The transmission network expansion planning is necessary for supplying the future needs, considering load growth. Furthermore, in restructured environments, transmission lines provide the required infrastructure for creating a competitive environment. In recent years, there has been a signifi cant advancement in Storage technologies. This advancement leads to using Energy Storage systems to postpone the construction or replacement of transmission lines. Therefore, in this paper, the problems of transmission expansion planning and Energy Storage systems deployment are investigated simultaneously. Considering the presence of Storage devices and their effect on network operation cost, in this paper, the operation cost is modeled as an independent objective function along with investment cost. Moreover, the problems of transmission and Storage expansion planning are modeled as a tri-objective optimization problem with the objectives of reducing costs and increasing the social welfare index in the power market. The multiobjective shuffl ed frog leaping evolutionary algorithm is used to solve these problems. The presented model for expansion planning is implemented and analyzed on IEEE 24-bus test system in the presence and absence of Energy Storage systems, and the effect of change in the price of Energy Storage systems is studied. The results of this research show that as the technology advances and the Storage costs decrease, Energy Storage systems can play a pivotal role in reducing expansion planning costs of the power network and improving market-based indices in the restructured environment.

Due to the limited Energy resources and the need to save Energy, use of solar Energy as a strategic approach is extremely important. So in this article by using system to store solar Energy for heating buildings in Laboratory of Islamic Azad university-Semnan Branch. In this approach tried to optimized using of solar Energy. In this system, the Energy requirements of the building using software «Carrier» during the day and then the solar Energy are calculated using mathematical equations. A code written in «MATLAB» for optimum Solar Energy consumption where calculates Storage system level thermal load and thermal load of the auxiliary system (boiler) on the day. Utilizing the code, all needed magnitude of geometry as the collector area requirements according to the heat load are provided.

Net zero Energy buildings and positive Energy buildings are gaining more and more interest. This paper evaluates the impact of the integration of a battery in a positive Energy building used to increase its self-consumption of electricity. Parametric studies are carried out by varying the building envelope characteristics, the power supply system, the climate, the lighting and appliances profiles, the roof tilt angle, the battery size and the electricity tariffs, leading to 3200 cases. The analysis is performed on an annual basis in terms of self-consumption and self-production rate and payback period. It is shown that the battery size leading to the minimum payback period within the input range is comprised between 2.6 and 4.5 kWh. The lowest payback periods, (~7 years), are reached with a well-insulated building envelope, a high lightning and appliance consumption, a low feed-in tariff and a 3.7 kWh battery. Finally, simple correlations (based on the feed-in tariff, the annual electrical consumption and production) to predict the optimal size of battery and the lowest payback period are proposed.

Sunlight is converted into electricity and heat simultaneously with the help of PV thermal panels. It is examined that the efficiency of the PVT panel is higher than the separate PV panels and solar thermal collectors’ efficiency. The electricity conversion-efficiency for a PV system is about 6% to 15% and in moreover cases 85% of the incoming solar Energy is either reflected or absorbed as heat Energy. Now a day’ s Renewable Energy has become a hot topic. The Energy researchers day by day making advanced researches to make this type of system a useable one. Non-renewable sources will be approximately finished within next 100-150 years. So this type of Energy is very important for everyone. Normally researches are made on producing electricity from renewable sources like sun-light, wind Energy, tidal Energy and etc. In this paper there is a compact review of solar photovoltaic thermal system. The performance of the solar cell decreases with the increasing of temperature. Both the electrical efficiency and the power output of PV module depend on the operating temperature. Photovoltaic thermal hybrid solar collectors, also known as hybrid PV/T systems are systems in which sunlight is converted into thermal and electrical Energy both. This paper contains a combination of basic and advanced hybrid PV/T systems that are usable in Asian region.

