Abstract
This paper presents a new adaptive scheme for doubly fed induction generators (DFIGs) in order to augment their flexibility confronting with unpredicted operational conditions. Due to large fluctuations in the wind velocity, the proposed scheme would handle system unreliable operational conditions. In such system, which has multi-input, multi-output and is also represented as a nonlinear control system, the uncertain parameters would affect the operational conditions. So, in order to have a robust controlling scheme, the mentioned characteristics should be considered in the proposed method. The adaptive control scheme proposed in this paper satisfies the expected constraints and could also be implemented in real-world platforms, especially in large-scale wind farms with DFIG turbines. © 2014 Taylor & Francis.

Abstract
In this paper, the problem of optimal economic scheduling of multi-reservoir cascaded hydrothermal units is investigated in the presence of an individual pumped-storage generating unit in the network. The proposed problem is modeled in a multi-objective framework comprising two objective functions. The goal of the first objective function is to minimize the operation costs and the second one is set to minimize the emissions caused by the thermal units while all the technical constraints are satisfied. Furthermore, the valve loading effect is included in the first objective function as a sinusoidal function. The problem is modeled and solved as a Mixed Integer Non-Linear Programming (MINLP). The augmented É"-constraint technique and lexicographic optimization are employed to solve the problem. Numerical results obtained from implementing the model on a case study are discussed. Also, the decision making procedure has been done using a fuzzy satisfying method to select the most preferred solution among the Pareto solutions derived through solving the multi-objective problem.

Abstract
Smart grid can be expressed as a combination of power network substructures with an extensive telecommunication network which is able to provide a two-way communication and use of advanced sensors in order improve efficiency, system reliability, transport security, and power consumption. Loads in this network are divided into two groups, linear and non-linear. The majority of these loads on the network, such as rectifiers, electric vehicles are non-linear. The non-linear loads can cause odd harmonics in the network and can damage transformers. In this article, management and planning of hybrid vehicles for total harmonic index reduction and also annual cost reduction has been considered.

Abstract
Allocation of flexible AC transmission systems (FACTS) devices is a challenging power system problem. This paper proposes a new particle swarm optimisation (PSO) variant, called enhanced leader PSO (ELPSO), for solving this problem. This algorithm is capable of solving FACTS allocation problem in a way leading to lower amounts of power flow violations, voltage deviations and power losses with respect to other optimisation algorithms. Distributed thyristor controlled series compensators (D-TCSC's) are used. D-TCSC's are installed at all branches except those with regulating transformers. The reactances of D-TCSC's are found in optimisation process. ELPSO features a five-staged successive mutation strategy which mitigates premature convergence problem of conventional PSO. ELPSO and other optimisation algorithms are applied to IEEE 14 bus and 118 bus power systems for N-1 contingencies and also for simultaneous outage of four branches. The results show that it leads to lower amounts of power flow violations, voltage deviations and power losses with respect to conventional PSO (CPSO) and eight other optimisation algorithms including genetic algorithm (GA), gravitational search algorithm (GSA), galaxy based search algorithm (GBSA), invasive weed optimisation (IWO), asexual reproduction optimisation (ARO), threshold acceptance (TA), pattern search and nonlinear programming (NLP).

Abstract
The objective of the retailer in medium-term planning is managing the portfolio of contracts from different sources as well as determining the optimal selling price offered to its customers. When supplying the electricity sold to the costumers, two main challenges are faced by retailers. The first problem occurs during the electricity procurement procedure. In this stage, the retailer must deal with the uncertainty due to the pool price that propels the retailers to move towards agreeing to forward contracts signed at higher average prices. Besides, when the retailer decides on selling the electricity, another problem is to face the uncertainty caused by the demand while taking into consideration the possibility of reducing its clients in the case of high selling price. In this regard, this paper proposes a stochastic multi-objective framework for the retailer with profit maximization and risk minimization as two objective functions. The risk, due to the market price uncertainty, is modeled, employing the expected downside risk. The problem is formulated as mixed-integer programming while the stochastic optimization problem is characterized using the roulette wheel mechanism and lattice Monte Carlo simulation. Furthermore, lexicographic optimization and augmented epsilon-constraint method are used to solve the proposed multi-objective problem, and the best compromise solution is determined employing a fuzzy satisfying method. The presented model has been implemented using a realistic case study to verify the effectiveness of the method used in this paper. © 2015 John Wiley & Sons, Ltd.

Abstract
Developing an inverter with high efficiency and with the ability of starting with inductive, capacitive, and resistive loads along with output voltage stability is a challenging problem. Considering higher reliability and convenient maintenance, this paper focuses on the use of analog circuits. In this regard, this paper uses pulse width modulation techniques, intelligent feedback, and peak as well as effective voltage supply are employed. Results indicated that this designed inverter with a power of 700 W can be started with ohmic loads (100% quality), inductive loads (97% quality), and capacitive loads (83% quality).