Distributed energy systems (DESs) exhibit potential to promote the energy market reform worldwide. In this study, a bi-level optimization model is proposed to analyze the operation of a DES that purchases high-voltage electricity and natural gas from utility companies, and supplies low-voltage electricity and heat to multiple users. To simplify the resolution process, the bi-level optimization is transformed into a single-level mixed integer linear programming model using the Karush-Kuhn-Tucker approach and Big M method. The results indicate that (i) the time-sensitive energy prices offered by the DES could smoothen the load profiles of users; and (ii) the tiered pricing scheme set up by the utility companies could maximize the utility of the ESS integrated into the DES, but the capacity of the ESS should be accurately designed to fit the corresponding pricing scheme.
Cross Laminated Timber (CLT) is attracting worldwide attention, due to its durability, usability, and many other advantages. However, since CLT is made of wood, analysis of the hygrothermal performance is essential. In this study, the various conditions that affect the thermal moisture behavior were applied to the simulation for getting stable hygrothermal results. As a result, the standard of Passive house and Domestic wooden house, the climate condition, the presence of breathable water proofing paper, and the insulation alternatives of Expended Polystyrene (EPS) and Extruded Polystyrene (XPS) were applied. It was concluded that breathable waterproofing paper should be installed inside, and the applications of both XPS and EPS made no difference to moisture but the application of Mineral Wool was adversely affect to hygrothermal performance of the CLT wall system. The thickness of insulation should be designed according to the Passive house standard (0.15 W/m 2 K) rather than the Domestic (Korea) Wooden house standard (0.21 W/m 2 K).
In this study, we aim to find an optimally sized battery that can be installed to an existing grid-tied solar home system without a prior energy storage system, in order to maximize the user’s financial benefits while maintaining reliable power supply to the home. To solve this optimization problem, we formulate the objective function as the net present value of the investment on the battery. Solution to the optimization problem returns the optimal battery size, power flows and battery age status during a 10-year evaluation period. In order to identify the most favorable solution to the user, we apply the proposed optimization algorithm to five typical photovoltaic (PV) generation and home load levels, and find that the optimal battery size is very sensitive to the level of PV power generation and the home load. In addition, it is more financially viable to have the battery when the daily PV power generation is less than the home load.
This study aims at exploring the relationship between renewable energy consumption and carbon dioxide emissions in China, and through the significance of renewable energy consumption, the hypothesis of environmental Kuznets curve at individual country level is tested as well as. Autoregressive distributes lag bounds testing approach is employed for empirical analysis. The results show that a quadratic relationship between renewable energy and CO2 emission has been found for the period support EKC relationship, and there exists a negative causality from renewable energy consumption to CO2 emissions.
In order to better understand the real-life thermal performance of Solar domestic hot water (SDHW) systems, SDHW systems installed in dormitories in a university were selected for on-line monitoring. There are 50 dormitory buildings in this university, and each building contains around 430 students. A SDHW system is installed in each building, using the glass evacuated solar tube collector, with an average collector area of 260 m2 . Air source heat pumps are used as auxiliary heat sources in the collector side. All SDHW systems were equipped with data logging system and remotely monitored with online data. Thermal performance analysis and economic analysis of SDHW systems were presented in this paper. The results show that the thermal performance and economy of SDHW systems for dormitory buildings are very good because the domestic hot water demand of student dormitories is relatively concentrated in time and space. Therefore, SDHW systems has a good application prospect in dormitory buildings.
The development of renewable energy is a huge opportunity and challenge in the energy field. As the ultimate energy source, solar energy is one of the most reliable energy sources among the renewable energies. Solar water splitting for hydrogen production is one of the most promising technologies of solar energy utilization, in recent decades. As an ideal clean energy source, hydrogen has made a significant breakthrough in transportation and storage technologies and hydrogen is also of great significance for applications such as chemical synthesis and energy storage. This paper reviews the basic methods and development of hydrogen production from solar water splitting, including photovoltaic, photoelectrochemical, and photothermal methods. In view of the photothermal method-solar thermochemical hydrogen production technology, this paper analyzes the thermodynamics, summarizes its future development perspectives. Furthermore, this paper also points out some new ideas for the realization of solar-thermal water splitting for hydrogen production.
