In this paper, a novel risk-based, two-objective (technical and economical) optimal reactive POWER dispatch method in a WIND-integrated POWER system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive POWER GENERATION and active POWER loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the WIND speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive POWER resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.

This paper presents an intelligent POWER management strategy for hybrid WIND/ fuel cell/ energy storage POWER GENERATION system. The dynamic models of WIND turbine, fuel cell and energy storage have been used for simulation of hybrid POWER system. In order to design POWER flow control strategy, a fuzzy logic control has been implemented to manage the POWER between POWER sources. The optimal operation of the hybrid POWER system is a main goal of designing POWER management strategy. The hybrid POWER system is simulated in MATLAB/ SIMIULINK environment and different operating conditions have been considered to evaluate the response of POWER management strategy.

The rapid industrialization and growth of world’s human population have resulted in the unprecedented increase in the demand for energy and in particular electricity. Depletion of fossil fuels and impacts of global warming caused widespread attention using renewable energy sources, especially WIND and solar energies. Energy security under varying weather conditions and the corresponding system cost are the two major issues in designing hybrid POWER GENERATION systems. In this paper, the match evaluation method (MEM) is developed based on renewable energy supply/demand match evaluation criteria to size the proposed system in lowest cost. This work is undertaken with triple objective function: inequality coefficient, correlation coefficient, and annualized cost of system. It provides optimum capacity of as many numbers of supplies as required to match with a load demand in lowest investment, so it can handle large-scale design problems. Meteorological data were collected from the city of Zabol, located in south-east of Iran, as a case study. Six types of WIND turbine and also six types of PV modules, with different output POWERs and costs, are considered for this optimization procedure. A battery storage system is used to even out irregularities in meteorological data. A multi-objective particle swarm optimization algorithm has been used for the prediction of an optimized set of design based on the MEM technique. The results of this study are valuable for evaluating the performance of future stand-alone hybrid POWER system. It is worth mentioning that the proposed methodology can be effectively employed for any composition of hybrid energy systems in any locations taking into account the meteorological data and the consumer’s demand.

WIND GENERATION with an uncertain nature poses many challenges in grid integration and secure operation of POWER system. One of these operation problems is the unit commitment. Demand Response (DR) can be defined as the changes in electric usage by end-use customers from their normal consumption patterns in response to the changes in the price of electricity over time. Further, DR can be also defined as the incentive payments designed to induce lower electricity use at the times of high wholesale market prices or when system reliability is jeopardized. This paper presents a novel approach for incorporating stochastic WIND POWER GENERATION and DR with Security-Constrained Unit Commitment (SCUC) for improving the security and economic operation in POWER systems. DR is one of the methods of managing the economic filed in unit commitment. Demand includes the fixed and responsive loads, and the volatile nature of WIND POWER is modeled. Responsive loads can be curtailed or shifted to another off peak hours. The combination of WIND POWER GENERATION and DR to SCUC problem makes a large scale optimization problem which needs a heavy mathematical computation and time consuming process. So, benders decomposition technique is applied to reduce the volume of the computation and problem complexity. To reach a fast approach, a proposed statistical and probabilistic method for omitting infeasible terms is used. Numerical simulation and final results on a modified IEEE 6-and 118-bus systems show the performance and effectiveness of the proposed approach.

Iranian offshore oil and gas platforms are mostly located in the Persian Gulf. Technical and environmental challenges resulted from an off-design running condition of processes on a platform are important issues. The weakness of strategies to stop or decrease the amount of greenhouse gas emission production rate in the Persian Gulf; which is intensively increasing, is another matter of concern. modern methods of energy GENERATION from available renewable potentials near offshore platforms are suggested. Integration of renewable energy converters with offshore oil and gas platforms can solve both problems with machinery and environment to an acceptable extent. In this study, the economics of the Soroush offshore complex is subjected to two scenarios. The first scenario defines the present condition in which the total POWER demand of the complex is supplied by burning the associated extracted natural gas on board the platform in its thermal POWER plant and the second scenario considers a WIND farm located near Bardekhun in Bushehr province to be connected to the complex POWER network and shares its renewable source generated POWER with the platform. The economics of both scenarios are compared in terms of total annual POWER cost. The second scenario shows more beneficial, although there are some conservative assumptions included due to a shortage of data and limitations.