Annual Energy Cost Research Articles

Syria’s wind resources: Outlook for the Future

15 locations with wind speeds of more than 5 m/s were explored among 24 locations across Syria. Wind data from these locations was analyzed using the Weibull distribution, along with 15 different turbines. Three performance indicators were calculated and compared between each other: annual energy production, power factor (θ) and energy cost (z). The economic potential was calculated and the economic efficiency of wind turbines was studied on the basis of optimization of wind farm parameters that helped to find an option that provides the lowest price for electricity production on wind turbines. The study reveals that E70 71m 2300kw is the optimal turbine in all areas (from the places under consideration), both in terms of the highest efficiency and the lowest energy cost. The results show that the area of Sokhna has the largest economic potential because of the big space suitable for the establishment of wind turbines. Using the proposed wind farm scenario until 2030 is able to cover the deficit by 7.22%.

Optimal Sizing and Design of Isolated Micro-Grid systems

Micro-grid and standalone schemes are emerging as a viable mixed source of electricity due to interconnected costly central power plants and associated faults as well as brownouts and blackouts in additions to costly fuels. Micro-Grid (MG) is gaining very importance to avoid or decrease these problems. The objective of this paper is to design an optimal sizing and energy management scheme of an isolated MG. The MG is suggested to supply load located in El-shorouk Academy, Egypt between 30.119 latitudes and 31.605 longitudes. The components of the MG are selected and designed for achieving minimum Total Investment Cost (TIC) with CO2 emissions limitations. This is accomplished by a search and optimization MATLAB code used with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques. The use of Diesel Generators (DGs) is minimized by limiting the gaseous CO2 emissions as per targeted allowable amount. A comparison is accomplished for investigating the CO2 emissions constraints effects on the TIC in $/year and annual cost of energy in $/kWh. The obtained results verified and demonstrated that the designed MG configuration scheme is able to feed the energy entailed by the suggested load cost effectively and environmental friendly.

Assessing the energy and indoor-PM2.5-exposure impacts of control strategies for residential energy recovery ventilators

The energy recovery ventilator (ERV) is a type of mechanical equipment that provides ventilation into the building while reducing the energy required to condition the ventilation air. A computer modelling approach was used to assess energy consumption (the energy used to run the air-conditioning and ERV) and indoor PM2.5 exposure concentrations from both indoor and outdoor sources in Hong Kong high-rise residential flats under various ERV control strategies. Three varying inputs, including ventilation mode (energy-exchange, bypass or a hybrid of both), filter efficiency and ventilation rate, were used to develop different ERV control strategies. The estimated energy consumption and indoor PM2.5 exposure concentration were monetised using per-occupant cost functions, in order to allow a direct combination between the two. Results show that the ERV switching between energy-exchange and bypass modes according to outdoor weather conditions saves 43% of the annual energy cost compared with that operating in bypass mode, while the ERV operating in energy-exchange mode saves 28%. Integrating an air filter with a high PM2.5 removal efficiency into the ERV causes a reduction in the annual exposure cost with increased ventilation. By combining energy and exposure costs, this study has been able to determine the most cost-effective ventilation rate of the ERV, which costs an occupant approximately HK$ 2692 over the course of a year. Varying the ventilation rate as a function of outdoor temperatures, outdoor humidity ratios or outdoor enthalpy further reduces the combined cost compared with operating the ERV at the most cost-effective ventilation rate.

3D modeling of supply and exhaust ventilation in the concept of passive building in the software package Autodesk 3ds Max

The main issue of the study is the problem of the possibility and feasibility of 3D modeling, and the use of supply and exhaust systems for heat and moisture recovery in the design of a passive building, using a 2-stage scheme of air heating in climatic and geographical conditions for the city of Kaliningrad. After all, using this mechanical ventilation and air heating scheme in a passive building, it is possible to reduce annual energy costs by 3-4 times. The higher capital costs of a passive building are offset by lower operating costs due to a significant reduction in energy consumption.

