Quantifying the correlations between the total household electrical demand of residential dwellings and their appliances-spaces demand: A clustering multi-method approach

Optimization and performance comparison of combined cooling, heating and power/ground source heat pump/photovoltaic/solar thermal system under different load ratio for two operation strategies

In April 2014, I attended the ASME Small Modular Reactor (SMR) Symposium in Washington, DC. It was an excellent meeting with a very positive vision of the future of SMRs. However, there was little emphasis given to the urgency for the revival of nuclear energy in the United States. As an ASME Fellow Member, I am concerned that we are running out of time for building new nuclear power plants including inherently safe SMRs.Figure 1 shows the past and potential future of the U.S. nuclear power generation [1]. In the 1970s to 1990s, we were building nuclear power plants and reached roughly 19% nuclear power of the entire electric power demand. If this trend had not been stopped, today we would have produced about 25% of the total power demand in nuclear power plants, and if this trend would have continued, we would have reached 39% in 2040. This is still much less than roughly 80% nuclear power presently provided of the total electric power demand in France. No wonder that the carbon dioxide discharge per person in France is half of ours in the U.S.Since the early 2000s to about 2020, the nuclear power supply is expected to remain at 19% of total power production. If we do not wake up, old nuclear power plants will be retired and if no new nuclear plants are built, the remaining plants in the U.S. will only provide about 8% of our total electricity demand by 2040. If we start building nuclear plants now in a trend like in the 1970s to 1990s, we could reach 29% of our demand; however, this also requires the additional replacement of the old nuclear power plants. The loss of roughly 11% power generation by the shutdown of old nuclear power plants would be a large loss of green carbon-dioxide-free power generation, since nuclear power plants provide more than the half of all our green electricity.In the past, especially during the Cold War, more small nuclear reactors for submarines, aircraft carriers, icebreakers, and other ships were built than large reactors for power plants. These small reactors went all over the globe, even underneath the ice at the North Pole. Ships with nuclear reactors are in harbors and shipyards; they have to be maintained, repaired, and the reactors refueled. Such small reactors or modifications of them, if inherently safe, could also be used to generate electric power, especially for remote locations, to avoid high fuel supply and electricity transmission costs.SMRs should also be specifically used by industrial users, which currently use a large amount of fossil fuels for providing not just electric power but high-temperature heat. Most industrial processes could be clean by switching to SMRs for supplying process heat and electric power. An example is shown in Fig. 2, where a high-temperature gas-cooled reactor (HTR 250) provides heat at a temperature of 950°C (1740°F) and steam for an extraction turbine. The 65 kg/s (0.52 Mil.lb/h) helium can be used in a heat exchanger or steam reformer. The helium discharge temperature of 680°C (1200°F) can provide 50 kg/s (0.4 Mil.lb/h) main steam at 140 bar/540°C (2000 psi/1000°F) to the turbine. The turbine generator can provide a maximum of 50 MW if no steam is used for a specific application. However, main and/or extraction steam can be provided specifically for a high-temperature hydrogen production process or any other chemical processes [2].Combinations of the inherently safe HTRs with any specific industrial processes can be developed. Detailed designs of such combinations should be finalized and could become available now, because of the experience already gained with the HTR design. In 1984, a combination of an HTR 200 with a coal-to-gasoline conversion system was designed and ready to start the permitting procedures, but was stopped because of the antinuclear trend in Germany after Chernobyl. However, in China at present, two HTR 250 units are in their start-up phase.As we have seen in Fig. 1, we have only limited time to revitalize the nuclear power industry within the next couple of years. We cannot just wait and witness nuclear power generation rapidly decreasing in the U.S.

Sensitivity analysis of cooling demand applied to a large office building

Electricity is the “power to succeed.” However, the United States faces a hidden electricity crisis, i.e., the “power to fail.” As the economy grows at 2–3 percent per year, the total demand for electricity has grown in tandem at 2.1 percent per year over the 1994–2004 period. Inversely, however, electricity capacity margins, the percent of “spinning” supply above demand, have declined consistently over the last decade from 25–30 percent in 1992 to about 15 percent today. In fact, the Eastern Independent Power Grid, with nearly 75 percent of total U.S. electricity demand, has only a 13.9 percent capacity margin. Additionally, the North American Electric Reliability Council (NERC) forecast in 2006 that overall electricity demand will rise 19 percent by 2015, but overall electricity capacity will rise only 6 percent. This compound total demand growth coupled with declines in utility plant capacity margins only masks the serious underlying problem: peak electricity demand, typically for summertime air conditioning, is growing at 2.6 percent per year, consistently as fast as total electricity demand. While the nation considers the need for energy independence critical due to the fact that half the nation's oil consumption is imported, the resulting economic consequences of a peak electricity shortfall would be as bad or worse, given the nation's reliance on electricity to cool, light, and power motors and computers. That is the nexus of this article: the available energy technologies and programmatic procedures to reduce electricity peaks or peak-shaving in the U.S.

