Optimal residential load scheduling under dynamic pricing and demand-side management

Balancing electricity consumption and generation in the residential market is essential for power grids. The imbalance of power scheduling between energy supply and demand would definitely increase costs to both the energy provider and customer. This paper proposes a control function to normalize the peak cost and customer discomfort. In this work, we modify an optimization power scheduling scheme by using the inclined-block rate (IBR) and real-time price (RTP) technique to achieve a desired trade-off between electricity payment and consumer discomfort level. For discomfort, an average time delay between peak and off-peak is proposed to minimize waiting time. The simulation results present our model more practical and realistic with respect to the consumption constrained at peak hours.

Designing and Simulating Transformer Experiments under Dynamic Experiments

Enormous power transformers are the main gear for the power lattice. Their dependability not just influences the accessibility of power in the inventory region, yet in addition influences the monetary working of an energy provider. The primary goal of this work of the improvement of the transformer testing simulating model on the MATLAB/SIMULINK climate.The testing which depends on generator and grid of the transformer, as well as the related outcomes in SIMULINK, will be part of the conceptual stage. In addition, the technique will look into the effects of transformer validation in the method relying on grid on devices which are connected to the grids. According to the findings, neither source has an impact on the parameter calculation of Open Circuit and Short Circuit assessments. Realistic situations, on the other hand, would necessitate testing which relies on grid, which would enable a broader variety of transformers of different ratings to be evaluated with increased current capacity. The effect of a mistake on the grid can be quickly assessed by looking at the destination of the mistake, the period of the mistake, and any dips that may have took place.

Data-Driven Consumption Load Monitoring and Adjustment Strategy in Smart Grid

The enhancement of the intelligent construction of the power grid and widespread popularity of smart meters enable large amounts of electrical energy consumption data to be collected and analyzed. Based on the data, the energy provider gives a guiding price in the future periods to users. It encourages users to be more economical and smarter in the process of using electricity. By applying the social welfare model to equate demand and supply in every time interval, we gain the optimal prices and generation capacity. Nevertheless, the truth is that there is a great gap between the consumers’ booked electrical energy consumption and the optimal generation capacity, causing the power system overload and even outage. This article puts forward a novel automatic process control strategy in order to monitor the gap between the consumers’ booked electrical energy consumption and optimal generation capacity by using statistical method to predict the future one. When the predicted value exceeds the boundary, the energy provider adopts the changeable electricity price to stimulate consumers to adjust their electrical energy demands so that it can have smoothly actual electrical energy consumption. Our adjustment method is data-driven exponential function-based adjustment. Case study results show that the strategy can obtain small adjustment times, stable actual consumption load, and controllable prediction errors. Different from the linear monitoring and adjustment strategy, our approach obtains almost the same adjustment frequency, less standard deviation of residuals, and higher total social welfare and energy provider profit.

Long Term Household Electricity Demand Forecasting Based on RNN-GBRT Model and a Novel Energy Theft Detection Method

The long-term electricity demand forecast of the consumer utilization is essential for the energy provider to analyze the future demand and for the accurate management of demand response. Forecasting the consumer electricity demand with efficient and accurate strategies will help the energy provider to optimally plan generation points, such as solar and wind, and produce energy accordingly to reduce the rate of depletion. Various demand forecasting models have been developed and implemented in the literature. However, an efficient and accurate forecasting model is required to study the daily consumption of the consumers from their historical data and forecast the necessary energy demand from the consumer’s side. The proposed recurrent neural network gradient boosting regression tree (RNN-GBRT) forecasting technique allows one to reduce the demand for electricity by studying the daily usage pattern of consumers, which would significantly help to cope with the accurate evaluation. The efficiency of the proposed forecasting model is compared with various conventional models. In addition, by the utilization of power consumption data, power theft detection in the distribution line is monitored to avoid financial losses by the utility provider. This paper also deals with the consumer’s energy analysis, useful in tracking the data consistency to detect any kind of abnormal and sudden change in the meter reading, thereby distinguishing the tampering of meters and power theft. Indeed, power theft is an important issue to be addressed particularly in developing and economically lagging countries, such as India. The results obtained by the proposed methodology have been analyzed and discussed to validate their efficacy.

What Traits Should Be Measured for Biomass in Kenaf?

Kenaf (Hibiscus cannabinus L.) is widely used as an important industrial crop. It has the potential to act as a sustainable energy provider in the future, and contains beneficial compounds for medical and therapeutic use. However, there are no clear breeding strategies to increase its biomass or leaf volume. Thus, to attain an increase in these parameters, we examined potential key traits such as stem diameter, plant height, and number of nodes to determine the relationship among them. We hypothesized that it would be easier to reduce the amount of time and labor required for breeding if correlations among these parameters are identified. In this study, we found a strong positive correlation between height and number of nodes (Spearman’s Rho = 0.67, p < 0.001) and number of nodes and stem diameter (Spearman’s Rho = 0.65, p < 0.001), but a relatively low correlation (Spearman’s Rho = 0.34, p < 0.01) between height and stem diameter in the later stages of kenaf growth. We suggest that an efficient breeding strategy could be devised according to the breeding purpose, considering the correlations between various individual traits of kenaf.