Practical low-cost method to sustain mine compressed air savings

Efforts to ensure a sustained growth path for the mining industry are vital for its survival, as well as the communities that depend on it. Mining companies in South Africa thus need to focus on reducing their operational costs in order to remain competitive. Mines can reduce their operational costs by optimising compressed air production and curbing oversupply. However, complex and expensive solutions are impractical, and the need for a simple, lowcost solution to match compressed air supply with the required demand is evident. A simplistic and inexpensive step-by-step methodology was subsequently developed. The methodology focused on identifying cost-saving initiatives to reduce compressed air network inefficiencies. These inefficiencies were evaluated, and a suitable solution strategy was developed. The methodology was implemented on the compressed air network of Mine A and proved to have no negative effects on the production of the mine, while annual energy cost savings of R1,1-million were shown to be viable.

Quantifying potential savings from sustainable energy projects at a large public university: An energy efficiency assessment for texas state university

At Texas State University (TSU) in the United States, “sustainability” is pursued within the context of (1) a non-binding declaration in the University’s plan, and (2) a State legislative directive to reduce energy consumption. Grounded in these direct links between sustainability and energy use, this paper evaluates energy efficiency at TSU. The aim of the applied case study is to inventory current (business as usual) energy consumption levels at TSU, and to understand how those levels might change under a regime of more sustainable energy technology. The paper performs financial analysis to show that selected sustainable energy projects can not only reduce energy use at TSU, and thereby strengthen the University’s commitment to sustainability. Sustainable energy projects will also save the University money in the long run. The case study draws on a sample of the 13 on-campus buildings with the highest current levels of energy consumption. The approach of the paper is to determine the level of attractiveness of investing in new technology by calculating the Net Present Value (NPV) in terms of financial savings every year (simple payback) or a more extended period (cash flow model). The environmental impact is calculated in terms of CO2 emission based on Scope 2 methodology. We find that TSU could achieve annual electricity savings of 15,391,436 kWh (17% of its annual energy costs) from implementing selected projects and save more than $1,000,000 in annual costs. Overall, TSU could reduce CO2 emissions by 12,561.81 metric tons. The shortest payback period belongs to the pump replacement, and the most significant annual kWh saving is represented by the replacement of the lighting system. Solar panel installation has the highest upfront investment reaching more than $7 million, while its implementation will bring the highest environmental impact by avoiding 2926.81 metric tonnes of CO2 every year. However, the recommended minimum cost of energy at 14–16 (¢/kWh) for solar panel implementation cannot compete with the 8 cents per kWh paid for the electricity at San Marcos. The findings have immediate practical relevance for campus planning at TSU, and the methods are replicable and extendable for use by practitioners and researchers at other Universities or large institutions.

Optimization and control of energy saving side-stream extractive distillation with heat integration for separating ethyl acetate-ethanol azeotrope

Currently, limited efforts have focused on the multi-objective optimization and effective control of the side-stream extractive distillation processes (EDS). Herein, the EDS and a heat-integration scheme (EDSH) are proposed for separating the minimum-boiling azeotropic mixture ethyl acetate (EtAC)-ethanol (EtOH). Firstly, the conceptual design by residue curve maps is demonstrated for the EDS. Following which, the genetic algorithm (GA) optimization is carried out to minimize the total capital investment cost (CAP) and the annual energy cost (ENR). Optimal scheme under the product purity constraints is then obtained from the Pareto front. And the EDSH scheme is shown with less TAC and CO2 emission. Therefore, an improved control structure CS3 combining the composition-(RR1/SIDE) cascade and feedforward strategy is developed to achieve decent dynamic responses for the EDSH. The anti-disturbance capability of different control structures in terms of the transient deviation and offsets are compared with the assistance of the integral absolute error.

Power‐saving policies for annual energy cost savings in green computing

SummaryThe concept of green computing is a step toward advanced information technology‐related data computations. There is an urgent need to develop sustainable mobile telecommunication networks subscribed by Telecommunication Regulatory Authority of India (TRAI). This paper aims at deploying major recommendations and directions in computing systems directed by regulating authorities. Green computing–based power‐saving policies include virtualization technique, power‐saving method, and recycling technique‐type solution components that we tried to embed in existing systems. The energy‐efficient green computing reserves the reliability and power of information‐driven technology. This research paper provides a comprehensive approach toward applying green mechanism by spotting the difference between energy consumption of current academic scenario and after embedding power‐saving policies of green computing. Moreover, an account has been maintained about the amount of energy preservation. The extraordinary energy‐ and cost‐saving features of green computing make environment sustainable and lively for future generations.

