A Robust Scheduling Optimization Model for an Integrated Energy System with P2G Based on Improved CVaR

The uncertainty of wind power and photoelectric power output will cause fluctuations in system frequency and power quality. To ensure the stable operation of the power system, a comprehensive scheduling optimization model for the electricity-to-gas integrated energy system is proposed. Power-to-gas (P2G) technology enhances the flexibility of the integrated energy system and the power system in absorbing renewable energy. In this context, firstly, an electricity-to-gas optimization scheduling model is proposed, and the improved Conditional Value at Risk (CVaR) is proposed to deal with the uncertainty of wind power and photoelectric power output. Secondly, taking the integrated energy system with the P2G operating cost and the carbon emission cost as the objective function, an optimal scheduling model of the multi-energy system is solved by the A Mathematical Programming Language (AMPL) solver. Finally, the results of the example illustrate the optimal multi-energy system scheduling model and analyze the economic benefits of the P2G technology to improve the system to absorb wind power and photovoltaic power. The simulation calculation of the proposed model demonstrates the necessity of taking into account the operating cost of the electrical gas conversion in the integrated energy system, and the feasibility of considering the economic and wind power acceptance capabilities

Trend Analysis and Comprehensive Evaluation of Green Production Principal Component of Thermal Power Unit Based on ANP-MEEM Model

Low-emission environmental protection concept once it replaced the low-carbon energy transformation concept, to a certain extent, disrupted the core direction of energy transformation. This paper takes the green development of electric power as the research direction, the thermal power unit is the green source control point of electricity, and the green production of the thermal power unit is the research target; based on the actual research data and the actual data, the comprehensive evaluation of the green production of a thermal power generating unit in a city is carried out by means of ANP, matter-element extension model, and principal component analysis. This paper not only reflects the quantification of green benefits in each year, but also achieves the comparison of green achievements and the analysis of increasing losses in the data years. Furthermore, the indexes of annual increase and loss of the index system are analyzed and filtered. The indexes of strong contribution index and short board of barrel are found out, and the dimension reduction management of green production of thermal power unit is realized

Multi-Level Market Transaction Optimization Model for Electricity Sales Companies with Energy Storage Plant

Due to market price uncertainty and volatility, electricity sales companies today are facing greater risks in regard to the day-ahead market and the real-time market. Along with introducing the Time of Use (TOU) price for the customer as a type of balancing resource to avoid market risk, electricity sales companies should adopt the market risk-aversion method to reduce the high cost of ancillary services in the real-time market by using multi-level market transactions, as well as to provide a reference for the profits of power companies. In this paper, we establish a non-linear mathematical model based on stochastic programming by using conditional value-at-risk (CVaR) to measure transaction strategy risk. For the market price and consumer electricity load as the uncertain factors of multi-level market transactions of electricity sales companies, the optimal objective was to maximize the revenue of electricity sales companies and minimize the peak-valley differences in the system, which is solved by using mixed-integer linear programming (MILP). Finally, we provide an example to analyze the effect of the fluctuation degree of customer load and market price on the profit of electricity sales companies under different confidence coefficients

Armchair Janus WSSe Nanotube Designed with Selenium Vacancy as a Promising Photocatalyst for CO₂ Reduction

Photocatalytic conversion of carbon dioxide into chemical fuels offers a promising way to not only settle growing environmental problems but also provide a renewable energy source. In this study, through first-principles calculation, we found that the Se vacancy introduction can lead to the transition of physical-to-chemical CO2 adsorption on Janus WSSe nanotube. Se vacancies work at the adsorption site, which significantly improves the amount of transferred electrons at the interface, resulting in the enhanced electron orbital hybridization between adsorbents and substrates, and promising the high activity and selectivity for carbon dioxide reduction reaction (CO2RR). Under the condition of illumination, due to the adequate driving forces of photoexcited holes and electrons, oxygen generation reaction (OER) and CO2RR can occur spontaneously on the S and Se sides of the defective WSSe nanotube, respectively. The CO2 could be reduced into CH4, meanwhile, the O2 is produced by the water oxidation, which also provides the hydrogen and electron source for the CO2RR. Our finding reveals a candidate photocatalyst for obtaining efficient photocatalytic CO2 conversion

An Income Distributing Optimization Model for Cooperative Operation among Different Types of Power Sellers Considering Different Scenarios

To alleviate the shortcomings of large-scale grid connections for clean energy, which require stable thermoelectric units to provide backup services, a stable cooperative alliance among different energy types of power sellers must be established. Consequently, a reasonable method to distribute income is required, due to different contributions of each entity in the alliance. Therefore, this paper constructs a comprehensive correction algorithm for income distribution using an improved Shapely value method. We analyze the operating mode of the power seller, and establish the net income calculation model under both independent and alliance operations. We then establish an alliance operation optimization model that considers the constraints of unit output, as well as the balance between supply and demand, with the goal of maximizing income. Finally, an industrial park in a province of northern China is taken as an example to verify the model’s practicability and effectiveness. The results show that the power sales alliance can effectively promote clean energy consumption. The maximum reduction in thermal power generation and CO2 is 8510 MW and 684.515 tons, respectively. We apply the algorithm to income distribution and find that the thermal power seller’s income increased by ¥1,463,870, which enhances the stability of the alliance. Therefore, our income distributing optimization model guarantees the interests of each participant to the greatest extent, and serves as an important reference for income distribution