scholarly journals A Gini Coefficient-Based Impartial and Open Dispatching Model

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3146
Author(s):  
Liang Sun ◽  
Na Zhang ◽  
Ning Li ◽  
Zhuo-ran Song ◽  
Wei-dong Li
Keyword(s):  
Power Generation ◽  
Gini Coefficient ◽  
Optimal Allocation ◽  
Electric Energy ◽  
Threshold Value ◽  
Economic Benefits ◽  
Electricity Production ◽  
System Operation ◽  
The Gini Coefficient ◽  
Proposed Model

According to the existing widely applied impartial and open dispatching models, operation fairness was mainly emphasized, which severely restricted the optimization space of the economy of the overall system operation and affected the economic benefits. To solve the above problems, a scheduling model based on Gini coefficient under impartial and open dispatching principle is proposed in this paper, which can consider the balance between the fairness and economy of system operation. In the proposed model, the Gini coefficient is introduced to describe the fairness of electric energy completion rate among different generation units in the form of constraint conditions. Because the electricity production schedule can reflect the economic income of the electric power enterprise, and the Gini coefficient is used as an economic statistical indicator to evaluate the fairness in the overall distribution of income in social statistics, it is more appropriate to be used to measure the fairness of the power generation dispatching. The objective of the proposed model is to minimize the total operation costs. In the model, the balance between the system operation economy and fairness can be realized by adjusting the Gini coefficient value. The simulation results show that the proposed model is an extension of the traditional model. Compared with the traditional economic dispatching model and normal “impartial and open dispatching” model, the proposed model can better coordinate the relationship between fairness and economy. It could provide more choices for power generation dispatchers. It could also provide a reference for regulatory departments to formulate relevant policies by adjusting the threshold value of the Gini coefficient. Case studies show that the power dispatching decisions according to the proposed model can provide a scientific and fair reference basis for dispatching schemes, and could reduce the generation costs and also achieve optimal allocation of resources on the basis of ensuring fair dispatching.

scholarly journals An Optimization Model Based on Electric Power Generation in Steel Industry

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jing-yu Liu ◽  
Jiu-ju Cai
Keyword(s):  
Power Generation ◽  
Electric Power ◽  
Optimization Model ◽  
Steel Industry ◽  
Optimal Allocation ◽  
Mathematical Optimization ◽  
Production Equipment ◽  
Electricity Production ◽  
Cost Of Energy ◽  
Save Energy

Electric power is an important energy in steel industry. Electricity accounts for roughly 20% to 30% of the gross energy consumption and costs about 10% of the gross cost of energy. In this paper, under the premise of ensuring the stability of energy supply and the normal production safety, the mathematical programming method and the dynamic mathematical optimization model were used to set up the surplus gas in the optimal allocation among the buffer users and steam production dispatching for the production equipment. The application of this optimization model can effectively improve the energy efficiency and the accuracy of power generation, making full use of secondary energy and residual heat. It also can realize the rationalization of the electricity production structure optimization which can effectively reduce the flare of the gas and steam on one hand, and save energy and decrease production cost on the other.

The Optimal Operation of Super High Head Hydropower Station with Multiple Water Supply Modes

2014 ◽  
Vol 492 ◽  
pp. 536-543
Author(s):  
Rong Yong Ma ◽  
Jia Li Lin ◽  
Li Song ◽  
Xiao Chen Xie
Keyword(s):  
Power Generation ◽  
Water Supply ◽  
Electric Energy ◽  
High Water ◽  
Economic Benefits ◽  
Optimal Operation ◽  
Hydropower Station ◽  
Operation Model ◽  
Power Station ◽  
Small Change

In order to improve the power generation benefit of the Tianhu Hydropower Station, a optimal operation model of the water supply system of the power station is built to maximize the gross electric energy generated. The model takes into consideration that Tianhu Hydropower Station has multiple water supply modes and is characterized by its super-high water head, and that any small change on flow control may bring great impact on the output of the power station. Based on existing hydrological data and the optimal scheduling model, the optimized results are calculated and made to optimization curves. These optimization curves are used to guide the operation of the hydropower station. Years of actual practices demonstrated that operating Tianhu Hydropower Station under the guidance of the optimal reservoir group operation model presented in this paper has brought in significant economic benefits, with an annual increase in power generation income of more than eight million yuan.