Input data reduction for microgrid sizing and energy cost modeling: Representative days and demand charges

Computational time in optimization models scales with the number of time steps. To save time, solver time resolution can be reduced and input data can be down-sampled into representative periods such as one or a few representative days per month. However, such data reduction can come at the expense of solution accuracy. In this work, the impact of reduction of input data is systematically isolated considering an optimization which solves an energy system using representative days. A new data reduction method aggregates annual hourly demand data into representative days which preserve demand peaks in the original profiles. The proposed data reduction approach is tested on a real energy system and real annual hourly demand data where the system is optimized to minimize total annual costs. Compared to the full-resolution optimization of the energy system, the total annual energy cost error is found to be equal or less than 0.22% when peaks in customer demand are preserved. Errors are significantly larger for reduction methods that do not preserve peak demand. Solar photovoltaic data reduction effects are also analyzed. This paper demonstrates a need for data reduction methods which consider demand peaks explicitly.

Influence of emerging technologies deployment in residential built stock on electric energy cost and grid load

High penetration rates of novel building energy technologies has prompted a growing concern about their microeconomic effect and grid influence. Deployment of photovoltaic (PV), solar water heating (SWH) systems and energy storage solutions, in addition to the growth of electric vehicles (EV) fleet, are reshaping the structure of built stock and lead to the changes in its electric energy demand profile. Long-term forecasting of such structural changes is necessary to guide the decision-making process that would satisfy the needs of both, energy consumers and the suppliers. Whereas electric energy price model is one of the key influencing factors of technologies acceptance for households, peak loads and grid feed-in determine the needed capacity of power grids. The objective of this study was to assess both, the aggregated cost of energy and the changes in cumulative load profiles that are excepted by 2050 for one of residential building typologies in Norway. Methodologically, it was achieved with descriptive statistics, stochastic forecasting and detailed energy performance simulation. Annual electric energy cost for consumers were evaluated under six pricing models. The results suggested that time-of-use and variable maximum power extraction models represent the lowest and the highest extremes in energy cost. At the aggregated level, peak load will decrease in range 1% to 13% compared to current level. Peak PV feed-in will reach up to 40% of peak load by 2050.

Impact of window parameters on the building envelope on the thermal comfort, energy consumption and cost and environment

In this paper, the impact of window parameters (shape, design, sizes, position and orientation) on the building thermal comfort (temperature, relative humidity and discomfort period), energy consumption (lighting loads, heating and cooling loads and total energy consumption) and cost, and environment effect (CO2 emissions) is analysed under hot semi-arid climate conditions. This study considers the effective window design parameters; window to wall area ratio (WWR), position on the wall, and orientation. An experimental setup is used to validate the numerical solution of the mathematical model by Design-Builder software. Results show that window at north has the minimum interior temperature, discomfort hours, cooling load, CO2 emissions, total energy consumption and energy cost, and maximum lighting, relative humidity and heating load and contrarily the window at south. Window characteristics haven’t great effect on the relative humidity. Increasing WWR increases the cooling load, interior temperature, energy consumption and cost and decreases lighting and heating loads. Window shape ratio (2-1) and middle position represent the lowest in the energy consumption contrarily ratio (1-3) and down position. Controlling, studied window parameters reduces annual cooling load by about 30%, lighting power, CO2 emissions, annual energy consumption and energy cost by about 39%, 22%, 24% and 21%, respectively.

Performance Assessment and Improvement of Central Receivers Used for Solar Thermal Plants

In this work, the energy status and supply plans of Saudi Arabia are discussed with a focus on concentrated solar power (CSP) technologies. Subsequently, optimal designs for a 20 MWe solar power plant external receiver, combined with a 15 h thermal energy storage unit, operating under the weather conditions of Neom City, located in northeast Saudi Arabia, is proposed. The effects of receiver tube diameters, tube thicknesses, tube thermal conductivity and receiver’s performance are studied in detail and compared to those used in a well know operational CSP plant. Results show that a smaller tube diameter and thickness give higher receiver thermal efficiency but increase the annual cost of pumping energy. However, that increment in cost is negligible compared to the total energy gained. Furthermore, the aspect ratio is investigated and it was found that a higher aspect ratio gives a higher thermal efficiency. The thermal efficiency of the optimised receiver was increased by about 1% more than the reference plant. In addition, the new design decreases the total estimated cost of tube material by approximately 43%. It is anticipated that the reported results could pave the path for more efficient solar thermal power plants.

