An efficient scheduling approach for an iron-steel plant equipped with self-generation equipment under time-of-use electricity tariffs
31
Citation
45
Reference
10
Related Paper
Citation Trend
Electricity system
Electricity demand
Cite
Citations (47)
This paper presents the findings of our study on forecasting the levelized cost of electricity of different electricity generation technologies including renewable energy (solar PV, hydropower, biomass and wind) until 2030. Usually, the cost of electrical generation from renewable and conventional sources are compared by using the LCOE method (Levelized Cost Of Energy). In general, the LCOE is calculated based on the assumptions for each technology. In this paper, we evaluate the LCOE of the various electricity generation techniques for the case of Lebanon. The study predicts future evolution of these costs in Lebanon until 2030 according to specic assumptions related to each technology and taking into account the triple aspects : technical, economic and environmental. The generation costs don't depend only on investment, maintenance and fuel costs, but also on the cost of carbon emitted by each technology per unit of the electricity produced. We focus our analysis on these assumptions and the impact of their variability on the cost by using sensitivity analysis. Our study shows that by 2030, renewable generation technologies will remain more expensive than fossil-fueled technologies. However, within certain measures taken by the State, as integration of a carbon price, renewable energy resources could emerge strongly in the electricity generation investment planning and become much competitive.
Investment
Unit cost
Cite
Citations (0)
This paper introduces the optimization methods of Genetic Algorithm.Based on the Different Location Crossover and the Same Location Crossover,a new leading crossover is proposed.Then it is a self-adaptive manner judgment to choose which crossover is used before the crossover operator.At last,five different tests of the simulation function are given.The results show that the leading crossover is more efficient to improve convergence than other crossovers.And the new method is easy to find the optimal solution.
Operator (biology)
Cite
Citations (0)
The marketization process of electricity purchase and power generation and its significance in China
Abstract China’s electricity purchases and power generation have been subject to deterministic catalogue tariffs for a long time. With the continuous improvement of China’s electricity market reform, more and more parts of electricity purchase and power generation use market-based methods to determine electricity prices. This paper reviews the marketization process in China’s electricity purchase and power generation. In view of whether or not to participate in the electricity market, this paper classifies different types of electricity purchase and power generation in China. Finally, it summarizes the significance of China’s electricity purchase and power generation marketization.
Marketization
Electricity retailing
Stand-alone power system
Electric Power Industry
Cite
Citations (1)
It is known that selection and crossover operators contribute to generating solutions in genetic programming (GP). Traditionally, crossover points are selected randomly by a normal (canonical) crossover. However, the traditional method has several difficulties, in that building blocks (i.e. effective partial programs) are broken because of blind application of the normal crossover. This paper proposes a depth-dependent crossover for GP, in which the depth selection ratio is varied according to the depth of a node. This proposed method accumulates building blocks via the encapsulation of the depth-dependent crossover. We compare the performance of GP with depth-dependent crossover with that with normal crossover. Our experimental results clarify that the superiority of the proposed crossover to the normal method.
Crossover study
Cite
Citations (43)
This paper investigates the use of more than one crossover operator to enhance the performance of genetic algorithms. Novel crossover operators are proposed such as the Collision crossover, which is based on the physical rules of elastic collision, in addition to proposing two selection strategies for the crossover operators, one of which is based on selecting the best crossover operator and the other randomly selects any operator. Several experiments on some Travelling Salesman Problems (TSP) have been conducted to evaluate the proposed methods, which are compared to the well-known Modified crossover operator and partially mapped Crossover (PMX) crossover. The results show the importance of some of the proposed methods, such as the collision crossover, in addition to the significant enhancement of the genetic algorithms performance, particularly when using more than one crossover operator.