scholarly journals Life Cycle Cost of Electricity Production: A Comparative Study of Coal-Fired, Biomass, and Wind Power in China

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3463
Author(s):  
Xueliang Yuan ◽  
Leping Chen ◽  
Xuerou Sheng ◽  
Mengyue Liu ◽  
Yue Xu ◽  
...  
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Wind Power ◽  
Life Cycle Cost ◽  
Raw Material ◽  
Electricity Production ◽  
Maintenance Cost ◽  
External Cost ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity

Economic cost is decisive for the development of different power generation. Life cycle cost (LCC) is a useful tool in calculating the cost at all life stages of electricity generation. This study improves the levelized cost of electricity (LCOE) model as the LCC calculation methods from three aspects, including considering the quantification of external cost, expanding the compositions of internal cost, and discounting power generation. The improved LCOE model is applied to three representative kinds of power generation, namely, coal-fired, biomass, and wind power in China, in the base year 2015. The external cost is quantified based on the ReCiPe model and an economic value conversion factor system. Results show that the internal cost of coal-fired, biomass, and wind power are 0.049, 0.098, and 0.081 USD/kWh, separately. With the quantification of external cost, the LCCs of the three are 0.275, 0.249, and 0.081 USD/kWh, respectively. Sensitivity analysis is conducted on the discount rate and five cost factors, namely, the capital cost, raw material cost, operational and maintenance cost (O&M cost), other annual costs, and external costs. The results provide a quantitative reference for decision makings of electricity production and consumption.

scholarly journals Usage of the Pareto Fronts as a Tool to Select Data in the Forecasting Process—A Short-Term Electric Energy Demand Forecasting Case

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3204
Author(s):  
Michał Sabat ◽  
Dariusz Baczyński
Keyword(s):  
Energy Demand ◽  
Demand Forecasting ◽  
Electric Energy ◽  
Forecasting Model ◽  
Short Term ◽  
Complex Evaluation ◽  
Proposed Model ◽  
Energy Demand Forecasting ◽  
Pareto Fronts ◽  
Naive Approach

Transmission, distribution, and micro-grid system operators are struggling with the increasing number of renewables and the changing nature of energy demand. This necessitates the use of prognostic methods based on ever shorter time series. This study depicted an attempt to develop an appropriate method by introducing a novel forecasting model based on the idea to use the Pareto fronts as a tool to select data in the forecasting process. The proposed model was implemented to forecast short-term electric energy demand in Poland using historical hourly demand values from Polish TSO. The study rather intended on implementing the range of different approaches—scenarios of Pareto fronts usage than on a complex evaluation of the obtained results. However, performance of proposed models was compared with a few benchmark forecasting models, including naïve approach, SARIMAX, kNN, and regression. For two scenarios, it has outperformed all other models by minimum 7.7%.

scholarly journals Optimal Allocation of Surface Water Resources at the Provincial Level in the Uzbekistan Region of the Amudarya River Basin

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1446
Author(s):  
Min Wang ◽  
Xi Chen ◽  
Ayetiguli Sidike ◽  
Liangzhong Cao ◽  
Philippe DeMaeyer ◽  
...  
Keyword(s):  
River Basin ◽  
Water Allocation ◽  
Water Distribution ◽  
Optimal Allocation ◽  
Probability Distributions ◽  
Economic Benefits ◽  
Aral Sea ◽  
Incoming Flow ◽  
Provincial Level ◽  
Water Users

Water users in the Amudarya River Basin in Uzbekistan are suffering severe water use competition and uneven water allocation, which seriously threatens ecosystems, as shown, for example, in the well-known Aral Sea catastrophe. This study explores the optimized water allocation schemes in the study area at the provincial level under different incoming flow levels, based on the current water distribution quotas among riparian nations, which are usually ignored in related research. The optimization model of the inexact two-stage stochastic programming method is used, which is characterized by probability distributions and interval values. Results show that (1) water allocation is redistributed among five different sectors. Livestock, industrial, and municipality have the highest water allocation priority, and water competition mainly exists in the other two sectors of irrigation and ecology; (2) water allocation is redistributed among six different provinces, and allocated water only in Bukhara and Khorezm can satisfy the upper bound of water demand; (3) the ecological sector can receive a guaranteed water allocation of 8.237–12.354 km3; (4) under high incoming flow level, compared with the actual water distribution, the total allocated water of four sectors (except for ecology) is reduced by 3.706 km3 and total economic benefits are increased by USD 3.885B.

