Electricity In Residential Buildings Research Articles

Thermoeconomic analysis of a novel configuration of a biomass‐powered organic Rankine cycle for residential application with consideration the effect of battery energy storage

AbstractIn this article, the energy, exergy, and economic analysis of an organic Rankine cycle (ORC) system powered by biogas to provide electricity, heating, and cooling loads for a residential building in Munich city is investigated. Two methods have been proposed to meet the heating and cooling needs of the residential building. In the first method, heating and cooling needs are provided by a heat pump and mechanical refrigeration (System I), and in the second method, these needs are provided by a radiator and absorption refrigeration cycle (System II). In both modes of this system, the effects of battery energy storage (BES) have been analyzed for peak shaving. The working method of this research is that the residential building's electricity, heating, and cooling needs are calculated by Homer and Carrier software, respectively. Engineering equation solver software models the main local power generation system. A new method has been proposed to select the required number of units to meet the needs of the building with and without BES. The results showed that for System I with and without BES, 3 and 1 ORC units with a nominal power of 2 kW can meet all the needs of the building, respectively. In contrast, for System II, the number of 1 unit with 2 kW and 1 unit with 1 kW is needed to meet the energy needs of a residential building with and without BES. It can be concluded that heating and cooling the building with a radiator and absorption chiller cycle is more cost‐effective. The energy and exergy efficiency of ORC is reported as 11.3% and 65.7%, respectively, and the highest exergy destruction rate is related to the heater and boiler. From the economic point of view, the payback period of System II compared with System I is reduced from 18.4 to 5.66 years without using BES. With the use of BES, the payback period is reduced to 5.3 and 5.66 years, respectively. The lowest and highest electricity prices belong to System I with and without BES, which are 3.11 and 0.36 US$/kWh, respectively.

Peak power management of residential building using demand side management strategies

Peak power management is one of the demand-side management methods aiming at regulating energy usage throughout the day. This paper discusses peak load, which relates to a consumer's peak demand during specific hourly hours and how to manage it. Shifting loads from demand hours to non peak hours relieves pressure on utilities to meet demand and supply while also lowering the cost to consumers. The Peak Load Management Model offers a more effective framework for lowering peak loads and moving loads from peak to off-peak hours. A cascaded artificial neural network is utilised to construct a demand side management strategy for managing peak electricity in residential buildings in this paper. The peak load control model's results and discussion are highlighted in the simulation results and performance review.

Optimal storage systems for residential energy systems in British Columbia

In recent years, deployment of low carbon energy systems to supply electricity in residential buildings has increased. These energy systems typically integrate different renewable energy resources with energy storage systems to meet electrical energy demand. This paper applies the ”energy hub” model to various energy systems for residential buildings in British Columbia considering several scenarios. We explore the energy system changes in on-grid, off-grid and 100% renewable scenarios. In on-grid systems, the trade off between grid connection and energy storage is explored; the results shows that even the cheapest energy storage system is not feasible with the current cost of grid electricity. For off-grid systems with a diesel generator, storage technologies are used in some energy systems, however the systems still have carbon emissions. Finally, for 100% renewable off-grid systems, both Li-ion and pumped hydro storage systems are used to handle diurnal and seasonal intermittency.

Modelling the Disaggregated Demand for Electricity in Residential Buildings Using Artificial Neural Networks (Deep Learning Approach)

The paper addresses the issue of modelling the demand for electricity in residential buildings with the use of artificial neural networks (ANNs). Real data for six houses in Switzerland fitted with measurement meters was used in the research. Their original frequency of 1 Hz (one-second readings) was re-sampled to a frequency of 1/600 Hz, which corresponds to a period of ten minutes. Out-of-sample forecasts verified the ability of ANNs to disaggregate electricity usage for specific applications (electricity receivers). Four categories of electricity consumption were distinguished: (i) fridge, (ii) washing machine, (iii) personal computer, and (iv) freezer. Both standard ANNs with multilayer perceptron architecture and newer types of networks based on deep learning were used. The simulations included over 10,000 ANNs with different architecture (number of neurons and structure of their connections), type and number of input variables, formulas of activation functions, training algorithms, and other parameters. The research confirmed the possibility of using ANNs to model the disaggregation of electricity consumption based on low frequency data, and suggested ways to build highly optimised models.

