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With the advance of electricity market, all distributed power generators will participate in electric power bidding, start-up and shutdown of the unit must be considered in objective function of purchasing electricity. Therefore, this paper establishes the mathematical model of purchasing electricity optimization from distributed generators, which takes total costs from many distributed generators...
Different techniques for the optimization of utility systems have been developed in recent decades. The objective of this paper is to introduce a new mathematical programming model applied to the operational optimization for the utility system. Particle Swarm Optimization (PSO) presented by Kennedy has been described for solving mixed integer linear programming (MILP). It is a simple algorithm that...
Under deregulated environment, accurate electricity price forecasting is a crucial issue concerned by all participants. Experience shows that single forecasting model is very difficult to improve the forecasting accuracy due to the complicated factors affecting electricity prices. A particle swarm optimization (PSO) based GM(1,2) method on day-ahead electricity price forecasting with predicted error...
Under deregulated environment, accurate price forecasting provides crucial information for electricity market participants to make reasonable competing strategies. With comprehensive consideration of the changing rules of the day-ahead electricity price of the PJM electricity market, a day-ahead electricity price forecasting method based on particle swarm optimization (PSO) and GM(1, 1) model is proposed,...
In the past decades, there has been an implicit explosion of absorption in Artificial Intelligence (AI) field. AI supplies robust and flexible means for acquiring solutions to a diversity of problems that often cannot be solved by other, more traditional and orthodox methods. Nowadays, its use is increasing rapidly in many sectors of complicated practical problems. Meanwhile, electrical energy demand...
In order to improve the forecasting precision of traditional grey model for short-term price in competitive electricity market, a novel grey model is presented in this paper based on period-decoupled price sequence. According to the interval time of market cleaning, the historical price data are divided into 24 sequences or 48 sequences. In the proposed grey model, two kinds of price sequences, called...
To improve the forecasting precision of electricity consumption, and content the demand of marketing, we establish the model by combining particle swarm optimization (PSO) with the improved grey theory. The method is simple, easy to do practice and its convergence rate is quick. It can find the overall optimal solution of problems in great probability, and can effectively overcome the shortage of...
Time series analysis is an important and complex problem in machine learning. Support vector machine (SVM) has recently emerged as a powerful technique for solving problems in regression, but its performance mainly depends on the parameters selection of it. Parameters selection for SVM is very complex in nature and quite hard to solve by conventional optimization techniques, which constrains its application...
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