The primary objective of this research article is to introduce Differential Evolution (DE) algorithm for solving bidding strategy in deregulated power market. Suppliers (GENCOs) and consumers (DISCOs) participate in t...The primary objective of this research article is to introduce Differential Evolution (DE) algorithm for solving bidding strategy in deregulated power market. Suppliers (GENCOs) and consumers (DISCOs) participate in the bidding process in order to maximize the profit of suppliers and benefits of the consumers. Each supplier bids strategically by choosing the bidding coefficients to counter the competitors bidding strategy. Electricity or electric power is traded through bidding in the power exchange. GENCOs sell energy to power exchange and in turn ancillary services to Independent System Operator (ISO). In this paper, Differential Evolution algorithm is proposed for solving bidding strategy problem in operation of power system under deregulated environment. An IEEE 30 bus system with six generators and two large consumers is employed to demonstrate the proposed technique. The results show the adaptability of the proposed method compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Monte Carlo simulation in terms of Market Clearing Price (MCP).展开更多
The hydrothermal scheduling in the electric power market becomes difficult because of introducing competition and considering sorts of constraints. An augmented Lagrangian approach is adopted to solve the problem,whic...The hydrothermal scheduling in the electric power market becomes difficult because of introducing competition and considering sorts of constraints. An augmented Lagrangian approach is adopted to solve the problem,which adds to the standard Lagrangian function a quadratic penalty term without changing its dual property,and reduces the oscillation in iterations. According to the theory of large system coordination and decomposition,the problem is divided into hydro sub-problem and thermal sub-problem,which are coordinated by updating the Lagrangian multipliers,then the optimal solution is obtained. Our results for a test system show that the augmented Lagrangian approach can make the problem converge into the optimal solution quickly.展开更多
An improved network flow algorithm, which includes the minimum cost network flow and the same period network flow, is proposed to solve the optimization of cascaded hydroelectric power plants in a competitive electric...An improved network flow algorithm, which includes the minimum cost network flow and the same period network flow, is proposed to solve the optimization of cascaded hydroelectric power plants in a competitive electricity market. The typical network flow is used to find the feasible flow and add the discharge water to different cascaded hydroelectric power plants at the same step. The same period network flow is used to find the optimal flow and add the power output at a different step. This new algorithm retains the advantages of the typical network flow, such as simplicity and ease of realization. The result of the case analysis indicates that the new algorithm can achieve high calculation precision and can be used to calculate the optimal operation of cascaded hydroelectric power plants.展开更多
文摘The primary objective of this research article is to introduce Differential Evolution (DE) algorithm for solving bidding strategy in deregulated power market. Suppliers (GENCOs) and consumers (DISCOs) participate in the bidding process in order to maximize the profit of suppliers and benefits of the consumers. Each supplier bids strategically by choosing the bidding coefficients to counter the competitors bidding strategy. Electricity or electric power is traded through bidding in the power exchange. GENCOs sell energy to power exchange and in turn ancillary services to Independent System Operator (ISO). In this paper, Differential Evolution algorithm is proposed for solving bidding strategy problem in operation of power system under deregulated environment. An IEEE 30 bus system with six generators and two large consumers is employed to demonstrate the proposed technique. The results show the adaptability of the proposed method compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Monte Carlo simulation in terms of Market Clearing Price (MCP).
基金the Specialized Research Fund for the Doctoral Program of High Education(Grant No.20050213006) the Key Science Research Project of Heilongjiang Province(Grant No.GD07A304).
文摘The hydrothermal scheduling in the electric power market becomes difficult because of introducing competition and considering sorts of constraints. An augmented Lagrangian approach is adopted to solve the problem,which adds to the standard Lagrangian function a quadratic penalty term without changing its dual property,and reduces the oscillation in iterations. According to the theory of large system coordination and decomposition,the problem is divided into hydro sub-problem and thermal sub-problem,which are coordinated by updating the Lagrangian multipliers,then the optimal solution is obtained. Our results for a test system show that the augmented Lagrangian approach can make the problem converge into the optimal solution quickly.
文摘An improved network flow algorithm, which includes the minimum cost network flow and the same period network flow, is proposed to solve the optimization of cascaded hydroelectric power plants in a competitive electricity market. The typical network flow is used to find the feasible flow and add the discharge water to different cascaded hydroelectric power plants at the same step. The same period network flow is used to find the optimal flow and add the power output at a different step. This new algorithm retains the advantages of the typical network flow, such as simplicity and ease of realization. The result of the case analysis indicates that the new algorithm can achieve high calculation precision and can be used to calculate the optimal operation of cascaded hydroelectric power plants.