Kajian Dampak Ketidaknormalan Meter Elektronik Pada Sistem Automatic Meter Reading Pada Pelanggan Tegangan Rendah

PT. PLN (Persero) as an lsitrik energy provider has the task of checking and measuring the use of electricity used by customers. In this case of course requires technology to be able to read how much electrical energy is used, one of the technologies used is Automatic Meter Reading (AMR). The use of Automatic Meter Reading (AMR) system includes monitoring, recording the stand meter then the data can be displayed in the form of a report with data software used management. Electronic meters using AMR systems can be used as a detection tool against irregularities from troubled customers. The readings obtained from AMR are known to the customer's usage, moments before the maintenance error and after. So that it can accurately detect customers who occur maintenance errors and customers and PLN both know the amount of uncollectible kWh, so far the nursing has been impaired by maintenance errors from the beginning of the tide. Based on existing data AMR should not be worth kWh value, but with the error of maintenance in phase S kWh measurable import that will be calculated to obtain a follow-up bill. The result obtained is true there is an inverted phase, it is shown in the fasor diagram where the angle of phase S which was originally 168.30 to 14.40. So that in the stand meter becomes minus the impact due to the mistake of maintenance obtained follow-up bill is 41538.8 kWh equivalent to Rp. 60.949.050,- after calculation. It shows the impact that occurs due to the mismanagement of the follow-up bill that must be borne

CHANGING FOOD HABIT - A RE-EVALUATION

The supporting pillar of our body includes food, sleep & Bramacharya (Stay in conduct). A proper, optimum and skilful use of these triad maintains the integrity, physical, immunological strength, complexion, growth, nourish- ment, till full length of life. Among them food acts as the foundation or rather energy provider for the other two components. Most health problems develop due to the wrong eating habits and cooking methods. When we look back, to 1970’s Kerala state had already achieved the criteria similar to the health status which was to be achieved in 2000 as per the WHO criteria. But unfortunately, the condition got altered and the state got into the list of top ten among the lifestyle disorders. Foods are altered, treated, processed, coloured, sulphurated, embalmed, adulterated, preserved, pickled, cooked sterilised and pasteurized leading to deprivation of nutritional values, which is the curse of this age. The modern society got merged into the regimens of tea, coffee, cold- drinks, instant food, bottled and canned foods, alcohol consumption, smoking, drug addiction and so on. The commercial advertisement seems to bind a ready sale to the credulous miss informed public about the nutrition supplements. There is a high demand among the public for imported vegetables, fruits etc which actually do not suit the climate of India. This article will throw the light in the necessity of rethinking the suitability according to seasons, places, climates, occupation, way of life etc, which is the matter of the hour. This in turn will ponder over the problem in a verycritical manner and analyse various merits and demerits to rearrange them for the upliftment of good health and living. Keywords: food, Nidra (Sleep)

Contribution of cassava and cassava-based products to food and nutrition security in Migori County, Kenya

The promotion of cassava as a staple and food security crop is widespread in Africa,Kenya included. Overreliance on cassava as a sole energy provider could lead to malnutrition. Consumption of high hydro-cyanide levels from cassava products could lead to health complications for consumers.This study sought to establish the contribution of cassava consumption to nutrition in Migori County.A cross-sectional survey was carried out and data collected on households’cassava production and consumption practices. Two hundred and fifty-three households were randomly selected and household farming heads interviewed in West Kanyamkago, Orango Central and Kamgundho locations as areas where cassava is predominantly grown. Seven cassava flour samples of different cassava varieties grown in the area were obtained from farmers.Analyses were done to determine the moisture, cyanide and protein contents on flour and cooked stiff porridge (ugali). Results indicated that 99.1% of the households were farming. They highly depended on sale of farm and livestock produce as income.Ninety four percent of the households consumed cassava,of which 88.4% produced cassava on their farms. The most preferred cassava variety was ‘Rateng’.The main cassava products consumed were ugali(stiff porridge)and porridge. Majority of the households (95%) never consumed cassava leaves and were not aware that cassava leaves could be consumed.The cyanide level on average on dry flours was 53.23mg/kg while on consumed cooked ugali was13.44mg/kg. These levels were above the maximum limit of 10mg/kg recommended by WHO.Low average protein levels of <0.5g/100g were observed in the cooked ugali. This could pose a danger of protein energy malnutrition if no other sources are consumed by the household members.Cassava farming households in the study area require support to promote growth of low cyanide varieties in order to reduce intake.

Distribution and estimates of Australia's identified energy commodity resources

Australia is endowed with abundant, high-quality energy commodity resources, which provide reliable energy for domestic use and underpin our status as a major global energy provider. Australia has the world’s largest economic uranium resources, the third largest coal resources and substantial conventional and unconventional natural gas resources. Since 2015, Australia’s gas production has grown rapidly. This growth has been driven by a series of new liquefied natural gas (LNG) projects on the North West Shelf, together with established coal seam gas projects in Queensland. Results from Geoscience Australia’s 2021 edition of Australia’s energy commodity resources assessment highlight Australia’s endowment with abundant and widely distributed energy commodity resources. Knowledge of Australia’s existing and untapped energy resource potential provides industry and policy makers with a trusted source of data to compare and understand the value of these key energy commodities to domestic and world markets. A key component of Australia’s low emissions future will be the development of a hydrogen industry, with hydrogen being produced either through electrolysis of water using renewable energy resources (‘green’ hydrogen), or manufactured from natural gas or coal gasification, with carbon capture and storage of the co-produced carbon dioxide (‘blue’ hydrogen). Australia’s endowment with abundant natural gas resources will be a key enabler for our transition to a low emissions future through providing economically competitive feedstock for ‘blue’ hydrogen.