scholarly journals Why We Should Use the Gini Coefficient to Assess Punctuated Equilibrium Theory

2021 ◽  
pp. 1-6
Author(s):  
Constantin Kaplaner ◽  
Yves Steinebach
Keyword(s):  
Policy Change ◽  
Gini Coefficient ◽  
Policy Making ◽  
Punctuated Equilibrium ◽  
Equilibrium Theory ◽  
Punctuated Equilibrium Theory ◽  
The Gini Coefficient ◽  
Precise Measure

Abstract Punctuated Equilibrium Theory posits that policy-making is generally characterized by long periods of stability that are interrupted by short periods of fundamental policy change. The literature converged on the measure of kurtosis and L-kurtosis to assess these change patterns. In this letter, we critically discuss these measures and propose the Gini coefficient as a (1) comparable, but (2) more intuitive, and (3) more precise measure of “punctuated” change patterns.

scholarly journals The Security of Energy Supply from Internal Combustion Engines Using Coal Mine Methane—Forecasting of the Electrical Energy Generation

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3049
Author(s):  
Marek Borowski ◽  
Piotr Życzkowski ◽  
Klaudia Zwolińska ◽  
Rafał Łuczak ◽  
Zbigniew Kuczera
Keyword(s):  
Coal Mine ◽  
Predictive Models ◽  
Coalbed Methane ◽  
Internal Combustion Engines ◽  
Drainage System ◽  
Production Capacity ◽  
Methane Combustion ◽  
Economic Benefits ◽  
Electricity Production ◽  
Coal Mine Methane

Increasing emissions from mining areas and a high global warming potential of methane have caused gas management to become a vital challenge. At the same time, it provides the opportunity to obtain economic benefits. In addition, the use of combined heat and power (CHP) in the case of coalbed methane combustion enables much more efficient use of this fuel. The article analyses the possibility of electricity production using gas engines fueled with methane captured from the Budryk coal mine in Poland. The basic issue concerning the energy production from coalbed methane is the continuity of supply, which is to ensure the required amount and concentration of the gas mixture for combustion. Hence, the reliability of supply for electricity production is of key importance. The analysis included the basic characterization of both the daily and annual methane capture by the mine’s methane drainage system, as well as the development of predictive models to determine electricity production based on hourly capture and time parameters. To forecast electricity production, predictive models that are based on five parameters have been adopted. Models were prepared based on three time variables, i.e., month, day, hour, and two values from the gas drainage system-capture and concentration of the methane. For this purpose, artificial neural networks with different properties were tested. The developed models have a high value of correlation coefficient. but showed deviations concerning the very low values persisting for a short time. The study shows that electricity production forecasting is possible, but it requires data on many variables that directly affect the production capacity of the system.

Wave Energy Hyperbaric Device for Electricity Production

2007 ◽  
Author(s):  
Segen F. Estefen ◽  
Paulo Roberto da Costa ◽  
Eliab Ricarte ◽  
Marcelo M. Pinheiro
Keyword(s):  
Power Generation ◽  
Wave Energy ◽  
Experimental Results ◽  
Electricity Production ◽  
Scale Model ◽  
Small Scale ◽  
Regular Waves ◽  
Hyperbaric Chamber ◽  
Small Scale Model

Wave energy is a renewable and non-polluting source and its use is being studied in different countries. The paper presents an overview on the harnessing of energy from waves and the activities associated with setting up a plant for extracting energy from waves in Port of Pecem, on the coast of Ceara State, Brazil. The technology employed is based on storing water under pressure in a hyperbaric chamber, from which a controlled jet of water drives a standard turbine. The wave resource at the proposed location is presented in terms of statistics data obtained from previous monitoring. The device components are described and small scale model tested under regular waves representatives of the installation region. Based on the experimental results values of prescribed pressures are identified in order to optimize the power generation.

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