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 investigates joint user association, sub-channel assignment, and Power Allocation in the uplink of multi-user orthogonal frequency division multiple access (OFDMA) of a heterogeneous network (HetNet) where users are subject to maximum transmission Power constraints. It is shown that the underlying problem is a highly non-convex mixed integer non-linear problem. To tackle the problem, the integer variables are relaxed and a penalty function is added to the objective function to make sure that the relaxed variables take binary values. Finally, the objective function is rewritten as the difference of two convex (D. C. ) functions and the resulting problem is addressed through using the successive convex approximation method. It is worth mentioning that, to the best of the author’ s knowledge, the problem of joint user association, sub-channel Allocation, and Power control in the uplink of a heterogeneous network has not been addressed in the literature till now. Simulation results demonstrate the superiority of the proposed method over existing works in terms of achieving higher throughput despite exhibiting a higher complexity.

The role of waveform design is central to effective radar resource management for state-of-the art radar systems. The waveform shape employed by any radar system has always been a key factor in determining the performance and application. The design of radar waveform to minimize mean square error (MMSE) in estimating the target impulse response is based on Power Allocation using waterfilling. This paper shows the effect of various Power control strategies in the MMSE performance of the waveform design. We find that the truncated Power control strategy exhibits a good MMSE performance. The performance improvement results from the fact that with the truncated Power control no Power is wasted in poor quality modes.

This paper presents an investigation on the performance of the Non-Orthogonal Multiple Access (NOMA) in the Power domain scheme. A Power Allocation (PA) method is proposed from NOMA throughput expression analysis. This method aims to provide fair opportunities for users to improve their performance. Thus, NOMA users can achieve rates higher than, or equal to, the rates obtained with the conventional Orthogonal Multiple Access (OMA) in the frequency domain schemes. The proposed method is evaluated and compared with others PA techniques by computer system level simulations. The results obtained indicate that the proposed method increases the average cell spectral efficiency and maintains a good fairness level with regard to the resource Allocation among the users within a cell.

In this paper, we adopt supreme-utilities among fuzzy level (decision) vectors to propose a Power Allocation rule, its efficient extension and normalization in the framework of multicriteria fuzzy transferable-utility (TU) games. We also provide several axiomatic results to present the rationality for these rules. Based on different viewpoints, we introduce different formulations and dynamic results for the efficient extension and the normalization by applying the reduced game and the excess function respectively.

In recent years, Power system security has been discussed and experiences of recent wars and conflicts have emphasized it. Power system operator uses crisis management strategies to confront threats against Power system. One of these strategies is response, which means that the operator start to inject reserve Power into Power system while attack is taking place. Since considering some Power units as reserve units is costly, the value of reserve Power must be economically optimized. In this paper, a new method for calculation of system’s Energy not supplied based on Monte Carlo approach is presented. Then reserve Power is optimized based on cost/benefit Analysis to minimize operation cost and energy not supplied cost of system. In critical situation, value of lost load and unavailability of components are increased and consequently the optimized value of reserve Power is increased rather that normal situation. The presented method is tested on IEEE 24-bus test system and results are discussed.

This paper considers the Power-efficient resource Allocation problem in a cloud radio access network (CRAN). The C-RAN architecture consists of a set of base-band units (BBUs) which are connected to a set of radio remote heads (RRHs) equipped with massive multiple input multiple output (MIMO), via fronthaul links with limited capacity. We formulate the Power-efficient optimization problem in C-RANs as a joint resource Allocation problem in order to jointly allocate the RRH and transmit Power to each user, and fronthaul link and BBU assign to active RRHs while satisfying the minimum required rate of each user. To solve this non-convex optimization problem we suggest iterative algorithm with two-step based on the complementary geometric programming (CGP) and the successive convex approximation (SCA). The simulation results indicate that our proposed scheme can significantly reduce the total transmission Power by switching off the under-utilized RRHs.

Due to lack of resources such as transmission Power and bandwidth in satellite systems, resource Allocation problem is a very important challenge. Nowadays, new heterogeneous network includes one or more satellites besides terrestrial infrastructure, so that it is considered that each satellite has multi-beam to increase capacity. This type of structure is suitable for a new generation of communications, which leads to a specific benefit of using the available resource in wireless communication systems. The multi-beam technology is one of the multiple access methods for new satellite systems that are similar to very high throughput satellites systems. Therefore, in this paper, our proposed algorithm is mainly the jointly Power and bandwidth Allocation of satellite systems to each beam and it is simulated considering the limitation of the total transmission Power and bandwidth constraints for any beams. Furthermore, a bandwidth sharing algorithm is provided to dedicate extra bandwidth among beams. Finally, the total capacity of our proposed system model, which is heterogeneous network is obtained based on some parameters such as frequency reuse, modulation rate and total number of users for each beam. This comparison shows that the proposed algorithm allows maintaining the optimal capacity Allocation to use a new satellite network.