Impact of Low-E Window Films on Energy Consumption and CO2 Emissions of an Existing UK Hotel Building

In order to fulfil the UK government’s ambitious goal of 80% reductions in greenhouse gas emissions by 2050 compared to the levels of 1990s, unprecedented measures for improving the energy efficiency of buildings are needed. This study investigates the impact of a specific type of Low-emissivity (Low-E) window film—Thinsulate Climate Control 75—on the holistic energy consumption of an existing United Kingdom (UK) hotel building. Building modelling and energy simulation software EDSL TAS is used to conduct the study. The result of the simulations demonstrates that by applying Thinsulate films, savings in heating, cooling, and total energy consumptions are achieved by 3%, 20%, and 2.7%, respectively. Also 4.1% and 5.1% savings are achieved in annual CO2 emissions and total energy costs, respectively, while the initial costs may be an issue. This study found that application of Low-E window films results in slightly better energy performance of the hotel regarding its heating-dominant climate. The study also recommends using average annual actual energy consumption data for a time range, instead of picking a single year’s data for validating purposes.

Determining the Optimized Hub Height of Wind Turbine Using the Wind Resource Map of South Korea

Although the size of the wind turbine has become larger to improve the economic feasibility of wind power generation, whether increases in rotor diameter and hub height always lead to the optimization of energy cost remains to be seen. This paper proposes an algorithm that calculates the optimized hub height to minimize the cost of energy (COE) using the regional wind profile database. The optimized hub height was determined by identifying the minimum COE after calculating the annual energy production (AEP) and cost increase, according to hub height increase, by using the wind profiles of the wind resource map in South Korea and drawing the COE curve. The optimized hub altitude was calculated as 75~80 m in the inland plain but as 60~70 m in onshore or mountain sites, where the wind profile at the lower layer from the hub height showed relatively strong wind speed than that in inland plain. The AEP loss due to the decrease in hub height was compensated for by increasing the rotor diameter, in which case COE also decreased in the entire region of South Korea. The proposed algorithm of identifying the optimized hub height is expected to serve as a good guideline when determining the hub height according to different geographic regions.

Optimal investigation of daylighting and energy efficiency in industrial building using energy-efficient velux daylighting simulation

ABSTRACTDaylighting is one of the sustainable methods of controlling the flow of natural light into the interior surfaces of the building. Over past years of research daylighting are analyzed through simulation tools due to consistent and precise predictions. The aim of the research is to evaluate the daylight availability in an industrial building under a fixed level of orientation and design. The research initiates by field measurements on the building by an illuminance meter. For the comparative effectiveness, a simulation method is incorporated in the research for a comparative and optimized validation of the daylighting factor. Velux Daylight Visualizer is utilized in this research to simulate the daylighting by modelling the building surface 3 dimensionally with optimal window and glazing material and rendered it to actual interior surface to measure the daylighting at hourly working time zones. Sequentially, the energy utilization of the building is also measured using Velux EIC Visualizer, where the temperature comfort and the total energy utilized for lighting and ventilation is also measured. Hence by improving the design of building to efficient daylighting and ventilation, the annual energy cost investing in artificial lighting and ventilation for industrial operation in a certain period can be restricted respectively.

Energy Savings in HVAC System Using Green Building Practice and Its Environmental Benefits With an Example From Greater Noida, India

An attempt to save energy in an HVAC system using green building practices has been made in this paper. The two blocks of the building of Priyadarshini College of Computer Sciences and Engineering located in Greater Noida, Uttar Pradesh, India have been selected one as non-green (Block A) and other as green (Block B). Primary weather data, with temperature & relative humidity as variables, were measured daily in at least fifteen locations on each floor, of two hour’s interval (7.00am to 6.00 pm) during April to July 2017. The temperature difference of lawn area and each block has been calculated to determine the amount of energy that will be consumed by the air-conditioning (AC) system to maintain the normal atmospheric conditions in each block. Finally, a comparative analysis to quantify hourly, monthly and annual energy consumption, CO2 emission and cost and energy savings have been calculated. The study shows that a partial green block of the building can save 3,07,332 kWh of energy, 1,536,840 rupees and reduces 4,94,820 kgCO2/kWh of CO2 emission annually. Thus green buildings have a high potential for energy and money savings, reduction of CO2 emission, increasing efficiency and lifetime of ACs, and ultimately to save nature.

