Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

Buildings are the main energy consumers across the world,especially in urban communities.Building smartization,or the smartification of housing,therefore,is a major step towards energy grid smartization too.By controlling the energy consumption of lighting,heating,and cooling systems,energy consumption can be optimized.All or some part of the energy consumed in future smart buildings must be supplied by renewable energy sources(RES),which mitigates environmental impacts and reduces peak demand for electrical energy.In this paper,a new optimization algorithm is applied to solve the optimal energy consumption problem by considering the electric vehicles and demand response in smart homes.In this way,large power stations that work with fossil fuels will no longer be developed.The current study modeled and evaluated the performance of a smart house in the presence of electric vehicles(EVs)with bidirectional power exchangeability with the power grid,an energy storage system(ESS),and solar panels.Additionally,the solar RES and ESS for predicting solar-generated power prediction uncertainty have been considered in this work.Different case studies,including the sales of electrical energy resulting from PV panels’generated power to the power grid,time-variable loads such as washing machines,and different demand response(DR)strategies based on energy price variations were taken into account to assess the economic and technical effects of EVs,BESS,and solar panels.The proposed model was simulated in MATLAB.A hybrid particle swarm optimization(PSO)and gravitational search(GS)algorithm were utilized for optimization.Scenario generation and reduction were performed via LHS and backward methods,respectively.Obtained results demonstrate that the proposed model minimizes the energy supply cost by considering the stochastic time of use(STOU)loads,EV,ESS,and PV system.Based on the results,the proposed model markedly reduced the electricity costs of the smart house.

Internet of Things (IoT)

the world is experiencing a strong rush towards modern technology, while specialized companies are living a terrible rush in the information technology towards the so-called Internet of things IoT or Internet of objects, which is the integration of things with the world of Internet, by adding hardware or/and software to be smart and so be able to communicate with each other and participate effectively in all aspects of daily life, so enabling new forms of communication between people and things, and between things themselves, that’s will change the traditional life into a high style of living. But it won’t be easy, because there are still many challenges and issues that need to be addressed and have to be viewed from various aspects to realize their full potential. The main objective of this review paper will provide the reader with a detailed discussion from a technological and social perspective. The various IoT challenges and issues, definition and architecture were discussed. Furthermore, a description of several sensors and actuators and their smart communication. Also, the most important application areas of IoT were presented. This work will help readers and researchers understand the IoT and its potential application in the real world.

Smart partition system - A room level support system for integrating smart technologies into existing buildings

We proposed a support system caLLed the ＂Smart Partition System＂ for infill elements that integrate smart technologies according to the Open Building principles. The design requirements were collected from design practitioners. These design requirements consisted of both architectural and information subsystems. The Smart Partition System was composed of the foLLowing multiple levels of smartness： the foundation/core Level with an embedded design knowledge in the support system and the utility Level with a modular infill that integrate smart technologies. We constructed functional prototypes to demonstrate the feasibility of our proposed support system and some of the possibilities of the smart infill elements. Furthermore, the prototypes were evaluated by design practitioners. We compared our approach with current practices of smart building developments, and we also discussed some future prospects.

A Price-elastic Approach for Optimal Scheduling of Small-scale Storage Devices in Smart Houses with Short-term and Long-term Constraints

Consecutive charging and discharging of storage devices(SDs)might deem beneficial from the perspective of short-term operation.However,it highly impacts the life span of the embedded battery and render restrictions on energy storage capacity.We investigate short-term and long-term constraints of SDs through a three-stage price-elastic approach to the optimal operation of small-scale SDs in smart houses.The first stage deals with data and scenario characterization where the data for determining short-term and long-term operation constraints of SD are acquired.Proper number of scenarios are generated to represent uncertain parameters such as long-term demand forecasting,daily load profile,electricity price,and photovoltaic(PV)generation.The second stage optimizes the long-term operation of SD using the envisioned scenarios subject to the long-term operation constraints and the installment costs of SDs.The outputs of this stage are two indicators referred to as price elasticity and price offset coefficients,which are used as the inputs for the third stage.The third stage is responsible for decision-making on short-term operation of SDs.The outputs of the second stage along with short-term forecasting for daily electricity price,daily load and daily PV generation are acquired.Based on the acquired data,proper price elasticity and price offset are determined for optimal operation.Comprehensive simulations are performed for different demand forecasting and electricity prices.Simulation results confirm the effectiveness of the proposed approach.