Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

Aiming at the problems of large-scale wind and solar grid connection,how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations,a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed.Firstly,the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output,obtains the optimal output value under the economic conditions of each new energy station,and then obtains the maximum consumption space of the new energy station.Secondly,based on the optimization results of the first stage,the second stage dispatching model uses the dispatching method of fuzzy comprehensive ranking priority to prioritize the new energy stations,and then makes a fair allocation to the dispatching of the wind and solar stations.Finally,the analysis of a specific example shows that themodel can take into account the fairness of active power distribution of new energy stations on the basis of ensuring the economy of system operation,make full use of the consumption space,and realize the medium and long-term fairness distribution of dispatching plan.

Online complex nonlinear industrial process operating optimality assessment using modified robust total kernel partial M-regression

Although industrial processes often perform perfectly under design conditions, they may deviate from the optimal operating point owing to parameters drift, environmental disturbances, etc. Thus, it is necessary to develop efficacious strategies or procedure to assess the process performance online. In this paper, we explore the issue of operating optimality assessment for complex industrial processes based on performance-similarity considering nonlinearities and outliers simultaneously, and a general enforced online performance assessment framework is proposed. In the offline part, a new and modified total robust kernel projection to latent structures algorithm,T-KPRM, is proposed and used to evaluate the complex nonlinear industrial process, which can effectively extract the optimal-index-related process variation information from process data and establish assessment models for each performance grades overcoming the effects of outlier. In the online part, the online assessment results can be obtained by calculating the similarity between the online data from a sliding window and each of the performance grades. Furthermore, in order to improve the accuracy of online assessment, we propose an online assessment strategy taking account of the effects of noise and process uncertainties. The Euclidean distance between the sliding data window and the optimal evaluation level is employed to measure the contribution rates of variables, which indicate the possible reason for the non-optimal operating performance. The proposed framework is tested on a real industrial case: dense medium coal preparation process, and the results shows the efficiency of the proposed method comparing to the existing method.

Scheme to Implement Optimal Asymmetric Economical Phase-Covariant Quantum Cloning in Cavity QED

We propose an experimentally feasible scheme to implement the optimal asymmetric economical 1→2 phase-covariant quantum cloning in two dimensions based on the cavity QED technique. The protocol is very simple and only two atoms are required. Our scheme is insensitive to the cavity field states and cavity decay. During the processes, the cavity is only virtually excited and it thus greatly prolongs the efficient decoherent time. Therefore, it may be realized in experiment.

Economically Optimal Rates and Nutrients Use Efficiency Indices of Maize to the Application of Different Rates of Nutrients in Central Rift Valley of Ethiopia

The use of balanced fertilizers in adequate amount is very important to increase crop productivity and production in Ethiopia. The study was executed to quantify maize (Zea mays L.) grain yield response to different rates of nitrogen (N), phosphorus (P), potassium (K) and sulfur (S) under balanced fertilization of other nutrients. On farm trials were conducted at seven sites on 8 farmers’ fields in Negele Arsi districts, west Arsi zone of Oromia region for three consecutive cropping seasons (2014-2016). Six rates of N, P, S and eight rates of K treatments established separately for each nutrient were laid out in randomized complete block (RCB) design with three replicates per farm. Nutrient response function modelling showed that 184, 20 and 80 kg•ha−1 were the agronomic optimum rate for N, P, and K, respectively. Mean agronomic efficiency (AE) of N, P and K were recorded at the lower rates of these nutrients, application of 46, 10 and 20 kg•ha−1 N, P and K resulted in 19.1, 61.0, and 24 kg additional grain yield•kg−1 N, P and K, respectively. Also, the mean partial factor productivity (PFP) of N, P and K were 77.6, 370 and 158 kg additional grain•kg−1 applied N, P and K respectively. Economically optimal rate (EOR) of N, P and K were 48 - 114 kg•ha−1 N with CP 8 - 3.5, 12 - 20 kg•ha−1 P with CP 18 - 4.5 and 32 - 53 kg•ha−1 K with CP 8-4, from these rates net returns of US$487.23 - 143.30, US$698.16 - 498.3 and US$359.31 - 193.63 could be obtained respectively. To conclude, application of 84, 12 and 40 kg•ha−1 N, P and K could be recommended for the production of maize.