Real-time energy visualization system for light commercial businesses

Several real-time Energy Visualization (EV) systems have emerged in the market in recent years with specific applications for large industrial and commercial facilities and residential buildings. However, light commercial businesses have been neglected with only a few attempts for EV solutions. In this study a framework for an economical, flexible, and plug and play EV system for the light commercial businesses is presented. It was hypothesized that the proposed framework will provide flexible yet cost effective energy efficiency solutions. Our specific contributions are (1) critical evaluation of existing EV systems, (2) development of framework with respect to operational, technical and budgetary challenges that are specific to light commercial businesses, (3) a computerized program to guide business owners through a step-by-step process involved in the development and installation of the EV system. To test the hypothesis, a field study was conducted by performing energy audits at 15 light commercial businesses. On average, the cost of the EV system was found to be 5% of the annual energy cost. Overall, the findings from our field study conclude that the proposed EV system is economical and flexible enough to address “varied and unique” energy efficiency requirements of light commercial businesses.

Strategic control and cost optimization of thermal energy storage in buildings using EnergyPlus

An operational strategy to optimize building operating energy costs for suppliers and consumers is an important challenge for electrical power utilities. There are various supply-side measures that utilities have to take to ensure continuous energy supply for building heating and air-conditioning. During peak energy demand, utilities are often forced to use more expensive and less efficient generation, thereby increasing the cost of energy. However, some demand-side management practices behind the consumer meter can help in meeting this challenge. One such measure is the use of thermal storage for heating, ventilation, and air-conditioning applications in commercial buildings. There is a gap of adequate knowledge of an optimal control strategy of cold storage operation in buildings adapting to applicable time of day tariffs to minimize annual energy use and annual energy cost of operation. There is also a need to use commercially available tools to avoid the use of complex mathematical models. This study demonstrates strategic controls with six operating modes for using thermal energy storage to shift peak electricity demand, using the time of day tariffs as a decision variable, and reducing operating costs, while also minimizing the size of the system. EnergyPlus was used to model a standard reference large office building for three thermal energy storage system cases: mixed chilled water storage, stratified chilled water storage, and ice storage. An annual average shifting of 25–78% of peak electricity was achieved from the simulation results. The strategy was able to achieve an annual 10–17% cost reduction for consumers using the time of use rates available from a local utility.

Simulation and optimisation study of the integration of distributed generation and electric vehicles in smart residential district

This paper presents an optimisation methodology for simulating the integration of distributed generation and electric vehicles (EVs) in a residential district. A model of a smart residential district is proposed. Different charging scenarios (CS) for private cars are considered for simulating different power demand distributions during the day. Four different case studies are investigated, namely the Base Case, in which no EVs are present in the district and three study cases with different CSs. A global optimisation method based on a genetic algorithm approach was applied on the model to find the total power from PV panels installed and co-generative micro gas turbines while minimising the annual energy cost in the district for the four different scenarios. In conclusion, the results showed that the use of EVs in the district introduces considerable savings with respect to the Base Case. Moreover, the impact of the chosen CS is nearly insignificant under a purely economic perspective even if it is relevant for grid management. Additionally, the optimum amounts of installed power vary in a limited range if the distance travelled by EVs, users’ departure and arrival time change broadly.

Optimal configuration and energy management scheme of an isolated micro-grid using Cuckoo search optimization algorithm

This paper proposes an optimization scheme for optimal configuration and energy management of the micro-grid (MG), using the Cuckoo search optimization algorithm (CSOA). The selected MG supplies a load profile located between 30.119 latitude and 31.605 longitude. The energy produced by the MG generation sources, according to meteorological data of the proposed location, is calculated using MATLAB. The objective/fitness function is modeled and designed for minimizing the total investment cost (TIC) including capital, investment, operation and maintenance costs. A novel weighted goal attainment function (WGAF) has been proposed to reduce CO2 emissions and their associated costs. Moreover, WGAF also applies higher taxes on the amount of emissions that exceed governmental approved limits. To investigate the effects of WGAF on the TIC ($/year), annual cost of energy ($/kWh), and CO2 emissions, various weighted coefficients are analyzed. The simulation results have shown that the designed optimization scheme can robustly and efficiently produce the optimal MG configuration that is both eco-friendly and generates economic benefits.