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The present research proposes a comprehensive model to determine the retailer strategy for purchasing electrical power from the wholesale and/or local market in an active distribution network. The uncertainties associated with the load and distributed generation resources in the active distribution network, wholesale market price, and behavior of the local market players were all incorporated into the presented model. The demand response program benefits the retailers in governing the risks. A risk-based decision-making scheme was established in this paper that considered every instrument accessible to retailers and the uncertainties involved. The major objective of this paper is to maximize the retailer benefit concerning a tolerable risk. In order to model risks, scenario theories were exploited and Particle Swarm Optimization (PSO) was employed to solve the optimization problem. The proposed scheme was simulated in an actual network, and the obtained results confirmed the effectiveness and computability of this method. [ABSTRACT FROM AUTHOR]

Curtailment of the production of wind resources due to uncertainty can affect the expansion of the transmission networks. The issue that needs to be addressed is how to expand the transmission network, which is accompanied by increasing wind energy utilization. In this paper, a new framework is proposed to solve the transmission expansion planning (TEP) problem in the presence of wind farms, considering wind curtailment cost. The proposed model is a risk-constrained stochastic bi-level problem that, the difference between the expected social welfare and investment cost is maximized at the upper level where optimal decisions on expansion plans are adopted by the independent system operator (ISO). To make the best use of wind generation resources, a new term called wind power curtailment cost is added to the upper level. Also, the risk index is included in expansion decisions. The market-clearing is considered at the lower level, aiming at maximizing social welfare. Uncertainties relating to wind power and the forecasted demand are modeled by sets of scenarios. Using duality theory, the proposed framework is modeled as mixed-integer linear programming (MILP) problem. The model is examined using the classical Garver's six-bus test system and the IEEE 24-bus reliability test system (RTS). The results show that by considering the wind curtailment cost, the transmission network is expanded in a way that increases the wind energy utilization factor from 92.05% to 95.17%. [ABSTRACT FROM AUTHOR]

In this paper, we are proposing a novel approach for solving power economic dispatch among generation units, considering valve point effects and CO2 emissions. Here we are using particle swarm optimization (PSO) technique for solving an optimization problem. Besides a new hybrid priority list is applied for handling emissions constraint. In this respect, power economic dispatch is introduced, which comprises both objective functions and constraints. Then, the proposed algorithm is completely introduced. Efficiency of the algorithm has been tested in two system tests, as case studies. A few scenarios have been considered and simulations were conducted for demonstrating the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]