Predictive Mathematical and Statistical Modeling of the Dynamic Poverty Problem in Burundi: Case of an Innovative Economic Optimization System

The mathematical and statistical modeling of the problem of poverty is a major challenge given Burundi’s economic development. Innovative economic optimization systems are widely needed to face the problem of the dynamic of the poverty in Burundi. The Burundian economy shows an inflation rate of -1.5% in 2018 for the Gross Domestic Product growth real rate of 2.8% in 2016. In this research, the aim is to find a model that contributes to solving the problem of poverty in Burundi. The results of this research fill the knowledge gap in the modeling and optimization of the Burundian economic system. The aim of this model is to solve an optimization problem combining the variables of production, consumption, budget, human resources and available raw materials. Scientific modeling and optimal solving of the poverty problem show the tools for measuring poverty rate and determining various countries’ poverty levels when considering advanced knowledge. In addition, investigating the aspects of poverty will properly orient development aid to developing countries and thus, achieve their objectives of growth and the fight against poverty. This paper provides a new and innovative framework for global scientific research regarding the multiple facets of this problem. An estimate of the poverty rate allows good progress with the theory and optimization methods in measuring the poverty rate and achieving sustainable development goals. By comparing the annual food production and the required annual consumption, there is an imbalance between different types of food. Proteins, minerals and vitamins produced in Burundi are sufficient when considering their consumption as required by the entire Burundian population. This positive contribution for the latter comes from the fact that some cows, goats, fishes, ···, slaughtered in Burundi come from neighboring countries. Real production remains in deficit. The lipids, acids, calcium, fibers and carbohydrates produced in Burundi are insufficient for consumption. This negative contribution proves a Burundian food deficit. It is a decision-making indicator for the design and updating of agricultural policy and implementation programs as well as projects. Investment and economic growth are only possible when food security is mastered. The capital allocated to food investment must be revised upwards. Demographic control is also a relevant indicator to push forward Burundi among the emerging countries in 2040. Meanwhile, better understanding of the determinants of poverty by taking cultural and organizational aspects into account guides managers for poverty reduction projects and programs.

Economic Optimism

Though facing challenges, the Chinese Government has kept a steady hand on the tiller and managed to sail the economy through the first half of 2016 relatively unscathed, sustaining steady economic growth and accelerating economic transformation. According to a report recently released by the National Bureau of Statistics, China＇s GDP growth in the first half of 2016 was 6.7 percent year on year. A slowing growth rate, in relation to past stellar economic performance of around double-digit growth, has, however, given rise to ques- tions about the development trend of the world＇s second largest economy, What will be the highlights of the second half of the year？ What will be the impact of China＇s economic growth on the global economy going forward？ Renowned experts in this field believe there is much resilience and potential for China＇s economy to maintain a stable and healthy growth, Some of their views follow：

Optimized nitrogen application for maximizing yield and minimizing nitrogen loss in film mulching spring maize production on the Loess Plateau,China

Excessive use of N fertilizers(driven by high-yield goals)and its consequent environmental problems are becoming increasingly acute in agricultural systems.A 2-year field experiment was conducted to investigate the effects of three N application methods(application of solid granular urea once(OF)or twice(TF),application of solid granular urea mixed with controlled-release urea once(MF),and six N rates(0,60,120,180,240,and 300 kg N ha^(-1))on maize yield,economic benefits,N use efficiency,and soil N balance in the maize(Zea mays L.)film mulching system on the Loess Plateau,China.The grain yield and economic return of maize were significantly affected by the N rate and application method.Compared with the OF treatment,the MF treatment not only increased the maize yield(increased by 9.0-16.7%)but also improved the economic return(increased by 10.9-25.8%).The agronomic N use efficiency(NAE),N partial factor productivity(NPFP)and recovery N efficiency(NRE)were significantly improved by 19.3-66.7,9.0-16.7 and 40.2-71.5%,respectively,compared with the OF treatment.The economic optimal N rate(EONR)of the OF,TF,and MF was 145.6,147.2,and 144.9 kg ha^(-1) in 2019,and 206.4,186.4,and 146.0 kg ha^(-1) in 2020,respectively.The apparent soil N loss at EONR of the OF,TF,and MF were 97.1-100.5,78.5-79.3,and 50.5-68.1 kg ha^(-1),respectively.These results support MF as a one-time N application method for delivering high yields and economic benefits,with low N input requirements within film mulching spring maize system on the Loess Plateau.

Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Maximum Expected Benefit-Oriented Optimal Maintenance Decision for Existing Bridges

Abstract An optimal maintenance program is the key to making appropriate decisions to minimize cost and maintain an appropriate lev- el of safety. In this paper, the strategy on repairing and strengthening of existing bridges based on time-dependent reliability was analyzed with the maximum expected benefit as the objective function. Risk ranking and lifecycle cost analysis were considered in the reliability-based bridge assessment. A practical application of risk-ranking decision was illustrated herein based on updated inspection informarion with the bridge at survival age 35. The effects of improvement of live load and difference of repair methods on time-dependent reliability of existing bridges were studied. The decision method can be used in real projects, with the cost of failure consequence and the risk of failure considered.

