corresponding key management interoperability protocol based on RSA algorithm and Chinese remainder theorem, which can realize data transfer and information consensus for cross-chain transactions. The theoretical analysis verifies that the cross-chain communication information is effective and the system is able to protect against the attack of malicious nodes. Finally, a cross-chain simulation experiment is established to analyze the operation efficiency. The result shows that this cross-chain trading takes place within seconds, which basically meets the response requirements for multi-microgrid joint operation.
Solar energy has attracted the attention of researchers around the world due to its advantages. However, photovoltaic (PV) panels still have not attained the desired efficiency and economic mature. PV tracking techniques can play a vital role in improving the performance of the PV system. The aim of this paper is to evaluate and compare the technical and economic performance of grid-connected hybrid energy systems including PV and fuel cells (FC) by applying major types of PV tracking technique. The topology and design principles and technical description of hybrid system components are proposed in this paper. Moreover, this paper also introduces economic criteria, which are used to evaluate the economy of different PV tracking techniques and seek the optimal configuration of system components. In the case study, the results show that the vertical single axis tracker was ranked 1st in terms of highest PV generation, penetration of renewable energy to the grid, lowest CO2 emission, highest energy sold to the grid and lowest purchased, and lowest net present cost (NPC) and levelized cost of energy (LCOE). The study found that the optimal design of a grid-connected hybrid energy system (PV-FC) was by using a vertical single axis tracker which has the lowest NPC, LCOE.
Global warming and climate change are becoming a global concern. In this regard, international agreements and initiatives have been launched to accelerate the use of renewable energy and to mitigate greenhouse gas (GHG) emissions. Yemen is one of the countries signed on these agreements. However, Yemen is facing the problem that the structure of the power grid is fragile and the power shortage is serious. Accordingly, this paper aims to study the potential for renewable energy in Yemen and assess the technical and economic feasibility of hybrid energy systems. Firstly, this paper introduces the status and challenges of Yemen’s electricity sector, the status of renewable energy, and the status of GHG emission. Secondly, this study proposes the method of optimizing different configurations of off-grid hybrid (solar/wind/diesel engine) energy systems for electrifying various consumers in Taiz province, Yemen under three scenarios of energy strategies. The objective function is to seek the most optimal hybrid energy system that achieves the least cost and most advantageous technical performance, while instigating the best economic scenario of energy strategies. Finally, Homer pro software is used for simulation, optimization, and sensitivity analysis of the designed energy systems. The results found the best economically feasible scenario, the hybrid PV/wind/diesel energy system, among the other scenarios. A photovoltaic (PV)/wind energy system achieved the best technical performances of 100% CO2 reduction, with a 54.82% reduction in the net present cost (NPC) and cost of energy (COE); while the hybrid energy system (PV/wind/diesel engine) achieved the best economic cost of 61.95% reduction in NPC and COE, with a 97.44% reduction of CO2 emission.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.