Operator (biology)
Cite
Citations (2)
Sudan faces an electricity supply shortage despite its abundant natural resources. This paper aims to manage these resources for sustainable power generation to meet Sudan’s electricity demand. The sustainability assessment integrates quantitative analysis of power generation’s impacts on water, land, and greenhouse gas (GHG) emissions, in addition to the levelized cost of electricity (LCOE). Cost-effective, resource- and GHG emission-effective, and GHG-stringent scenarios are executed in this study to investigate the impact of different constraints on the sustainability of power generation in Sudan. The average LCOEAV for these three scenarios is 43.64–100.00 USD/MWh, with the lowest in the cost-effective scenario and the highest in the resource- and GHG emission-effective scenario. The LCOEAV for the stringent scenario is 32% higher than the cost-effective scenario. The two governmental and lowest-cost plans, which serve as the business-as-usual cases in this study, are optimized and comparatively evaluated. The sensitivity analysis is conducted by reducing each clean energy pathway to a minimum LCOE of 42.89 USD/MWh. Solar–photovoltaic (PV), wind, and hydroelectricity pathways are the most sensitive to the LCOE and can significantly contribute to Sudan’s total power generation if their costs are minimal. A rational scenario for power generation in Sudan is developed to improve sustainability performance and avoid the unreliability of the studied scenarios and cases. The rational average generation mix comprises 44% clean energy, 46% fossil fuels, and 10% imported electricity pathways.
Cite
Citations (1)
Carbon offset
Electricity system
Cite
Citations (17)
The Levelized Costs of Energy/Electricity (LCOE) is widely used to compare different power generation technologies by considering the various fixed and variable costs as a single cost metric. The levelized cost of electricity (LCOE) measures the average net present cost of generating electric power over the power plants entire life. As a metric, the levelized cost of energy does not capture all costs that affect the cost of electricity like the system costs. For accuracy of cost analysis, the LCOE is modified to account for other costs e.g., system levelized cost which considers externalities. The value-adjusted levelized cost of electricity (VALCOE) is a metric developed by the International Energy Agency (IEA) that captures the cost and value to the electricity system since the same amount of power may be less or more valuable during peak demand. The levelized cost of storage (LCOS) is another metric applied in comparing alternative energy storage systems for specific energy scenarios i.e. long-term, short-term, and medium-term storage. Another related metric is the Levelized avoided cost of energy (LACE) which n captures information about how the grid operates without the new power plant or storage facility entering service making it more complex than LCOE or LCOS, but more insightful. The value-adjusted levelized cost of electricity (VALCOE) captures both cost and value to the electricity system. Another metric, the Levelized Full System Costs of Electricity (LFSCOE), metric is used to analyze the costs incurred to supply the entire energy market with one power source plus storage presented as one value just like the levelized cost of energy (LCOE). Therefore, the levelized cost of energy (LCOE) metric is universally accepted as a tool for preliminary cost evaluations of generation technologies, but for accurate and reliable assessment, various modifications of the levelized cost of energy/electricity must be applied.
Grid parity
Fixed cost
Cite
Citations (49)
The aim of this study is forecasting of Turkey’s electricity generation and consumption for the period 2017-2027. To achieve this, Turkey’s electricity generation and consumption for the period 1996-2016 was modelled using Grey prediction method GM(1,1). Results showed that the small error probability (p) and posterior error ratio (C) values of GM(1,1) model for Turkey’s electricity generation were obtained as 0.12 and 0.97, respectively, and 0.11 and 0.97, respectively for Turkey’s electricity consumption. So, the level of established GM(1,1) models for Turkey’s electricity generation and Turkey’s electricity consumption is in good level. Additionally, mean absolute percentage error (MAPE) values of GM(1,1) models for Turkey’s electricity generation and consumption were obtained as 3.12% and 3.08%, respectively. Results of F-test showed that p-value of GM(1,1) model for Turkey’s electricity generation and consumption was 0.48. According to these results, GM(1,1) models are suitable for prediction of Turkey’s electricity generation and consumption. Furthermore, the average annual grow rates of Turkey’s electricity generation and consumption for the period 2017-2027 were forecasted as 5.25% and 5.58%, respectively. In addition to this, Turkey’s electricity generation and consumption were forecasted as 405310GWh and 344672GWh, respectively, for 2023.
Consumption
Cite
Citations (7)