In order to further alleviate the problems of large assessment deviations, low efficiency of trading organisation and difficulties in system optimisation in medium- and long-term market trading, the article proposes an optimisation model for continuous intra-month bidding trading in the electricity market that takes into account risk hedging. Firstly, the current situation of market players’ participation in medium and long-term trading is analysed; secondly, the impact of contract trading on reducing operational risks is analysed based on the application of hedging theory in the primary and secondary markets; finally, the continuous bidding trading mechanism is designed and its optimisation effect is verified. The proposed model helps to improve the efficiency of contract trading in the secondary market, maintain the stability of market players’ returns and accelerate the formation of a unified, open, competitive and well-governed electricity market system.
Nowadays, our life needs more and more electricity, and our lives cannot be without electricity, which requires our power to develop more quickly. Power plants are undoubtedly the place where electricity is produced. And now most of the power plant or chemical energy can be converted into heat, and then through the heat to do power production. The boiler is the main part of the power plant. Boiler unit consists of boiler body equipment and auxiliary equipment. The main body of the boiler consists of 'pot' (soft drinks system) and 'furnace' (combustion system). Baotou thermal power plant is mainly burning gas. The gas and air are at a certain rate into the furnace burning. This can greatly reduce the pollution of the environment, but also the full use of fuel. The soda system is mainly carried out in the drum. The heat generated by the combustion system heats the water in the drum, producing steam and then pushing the steam turbine into mechanical energy and finally into electrical energy. This has a high demand for water level, water composition, and the temperature of the steam produced in the drum. The water level should have upper and lower bounds, keeping it within a certain range. Water level is too high, will affect the steam drum soda separation effect, so that the steam drum exports of saturated steam with water increased, causing damage to the turbine, will cause serious explosion. And the water level is too low, it will affect the natural circulation of the normal, serious will make the individual water pipe to form a free water, resulting in flow stagnation, resulting in local metal wall overheating and burst pipe. Water in the heating at the same time will form a lot of scale, if not the chemical treatment of water will be in the formation of scale in the drum, cleaning more difficult, so the damage to the drum. The pressure of the drum is also an important control variable, and pressure control is highly correlated with liquid level control. It is necessary to ensure the integrity of the equipment, but also to ensure safety, followed by ensuring that the process of normal operation of the drum water. This time, the design is mainly for the unit steam temperature control system design. Steam temperature is one of the important indicators of boiler operation quality. It is too high and too low will significantly affect the power plant safety and economy. If the temperature of the steam is low, it will cause the power plant to increase the heat consumption and increase the axial thrust of the turbine to cause the thrust bearing to overload, but also cause the steam turbine to increase the final steam humidity, thus reducing the efficiency of the turbine, aggravating the erosion of the blade. On the contrary, the steam temperature is too high will make the super-heater wall metal strength decreased, and even burn the high temperature of the super-heater, the steam pipe and steam turbine high-pressure part will be damaged, seriously affecting safety. The boiler temperature control system mainly includes the adjustment of the superheated steam and the reheat steam temperature. The superheated steam temperature is the highest temperature in the boiler soda system. The stability of the steam temperature is very important for the safe and economical operation of the unit. Therefore, in the boiler operation, must ensure that the steam temperature in the vicinity of the specified value, and the temperature of the super-heater tube wall does not exceed the allowable working temperature.
The Ecuadorian electricity sector encompasses generation, transmission, distribution and sales. Since the change of the Constitution in Ecuador in 2008, the sector has opted to employ a centralized model. The present research aims to measure the efficiency level of the Ecuadorian electricity sector during the period 2012–2021, using a DEA-NETWORK methodology, which allows examining and integrating each of the phases defined above through intermediate inputs, which are inputs in subsequent phases and outputs of some other phases. These intermediate inputs are essential for analyzing efficiency from a global view of the system. For research purposes, the Ecuadorian electricity sector was divided into 9 planning zones. The results revealed that the efficiency of zones 6 and 8 had the greatest impact on the overall efficiency of the Ecuadorian electricity sector during the period 2012–2015. On the other hand, the distribution phase is the most efficient with an index of 0.9605, followed by sales with an index of 0.6251. It is also concluded that the most inefficient phases are generation and transmission, thus verifying the problems caused by the use of a centralized model.
Background: Bitcoin mining, an energy-intensive process, requires significant amounts of electricity, which results in a particularly high carbon footprint from mining operations. In the Republic of Kazakhstan, where a substantial portion of electricity is generated from coal-fired power plants, the carbon footprint of mining operations is particularly high. This article examines the scale of energy consumption by mining farms, assesses their share in the country’s total electricity consumption, and analyzes the carbon footprint associated with bitcoin mining. A comparative analysis with other sectors of the economy, including transportation and industry is provided, along with possible measures to reduce the environmental impact of mining operations. Materials and methods: To assess the impact of bitcoin mining on the carbon footprint in Kazakhstan, electricity consumption from 2016 to 2023, provided by the Bureau of National Statistics of the Republic of Kazakhstan, was used. Data on electricity production from various types of power plants was also analyzed. The Life Cycle Assessment (LCA) methodology was used to analyze the environmental performance of energy systems. CO2 emissions were estimated based on emission factors for various energy sources. Results: The total electricity consumption in Kazakhstan increased from 74,502 GWh in 2016 to 115,067.6 GWh in 2023. The industrial sector’s electricity consumption remained relatively stable over this period. The consumption by mining farms amounted to 10,346 GWh in 2021. A comparative analysis of CO2 emissions showed that bitcoin mining has a higher carbon footprint compared to electricity generation from renewable sources, as well as oil refining and car manufacturing. Conclusions: Bitcoin mining has a significant negative impact on the environment of the Republic of Kazakhstan due to high electricity consumption and resulting carbon dioxide emissions. Measures are needed to transition to sustainable energy sources and improve energy efficiency to reduce the environmental footprint of cryptocurrency mining activities.
This study aims to explore the asymmetric impact of renewable energy on the sectoral output of the Indian economy by analyzing the time series data from 1971 to 2019. The nonlinear autoregressive distributed lag approach (NARDL) is employed to examine the short- and long-run relationships between the variables. Most studies focus on economic growth, ignoring sectoral dynamics. The result shows that the sectoral output shows a differential dynamism with respect to the type of energy source. For instance, agricultural output responds positively to the positive shock in renewable energy, whereas industry and service output behave otherwise. Since the latter sectors depend heavily on non-renewable energy sources, they behave positively towards them. Especially, electricity produced from non-renewable energy sources significantly influences service sector output. However, growing evidence across the world is portraying the strong relationship between the growth of renewable energy sources and economic growth. However sectoral dynamism is crucial to frame specific policies. In this regard, the present paper’s result indicates that policies related to promoting renewable energy sources will significantly influence sectoral output in the long run in India.
We analyze Thailand’s projected 2023–2030 energy needs for power generation using a constructed linear programming model and scenario analysis in an attempt to find a formulation for sustainable electricity management. The objective function is modeled to minimize management costs; model constraints include the electricity production capacity of each energy source, imports of electricity and energy sources, storage choices, and customer demand. Future electricity demands are projected based on the trend most closely related to historical data. CO2 emissions from electricity generation are also investigated. Results show that to keep up with future electricity demands and ensure the country’s energy security, energy from all sources, excluding the use of storage systems, will be necessary under all scenario constraints.
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