International Journal of Smart Electrical Engineering
Volume:8 Issue: 4, Autumn 2019

Microgrids (MGs) contain a diverse mix of energy resources to provide safe and secure power to the consumers. Batteries are utilized in MGs for further energy security assurance as well as cost minimization. In this paper, an efficient approach is introduced for simultaneous energy management and optimal battery sizing to accomplish economic MG operation. Also, demand response programs are employed to further reduce MG operation costs (OCs) and strike a balance between supply and demand. The objectives sought in this context are the optimal values for DG generation levels, level of consumer participation and the respective incentive payments, battery charge and discharge levels and the amount of power exchange with upstream network within a 24-hour scheduling cycle so as to minimize OCs and maximize MG operator’s (MGO) profit as a result of demand response. In order to address the hybrid energy management system (EMS) and battery sizing problem, the proposed model is solved using whale optimization algorithm (WOA) in MATLAB software for a grid-connected MG. The results indicate that battery charge and discharge is significantly lowered through optimal battery sizing incorporated into the proposed approach.

in computational intelligence area, it is suitable to fulfill the analysis in order to interpret the concept and sources of uncertainty and the conditions of its incidence, and hence pursuit for reliable techniques of dealing with it. Dealing with uncertainties in this case is a challenging and multidisciplinary activity. So, there is a need for a capable tool for modeling, control, and analytics to test and evaluate uncertainties for different configurations of the same IoT system. This article emphasis on the analysis of the uncertainty in one of the most important technology trends, the IOT on case study of green environment, such as smart homes. In this research a Mamdani Fuzzy Inference System has been proposed with a Gaussian MFs to handle the uncertainty in intelligent environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSANs. It utilizes a fuzzy logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the actuator. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved.

Distribution of distributed generation resources in distribution systems has several advantages, including reducing losses, improving voltage profiles, reducing pollution, and increasing system reliability. However, one of the most important points regarding the placement of these resources in distribution networks is economic issues and the return on investment and the increase in profits from the placement of these resources. On the other hand, due to the privatization of power systems, other distribution networks will not necessarily own the distributed generation resources. Therefore, despite choosing the location of scattered production resources by the owners of scattered production resources and pricing their production power, the selection of purchasing power from each of the scattered production units or the national electricity system is done by the distribution network operator. It will be for supply. Thus, owners of scattered production resources must choose the location and price of the production capacity of their resources in such a way that their profit is maximized and at the same time the amount of payment paid by the network operator is minimized. Therefore, in this paper, the issue of location and optimal pricing of distributed products is considered to increase the profit of the owner of scattered production resources provided that the distribution company pays the minimum payment cost and the method used to solve this problem is the ant-optimization algorithm. It is inspired by the ant's milk hunting mechanism and is a powerful optimization algorithm.

Since the emergence of power market, the target of power generating utilities has mainly switched from cost minimization to revenue maximization. They dispatch their power energy generation units in the uncertain environment of power market. As a result, multi-stage stochastic programming has been applied widely by many power generating agents as a suitable tool for dealing with self-scheduling strategies under uncertainty. However, dependence structure between stochastic variables has been almost ignored in the literature. Copula function is a new concept in the probability and statistics field which has the capability to represent the dependence structure among stochastic variables. However, Copula function has recently taken into account in power system studies by some articles. In this article, self-scheduling strategy of a generation utility owning thermal units is investigated while the dependence structure among stochastic load and market price variables is taking into account. We assume that the generation utility is a price-taker agent in a power market, and it also has to meet the load of a specific region as a retailer. The results indicates that as the stochastic dependence structure among load and price variables is considered in modeling load and price scenarios, the output of unit commitment problem changes so that the revenue of generation utility increases.

Gas turbines play an important role in supplying power for the country especially in peak electricity load. The main disadvantages are the turbines, they produce large changes are a result of climate change. However, in times of peak electricity grid and at the same time warm months, can produce gas turbines under the effect of ambient temperature, the amount of reduced considerably. The methods adopted for the turbine compressor inlet air cooling and recovery of their power optimization is necessary. In this paper, different methods of cooling the inlet air to gas turbines for Fars power plants weather conditions and eventually introduced various schemes to install combined cycle gas turbine inlet air cooling system of the plant, good design, Media evaporative air cooler system have been selected according to technical and economic evaluation. Media evaporative air cooler by an external contractor blueprint designed, constructed and installed in the plant. Performance tests are conducted at the site, 11 MW equivalent to 14.5 percent for gas units and 1.2 MW (6.2%) for steam combined cycle unit to the circuit after the Media cooling system in the summer show.

In order to reduce the volume and size of distribution power transformer, precise and extended controlling of transformer output, the conventional transformers are replaced by intelligent universal transformers (IUTs). In this paper, an IUT, typical of Iran national grid, with the voltage ratio of 20kV:380 V is designed and simulated. Regarding the IUT implementation, a cascaded H-bridge inverter (CHB), and a double active bridge (DAB) inverter, along with a three-phase inverter is used. Finally, the proposed IUT is simulated in various conditions.