A model for efficient consumption of electricity in residential buildings

This paper reviews various applications of Radio Frequency Identification (RFID) technology and proposes electricity-saving power switch enhancement model to control the operation of electrical appliances in residential buildings using radio frequency identification (RFID) system. Estimation was made on the consumption of electricity in a private apartment in Pretoria, Gauteng Province, South Africa and compared with when the RFID card-reader system is deployed. The percentage energy saving in a year was calculated to be approximately 29 %. The possible energy savings for a period of 30years is estimated and the return on investment (ROI) determined. The authors concluded by making a case for a state policy on RFID energy efficiency technology.

Improvement of inverse change-point modeling of electricity consumption in residential buildings across multiple climate zones

Inverse modeling is a common method to predict electricity consumption in buildings. Residential building electricity consumption patterns can vary significantly due to occupants and their sporadic energy-consuming behaviors, as well as due to variations in HVAC system types and characteristics across climate zones. However most data-driven methods in this area have been developed and evaluated using limited datasets. This points to the need for an understanding of how well data-driven models perform using residential energy consumption data from a range of locations and home types using a diverse dataset. Thus in this research, first, inverse change-point modeling methods are used to develop predictive models of monthly electricity use for 3,643 houses in four U.S. cities in three ASHRAE climate zones (2A, 4A, 5A), to evaluate the model performance. However, approximately 40% of homes did not fit within recommended criteria for change-point model development following a common model development sequence. Therefore, a modified version of the sequence, including a segmented change-point model, is then developed and evaluated. Change-point models with relaxed prerequisite criteria are also used to enable the fitting of models to a larger number of homes’ data. As a result of these modifications, the number of homes with models increased from 60% to 71%, with a goodness-of-fit improvement of 13% (RMSE) and 8% (CV-RMSE) across the datasets evaluated. The results of this work enable improved prediction of energy use across a diversity of buildings and climate zones.

The study of a seasonal solar CCHP system based on evacuated flat-plate collectors and organic Rankine cycle

The demands of cooling, heating and electricity in residential buildings are varied with seasons. This article presented a seasonal solar combined cooling heating and power (CCHP) system based on evacuated flat-plate collectors and organic Rankine cycle. The heat collected by evacuated flat-plate collectors is used to drive the organic Rankine cycle unit in spring, autumn and winter, and drive the double-effect lithium bromide absorption chiller in summer. The organic Rankine cycle condensation heat is used to yield hot water in spring and autumn, whereas supply heating in winter. The system thermodynamic performance was analyzed. The results show that the system thermal efficiency in spring, autumn and winter, ?sys,I, increases as organic Rankine cycle evaporation temperature, T6, and evacuated flat-plate collectors outlet temperature, T2, decrease. The maximum ?sys,I of 67.0% is achieved when T6 = 80?C and T2 =100?C. In summer, the system thermal efficiency, ?sys,II, increases first and then decreases with the increment of T2. The maximum ?sys,II of 69.9% is obtained at T2 =136?C. The system output performance in Beijing and Lanzhou is better than that in Hefei. The average output power, heating capacity, hot water and cooling capacity are 50-72 kWh per day, 989-1514 kWh per day, 49-57 ton per day and 1812-2311 kWh per day, respectively. The system exergy efficiency increases from 17.8-40.8% after integrating the organic Rankine cycle unit.