In the present work, MoS2 decorated graphene nano composite powders were synthesized by laser scribing method. The obtained flexible light-scribed graphene/MoS2 composites are very suitable as microsuper capacitors and thus their performance was evaluated at different concentrations. The effect of laser scribing process to reduce graphene oxide (GO) was investigated. The GO/MoS2 composite was synthesized using a chemical mixing of GO solution withMoS2/Dim ethyl formamide (DMF) solution. The mixtures with various concentrations of MoS2 were then coated on a Light Scribe DVD disk and laser scribed to reduce GO and create aMoS2/laser-scribed graphene (LSG) composite. Four different concentrations of MoS2/LSG composites (pristine rGO, 1: 100, 1: 75 and 1: 50 MoS2/LSG) were utilized as supercapacitor electrode and the electrode with the best performance was selected for flexible micro-supercapacitor applications. The present findings demonstrate that MoS2/LSG microsupercapacitor has high specific capacitance per area. The sample with MoS2/LSG volume ratio of 1: 50 shows the highest specific capacitance (~ 8 Fcm-3 ) and its cyclic stability is favorable over 1000 cycles.

In the recent days, the main challenge for the electrical power system is an economical Storage technology. Energy Storage is essential for the future Smart Grid (SG) to smooth out the fluctuating output of Renewable Energy Resources (RERs). Even though many good Storage technologies are available but either they are not economical or they are not efficient. Several research studies are analyzed the application of Energy Storage with respect to voltage support, peak shaving, frequency stability, renewable firming, transmission upgrade deferral, and a host of other uses. RERs are dependent on the climate conditions for the power output. Therefore, an efficient Storage technology is an important part for the reliability of electric power system. This paper compares different Storage technologies available, i. e. hydrogen Storage, batteries, superconducting magnet Energy Storage, fly wheels, compressed air Energy Storage, pumped hydro Energy Storage, etc. This paper details the necessity of Storage techniques to help the RERs power output in the SG to meet the Energy demands of the future.

An optimal day-ahead operation of a microgrid based on coastal Energy hub is presented in this paper. The proposed CEH included wind turbine, photovoltaic unit, combined cooling, heat and power, and seawater desalination. The purpose of the optimization is minimization of the operational and environmental costs considering several technical limitations. The CEH includes an ice Storage conditioner together with an Energy Storage system, i. e. thermal Energy Storage system. Particularly, the impacts of an innovative rechargeable and emerging ESS that is solar-powered compressed air Energy Storage is scrutinized, on the efficiency and operational and pollution costs of the CEH. It is clear that there is an intrinsic deviation between predicted and actual uncertainty variables in MG. This paper presents a bi-level stochastic optimal operation model based on risk averse strategy of information gap decision theory to overcome this information gap and to help Microgrid operator. To reduce the complexity of the proposed model, Karush-Kuhn-Tucker method is used for converting the bi-level problem into a single level. The Augmented Epsilon Constraint method is used to deals with multi objective optimization problem to harvest the maximum horizon of the uncertainties of the parameters. The proposed model implemented the Time of Use program as a price-based demand response program. Finally, the efficacy of the SPCAES for minimizing the operational cost and pollutions in the day-ahead operation is depicted by implementation of the presented model on the typical CEH.

In a smart home, all its internal components interact with each other through an integrated system and environmentally reasonable logic. In this house, Energy management (EMS) can play a role in reducing Energy costs. Therefore, in this paper, given the increasing importance of this discussion, the operation of smart home with the presence of electric vehicles with the capability of exchanging power with the network, the Energy Storage system and solar panels have been modeled and evaluated in the framework of mixed integer linear programming. In this paper Various studies including the sale of electrical Energy produced by solar panels to power grid, Loads with time-consuming movement such as washing machines as well as various demand response strategies based on Energy price have been considered to evaluate the economic and technical effects of electric vehicles, Energy Storage batteries And solar panels. In assessing the performance of solar panels, uncertainty regarding the prediction of solar power is considered, and the proposed model has been analyzed by considering the conditional value at risk (CVAR) criteria. The proposed model is implemented in the GAMS software and the results indicate that the use of additional power systems will significantly reduce the cost of smart home power.