Online payment fraud:from anomaly detection to risk management

Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account.Successfully preventing this requires the detection of as many fraudsters as possible,without producing too many false alarms.This is a challenge for machine learning owing to the extremely imbalanced data and complexity of fraud.In addition,classical machine learning methods must be extended,minimizing expected financial losses.Finally,fraud can only be combated systematically and economically if the risks and costs in payment channels are known.We define three models that overcome these challenges:machine learning-based fraud detection,economic optimization of machine learning results,and a risk model to predict the risk of fraud while considering countermeasures.The models were tested utilizing real data.Our machine learning model alone reduces the expected and unexpected losses in the three aggregated payment channels by 15%compared to a benchmark consisting of static if-then rules.Optimizing the machine-learning model further reduces the expected losses by 52%.These results hold with a low false positive rate of 0.4%.Thus,the risk framework of the three models is viable from a business and risk perspective.

Modelling and Optimal Design of Hybrid Power System Photovoltaic/Solid Oxide Fuel Cell for a Mediterranean City

This work presents a hybrid power system consisting of photovoltaic and solid oxide fuel cell(PV-SOFC)for electricity production and hydrogen production.The simulation of this hybrid system is adjusted for Bou-Zedjar city in north Algeria.Homer software was used for this simulation to calculate the power output and the total net present cost.The method used depends on the annual average monthly values of clearness index and radiation for which the energy contributions are determined for each component of PV/SOFC hybrid system.The economic study is more important criterion in the proposed hybrid system,and the results show that the cost is very suitable for the use of this hybrid system,which ensures that the area is fed continuously with the sufficient energy for the load which assumed to be 500 kW in the peak season.The optimized results of the present study show that the photovoltaic is capable of generating 8733 kW electricity while the SOFC produces 500 kW electricity.The electrolyzer is capable of producing 238750 kg of hydrogen which is used as fuel in the SOFC to compensate the energy lack in nights and during peak season.

Repair and Strengthening Assessment of Existing Bridges Based on Time-Dependent Reliability Analysis

The strategy on repair and strengthening of existing bridges based on time-dependent reliability was analyzed with the maximum expected benefit as the objective function. A sample of risk-ranking decision was illustrated based on updated inspection information with 35 survival age. The effect of improvement of live loads and difference of repair methods on time-dependent reliability of existing bridges are considered. The results show that the decision method can be used in real project, with the cost of failure consequence and the risk of failure considered.

Simultaneous optimization of heat-integrated crude oil distillation systems

Crude oil distillation is important in refining industry. Operating variables of distillation process have a critical effect on product output value and energy consumption. However, the objectives of minimum energy consumption and maximum product output value do not coordinate with each other and do not lead to the maximum economic benefit of a refinery. In this paper, a systematic optimization approach is proposed for the maximum annual economic benefit of an existing crude oil distillation system, considering product output value and energy consumption simultaneously. A shortcut model in Aspen Plus is used to describe the crude oil distillation and the pinch analysis is adopted to identify the target of energy recovery. The optimization is a nonlinear programming problem and solved by stochastic algorithm of particle warm optimization.

The Optimal Control for Regional Economic Growth

The model of consumption principle to realize the optimal growth of the regional economyis proposed on the base of analysing the relation of production and consumption with consumptionutility as optimization object. According to the model, the numerical value of the optimal control ofconsumption is given in order to realize the ninth five-year plan of the regional economic growth.

Economic Optimism

Ever since January 14 when the Chinese Government unveiled plans to revamp the steel and automobile sectors, the country has embarked on an ambitious and comprehensive scheme of restructuring some of its key industries. This was done in an effort to keep the economy on track amid an adverse economic situation. Eight other sectors have been added into this revitalization package, ranging from electronics and information technologies to textiles, shipbuilding and petrochemicals,

Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand

This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.

The Evaluation Model of Government Intervention (GI) and its Optimization

The paper discusses how to reach the equilibrium and optimization GI during the period of economic transformation. The market economy might not work because of its mechanism flaws, based on the assumption that the government is the supplier and the market economy is the demander Of GI, there is an equilibrium and optimization issue. The theory suggests that GI could reach equilibrium through adjusting the government revenue, thus leads to the result of functional complement between the market economy and the GI, and the optimum economic efficiency.