ATC evaluation with multi-objective optimization of system stability and economic benefit in power market and its enhancement by FACTS devices

2006 ◽  
Author(s):  
Cheng Yun ◽  
T.S. Chung ◽  
C.W. Yu ◽  
C.Y. Chung
Keyword(s):  
Economic Benefit ◽  
Power Market ◽  
System Stability ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Facts Devices

scholarly journals Multi-Objective Optimization of Smallholder Apple Production: Lessons from the Bohai Bay Region

2020 ◽  
Vol 12 (16) ◽  
pp. 6496
Author(s):  
Shan Jiang ◽  
Hongyan Zhang ◽  
Wenfeng Cong ◽  
Zhengyuan Liang ◽  
Qiran Ren ◽  
...  
Keyword(s):  
Economic Benefit ◽  
Water Footprint ◽  
Bohai Bay ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
P Use Efficiency ◽  
Gray Water ◽  
Use Efficiency ◽  
Apple Production ◽  
Objective Improvement

Transforming apple production to one with high yield and economic benefit but low environmental impact by improving P-use efficiency is an essential objective in China. However, the potential for multi-objective improvement for smallholders and the corresponding implications for horticultural practices are not fully appreciated. Survey data collected from 99 apple producers in Quzhou County of Bohai Bay Region were analyzed by the Pareto-based multi-objective optimization method to determine the potential of multi-objective improvement in apple production. With current practices, apple yield was 45 t ha−1, and the economic benefit was nearly 83,000 CNY ha−1 but with as much as 344 kg P ha−1 input mainly from chemical fertilizer and manure. P gray water footprint was up to 27,200 m3 ha−1 due to low P-use efficiency. However, Pareto-optimized production, yield, and economic benefit could be improved by 38% and 111%, respectively. With a concurrent improvement in P-use efficiency, P gray water footprint was reduced by 29%. Multi-objective optimization was achieved with integrated horticultural practices. The study indicated that multi-objective optimization could be achieved at a smallholder scale with realistic changes in integrated horticultural practices. These findings serve to improve the understanding of multi-objective optimization for smallholders, identify possible constraints, and contribute to the development of strategies for sustainable apple production.

scholarly journals Investment Strategy and Multi–Objective Optimization Scheme for Premium Power under the Background of the Opening of Electric Retail Side

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2135 ◽  
Author(s):  
Yuanqian Ma ◽  
Xianyong Xiao ◽  
Ying Wang
Keyword(s):  
Value Added ◽  
Power Market ◽  
Investment Strategy ◽  
Matching Theory ◽  
High Tech ◽  
Main Concern ◽  
Determination Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Psychological Perceptions

With the opening of electric retail side, premium power value-added service has become a main concern for both sensitive customers (SCs) and new electric retail companies (NERCs). However, due to the lack of appropriate investment strategy and optimal premium power investment scheme (PPIS) determination method, the premium power market is difficult to form, thus SCs’ demand for premium power is difficult to meet. Under such condition, how to determine the investment strategy and choose the optimal PPIS are problems that need to be solved. Motivated by this, this paper proposes a multi–participant premium power investment strategy and an optimal PPIS determination method. Suppose that the NERC and the corresponding SCs have already been determined, according to two–sided matching theory, taking SCs’ and NERC’s disappointment–rejoicing psychological perceptions into consideration, premium power perceived utility (PU) (i.e., the perceived effectiveness or satisfaction degree) can be obtained, and a multi-objective optimization model of investment scheme is established. Finally, a field survey has been conducted by the authors on typical high-tech manufacturers (HTMs) located in a High-Tech Park in Sichuan, China. The matching results have been verified by the actual survey. The proposed method is a good way to manage the premium power market.

scholarly journals Multi-Objective Optimization for Metal Mine Production Technical Indicators with NSGA-II and ANN Algorithms

2018 ◽  
Author(s):  
Xunhong Wang ◽  
Xiaowei Gu ◽  
Qing Wang ◽  
Xiaochuan Xu ◽  
Minggui Zheng
Keyword(s):  
Economic Benefit ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Technical Indicators ◽  
Multi Objective ◽  
Metal Mine ◽  
Mine Production ◽  
Metal Volume

The selection of the best mine production technical indicators is crucial to increasing a mine’s economic benefit and saving resources for sustainability. Therefore, this research proposes a ‘multi-objective optimization model’ based on a ‘fast and elitist Non-dominated Sorting Genetic Algorithm’ (NSGA-II) and ‘Artificial Neural Networks’ (ANN) for the optimization of production technical indicators in the entire geology, mining and beneficiation metal mine production processes. The multi-objective optimization model has decision variables including ‘cut-off grade,’ ‘industrial grade’ and ‘loss rate,’ with objectives being ‘economic benefit (profit)’ and ‘resource benefit (metal volume).’ First, the relationship between the technical indicators of mine production is studied. The REG model, MATLAB’s own ksdensity function and the BP neural network are used to calculate the ore weight, the probability density of grade distribution, the dilution rate, the concentration ratio and the concentrate grade, and to further calculate geological reserves, profit and metal volume. Then, the NSGA-II is applied to maximize profit and metal volume simultaneously. Finally, the model is applied to the Huogeqi copper mine. The optimization result is a set of multiple optimal solutions called Pareto optimal solutions. Compared with the plan data, the profit and metal volume of partial optimization results increased by 2.89% and 2.64% simultaneously. These Pareto optimal solutions can help decision makers in bettering the actual process of metal mine production.

A non-dominated Sorting Hybrid Cuckoo Search Algorithm for multi-objective optimization in the presence of FACTS devices

2017 ◽  
Vol 88 (1) ◽  
pp. 44-53 ◽  
Author(s):  
M. Balasubbareddya ◽  
S. Sivanagarajub ◽  
Ch. Venkata Sureshc ◽  
A. V. Naresh Babud ◽  
D. Srilathaa
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Facts Devices
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