Interactive energetic, environmental and economic analysis of renewable hybrid energy system

One of the commitments of the European community is to increase the share of energy produced from renewable sources in order to minimize costs and risks, or that the society has to bear to produce electricity, in addition to compliance with European pollutant gas (CO2, SO2, NOx and PM) objectives. An ever-increasing body of research aims to study the actual energy savings of buildings with systems of renewable energy production implemented with storage systems, evaluating the potential energy savings. To date, however, the analysis of the environmental impacts of the total life cycle was not taken into account. Thus, no assessment has been made whether the amount of energy saved (esaved) outweighs the energy needed for production, use and disposal (einvested). This study presents an approach for the analysis and evaluation of the energy flows, environmental impacts and cost of a new modular and integrated system of renewable electricity generation and intelligent electrochemical storage systems, that allows auto-production and self-consumption of electricity in residential buildings (smart grid). The results show that the total impact depends on the configuration chosen, from the consumption profile and the types of users. If the duration of use is short and the savings achieved are small, the expected benefits will not always be achieved, in terms of costs for the user and the environmental impact.

Smart building-integrated photovoltaics (BIPV) for Qatar

The consumption of electricity in residential buildings in Qatar is on the rise. According to Kahramaa (Qatar General Electricity and Water Company), the factors leading to this increased demand include urbanization and growth of population.1 Government institutions in Qatar want solar power to be the country's key energy source and have built up large photovoltaic (PV) systems for this purpose. These large PV power plants contribute to a certain proportion of the country's electrical energy supply. This also ensures reasonable utilization of free and usually unprofitable areas, for example on large utility buildings. Small and middle-sized PV systems integrated into private buildings could fulfill more functions. These PV systems could also produce a significant proportion of electrical energy for places where electricity is consumed and could also provide the citizens of Qatar the opportunity to participate in the renewable energy age. This article presents a comprehensive strategy for the integration of solar energy into the private residential buildings area. The strategy describes the provision of adapted PV systems suitable for Middle East's climatic conditions and Arabic architecture, and provides advice regarding how to deal with the climatic hurdles. The main focus of this compilation paper is to figure out how to overcome the economical handicap of minimal electricity price. With the help of Smart building-integrated photovoltaic (BIPV) systems, owners of private residential houses could participate in the production of renewable energy, thereby improving their social prestige. These Smart BIPV systems possess the ability to visualize the entire energy flow in the connected buildings, making the residents aware of their energy demands, in addition to providing tools to replace conventionally produced energy by self-produced solar energy as far as possible. Furthermore, the integrated house management system can control individual room functions to improve the living comfort of the residents in a way that matches their lifestyle.

Efficiency and Environmental Analysis of a System for Renewable Electricity Generation and Electrochemical Storage of Residential Buildings

This study presents an approach for the evaluation of the energy efficiency and environmental impacts of a new modular and integrated system of renewable electricity generation and intelligent electrochemical storage systems, that allows auto-production and self-consumption of electricity in residential buildings. Homes with installed these renewable energy production systems are compared from an environmental and economic point of view, to the traditional ones, that draw electricity energy directly from the grid. In this context different scenarios are considered together with different configurations of power production and storage capacity, in order to compare different use cases. To this end, the environmental impact along all the life cycle of these systems is examined with the help of the SimaPro software simulation tool and quantitatively assessed.

Minimization of operational cost for an off-grid renewable hybrid system to generate electricity in residential buildings through the SVM and the BCGA methods

Abstract Recently Turkey's electricity demand has shown a considerable increase due to its population and economic growths. It is understandable that this may be very influential on electricity price on market as well as other factors such as an increase in natural gas price, etc. It should be noted that the half of Turkey's electricity generation is supplied from natural gas and 95% of this source is imported from other countries. However, Turkey is rich in wind and solar energy potentials to generate electricity and it is believed that this makes a considerable impact on reducing high electricity unit cost to competitive one. In this regard, these potentials can be utilized for electricity generation in order to meet a significant portion of the power demanded by residential houses through a PV/wind system. The electricity cost of the renewable system can be minimized by optimally scheduling generated and consumed powers. In this paper, optimal power scheduling in such systems is carried out by using the BCGA and the SVM methods. The results indicated that the proposed approach was able to minimize the operation cost in the hybrid system through the optimal power scheduling.