Carbon trading markets play an important role in emissions mitigation through financial tools. China has established seven carbon trading pilots in its major cities and provinces. This paper explores the evolution laws of the co-movement of daily prices between carbon markets using complex network theory. First, we combine the co-movement of prices in five continuous days to co-movement modes. Then, we construct a directed weighted complex network. The nodes are the co-movement modes. Edges are defined as the time adjacent relations of two nodes. The frequency of an edge is taken as its weight. Transaction prices for the pilots in Hubei and Shanghai are selected as the samples. Results show an appearance of 231 modes from the 243 possible patterns, indicating a scattering of co-movement modes. Among all modes, the most frequent one is the fully stable one, showing that the markets are inactive in most time. Compared to the full sample and other periods, the complex networks in the first sample period stands out due to its large nodes and the existence of rings. This finding indicates the exact mirroring of some successive co-movement modes. The method proposed in this paper helps in understanding the evolution of Intermarket co-movement.
The energy consumption and CO2 emission of China’s passenger transport have been increasing in recent years. With China’s population, economic development level, passenger volume, public transportation share, private car stock, and new energy vehicle (NEV) policies developing year by year, we need a medium – and longterm model to predict the future energy demand and greenhouse gas emissions of China’s passenger transport. In this paper, we divide the passenger transport sector into inter-city and inner-city, then establish a bottom-up model using the LEAP (long-term energy planning system) platform to estimate China’s provincial passenger transport emissions up to 2050. Four scenarios, namely reference (REF), business as usual (BAU), electric vehicles promoting(EVP) are set to evaluate possible policy alternatives. The results show that the BAU scenario and EVP scenario are efficiently reduce the energy consumption and CO2 emissions. Under the BAU scenario and the EVP scenario will reduce 45% and 53% energy consumption respectively. Under the BAU scenario and the EVP scenario will reduce 78% and 91% CO2 emissions respectively. The results show that promoting the development of electric vehicles will help China to achieve the goal of low-carbon transportation.
Heat pumps will be a major player in the future energy system for their ability to efficiently extract heat from a source at lower temperature and provide it at higher temperature using electrical work. If coupled with a heat storage tank, the system can store heat and provide it at the point in time when the electricity price is more favorable.
In this study, we present a model of the heat pump energy performance using the coefficient of performance (COP) and the Lorentz efficiency. The latter gives an indication of the offset of the actual COP from the theoretical COP. We then compare different refrigerants performance to find out which one provide the best performance for district heating application. Finally, we study the cost-optimal operation of a heat pump with and without a thermal storage tank.
Results show that ammonia is a better candidate in terms of performance compared to other selected refrigerants. The performance analysis shows that the heat pump has a better Lorentz efficiency for lower COPs. Finally, we show that coupling the heat pump to a thermal storage tank can reduce the electricity cost of operation.
A new online fault diagnostic method for photo voltaic array is proposed in this paper, which is based on the Extreme Gradient Boosting (XGBoost)classifier. Firstly, the string current, array voltage, temperature and irradiance are measured by a monitoring system, from which a seven-dimensional fault feature vector is extracted as the input of the fault diagnosis model. Secondly, based on the XGBoost classifier, a new fault diagnosis model is established. Lastly, the feasibility and superiority of the proposed XGBoost based fault diagnosis model are tested by both Simulink based simulation and real fault experiments on a laboratory PV system. The correct rate of fault diagnosis in Simulink simulation is 99.99%, while the correct rate of fault diagnosis in laboratory PV power plant simulation is over 99.90%. Extreme learning machines (ELM) and Random Forests (RF) are tested for comparison. Experimental results demonstrate the superiority of the proposed XGBoost based model.