As the share of variable renewable energy increases, adequate prices on electricity spot markets become increasingly important as they set signals for scarcity, investment, or demand response. Market prices are derive...
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As the share of variable renewable energy increases, adequate prices on electricity spot markets become increasingly important as they set signals for scarcity, investment, or demand response. Market prices are derived from the underlying welfare maximization problem. On electricity spot markets, this optimization problem is based on the non-convex and non-linear Alternating Current Optimal Power Flow (ACOPF) model. Since the ACOPF is intractable, electricity markets around the world use a linear approximation, the Direct Current Optimal Power Flow (DCOPF) model. Recent research has led to better non-linear relaxations of the ACOPF. We show that these non-linear relaxations increase welfare and imply significantly lower redispatch costs and side-payments. Most importantly, we show that the price signals obtained from non-linear relaxations are much improved. The DCOPF often yields high price differences between nodes when there is no line congestion in the AC-feasible solution or vice versa. Such biased price signals pose a significant problem in practice as they lead to inefficient demand response, distorted investment signals, and incorrect congestion incomes. The use of non-linear relaxations mitigates this problem and provides an important advantage of the resulting prices over prices based on the DCOPF.
Fuzzy multi-objective programming is an important optimization method to solve many complex practical problems. In this work, the applications of fuzzy multi-objective programming modeling for solving the practical pr...
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Fuzzy multi-objective programming is an important optimization method to solve many complex practical problems. In this work, the applications of fuzzy multi-objective programming modeling for solving the practical problems in regional water resources optimal scheduling are studied. In order to strengthen the planning and management of water resources, the limited water resources are fully and effectively used scientifically. And because of the multi-objective and uncertainties of the regional water resources optimization scheduling problem, this paper adopts the fuzzy multi-objective programming method to deal with this complex practical problem. Based on the fuzzy multi-objective programming technique, the fuzzy multi-objective nonlinearprogramming model of regional water resources optimal dispatching is established. The multi-objective includes three goals: economic benefit, environmental benefit and social benefit. Then, the establishment and solving steps of the fuzzy multi-objective nonlinearprogramming model are introduced for the established model. Finally, the proposed scheme is evaluated and sorted. Finally, combined with the actual situation of a city to solve, verify the validity of the model.
Classical control laws for power converters are based on the average model. Usually, they have a good performance in the transient. Nevertheless, the steady state behavior is not well-controlled (waveform, subharmonic...
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ISBN:
(纸本)9781424456956
Classical control laws for power converters are based on the average model. Usually, they have a good performance in the transient. Nevertheless, the steady state behavior is not well-controlled (waveform, subharmonics, etc.). This article shows a predictive approach that reaches an optimal periodic cycle from a set-point of the average model. The method uses the sensitivity functions and a Newton algorithm which allows to track an optimal trajectory based on a cost function.
Enterprises need to develop a process to determine how to find and develop new product ideas and finally, how to successfully introduce them to the *** address this problem,conceptions of Optimal Introduction Period a...
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Enterprises need to develop a process to determine how to find and develop new product ideas and finally, how to successfully introduce them to the *** address this problem,conceptions of Optimal Introduction Period and Correlative Profit were *** on the quantitative description of the product life cycle,a non-linear Semi-Infinite programming model of new product introduction was *** proposed model was solved by improved Particle Swarm Optimization(PSO) *** solution of the given example shows that Particle Swarm Optimization has become the hotspot of evolutionary computation because of its excellent performance and simplicity for implement in solving combined optimization problems.
Collision detection is very important to improve the truth and immersion in the virtual environment. Firstly the paper analyzes the problems that exist in traditional algorithms. There is no algorithm suitable to ever...
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Collision detection is very important to improve the truth and immersion in the virtual environment. Firstly the paper analyzes the problems that exist in traditional algorithms. There is no algorithm suitable to every situation, and the more complex the situations are, the more rapidly the efficiency declines. Secondly the paper analyses the problem of collision detection in theory, and then converts the problem of the collision detection to the non-linear programming problem with restricted conditions. In this paper, the definition of the distance between two objects and for which the quantum coding is given. Through the steps, such as quantum clone, quantum variation, the problem of collision detection is solved. Finally, the simulation test shows that the quantum-inspired immune algorithm has much more effective impact on solving the extreme-value problem compared to the traditional genetic algorithm. It is feasible to use the algorithm in collision detection.
This paper establishes the optimization model based on the Problem C of 2010 China Undergraduate Mathematical Contest in *** the Problem I,according to the different relative locations between
This paper establishes the optimization model based on the Problem C of 2010 China Undergraduate Mathematical Contest in *** the Problem I,according to the different relative locations between
The continuous berth allocation problem （BAPC） solves the BAP with continuous berth space and continuous time to optimize the utilization of space and time of the ports.A non-linear programming （NLP） model is buil...
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The continuous berth allocation problem （BAPC） solves the BAP with continuous berth space and continuous time to optimize the utilization of space and time of the ports.A non-linear programming （NLP） model is built and an immune algorithm （IA） is proposed to solve *** effects of the number of vessels,the berth space length and the length of planning time are well controlled so that the approach can handle supper large-scale BAP with promising *** proposed model and algorithm can be embedded into berth scheduling modules to provide a fast and flexible solution for real-world BAPC to improve the port efficiency.
This study applies the concept of the Voronoi diagram to a simultaneous search for the optimal shape and location of a polygon. Suppose that an area-like facility is contained in a finite two-dimensional uniform regio...
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This study applies the concept of the Voronoi diagram to a simultaneous search for the optimal shape and location of a polygon. Suppose that an area-like facility is contained in a finite two-dimensional uniform region. The objective of our study is to optimize the shape and location of the facility (polygon) in terms of the mini-sum distance from all the surrounding points. When the mini-sum distance is minimized, the polygon forms a star-shaped polygon at the center, and when maximized, it verges alongside the edge of the region. The results are represented by an approximate value of local optima obtained by replacing the boundary of the polygon with points. We justify the results by examining the difference between the value obtained from a line Voronoi diagram and that generated from points. International Federation of Operational Research Societies 2001.
With the rapid development of social economy, the society water consumption has increased dramatically which also lead to sharp contradiction between supply and demand, so how to allocate limited water resources r...
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With the rapid development of social economy, the society water consumption has increased dramatically which also lead to sharp contradiction between supply and demand, so how to allocate limited water resources reasonable has become a reality and urgent task of water management. With the author further studying the reservoir regulation theory and mechanism, the deterministic optimization is developed based on multi-objective optimizing reservoir scheduling model, using nonlinearprogramming as optimization algorithm for constructing the universal optimizing reservoir scheduling model And based on multi-objective thought, it has produced a set of Pareto frontier solution set, through the temple, the application of EPing hydropower station get a series of decisionmaking plan, so that policymakers can choose the preference for decision-making plan.
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