This paper uses the survey data on household electricity demand from five districts of Vientiane, Lao PDR, for the demand projection up to 2030 using the end-use model. The scenario analysis is used to verify the potential of an energy-saving program by alternating selected appliances with more energy-efficient ones following the labelling standard of Thailand. The demographic structure of electrified households and the energy efficiency of electric appliances are considered as the dominant factors affecting electricity demand. Under the base-case scenario, the total electricity demand of Vientiane increased from 593 GWh in 2013 to 965 GWh in 2030. In the energy efficiency scenario, it is revealed that the appliance standard enhancement program can save total electricity demand in 2030 by 147 GWh (−15.2%), where 117 GWh (−12.1%) of which is contributed by the air conditioner and 30 GWh (−3.1%) by the lighting equipment.

Based on the bottom-up modeling approach, this paper establishes a electricity demand forecasting model covering primary industry, secondary industry, tertiary industry, residential consumption and key sub-industries by using the method of sectoral analysis. The forecasting model can provide a scientific measure for determining the trend of China’s electricity demand in 2017 and 2018. The forecast results show that China’s economy will grow steadily in 2017, GDP growth rate is estimated to be about 6.8%, and total electricity demand is estimated to be 6354 TWh with a growth rate of 6.3%. The contribution rates of three industries and residential electricity demand will be 2.3%, 55.7%, 22.7% and 19.3%. In 2018, China’s economy will remain stable with an estimated GDP growth rate of 6.7%, total electricity demand will be 6674 TWh with a growth rate of 5.0%. The contribution rates of the three industries and residential electricity demand will be 2.6%, 57.6%, 22.8% and 17.0% respectively.

Two representative buildings were selected to qualitatively and quantitatively study the impact of lighting and of heating, ventilating, and air conditioning (HVAC) system operation on total electrical demand. Recordings were made at five minute intervals for total building electrical consumption and for selected lighting circuits. The data were collected during the times when electrical demand was highest. Using multiple linear regression, the impact on total electrical demand from operational and climatic variables was determined. The results from these analyses are presented. Various sensitivity analyses were conducted to show the difference between the average and peak demand levels and their implications for energy reduction strategies. >

The Demand For Storage Technologies In Energy Transition Pathways Towards 100% Renewable Energy For India

Electricity demand in Saudi Arabia is undergoing unprecedented changes following the implementation of efficiency measures and energy price reforms. These changes raise uncertainties about the potential trajectory of long-term electricity demand. Thus, this study uses a computable general equilibrium model to project sectoral electricity demand in Saudi Arabia through 2030. We project that growth in total Saudi electricity demand will significantly decelerate over the coming decade compared with historical trends. In our reference scenario, this demand reaches 365.4 terawatthours (TWh) by 2030. However, our sectoral decomposition shows large disparities across sectors. Demand is projected to grow more rapidly in the industrial and services segments than in the residential sector. We also simulate four additional scenarios for domestic electricity price reforms and efficiency policies. Successfully implementing these measures may result in significant energy savings. Aligning Saudi electricity prices with the average electricity price among G20 countries can reduce total electricity demand by up to 71.6 TWh in 2030. Independently enforcing efficiency policies can reduce total electricity demand by up to 118.7 TWh. Moreover, alternative policy scenarios suggest that the macroeconomic gains from energy savings can alleviate some of the Saudi energy system's burden on public finance.

This study presents a set of twelve monthly cross section regression analyses of the household demand for electricity. The methodology to be used is based upon a conditional demand framework which can be used to disaggregate the total household demand for electricity into the component demand functions for electricity through the media of particular appliances, even though no direct observations on specific appliance energy usage exist. The latter demand functions are used to estimate the monthly and annual average energy use for these appliances as well as the corresponding price and income elasticities.

Battery Electric vehicle (BEV) has been set as one of the most prominent sectors of automobile industry in China in the future due to its significant contribution to energy safety, low carbon emission and leading technology status in vehicle driven by new energy. High penetration of BEV will have obvious impacts on power systems, and its load characteristics are quite different from those traditional loads. Therefore with an eye on the safe, stable and economic operation of power system, this paper studied the impacts of EV on power systems from four aspects: total electricity demand, power rush in short period, power quality and vehicle to grid (V2G) technology. Total electricity demand by BEV charging in 2020 in China was firstly estimated in the paper, and it is sure that power system has the capability to meet this demand. However uncontrolled massive BEV charging will probably results in higher peak load and upgrading requirement of power systems, so orderly charging is required. EV battery is charged through rectifier, which will decrease power quality by harmonic current, therefore power electronic equipment is required to ensure power quality. Finally possibility of scheme of vehicle to grid (V2G) application is discussed when the scale of BEV is large enough and performance of EV battery is greatly improved.

Maua Nusa Penida is one of the hotels and villas in Nusa Penida which will be discussed in this research. The number of hotel blocks to be built is 4 blocks, where each block consists of 8 rooms. As for the villa as many as 26 various villas. There is also a main building and a restaurant that will serve as future support. Once the existing buildings are complex, the developers are required to plan all the buildings to be built in order to obtain security and also economic factors in the development process. From the results of the planning that has been carried out on each building, each building requires a different number of lights depending on the type of lamp, the type of building and also the area of the building. After getting the total electricity demand in a building, planning is continued by determining the area of cable conductors that supply each building. From the calculation results, it is also known that the type of cable used is planting cable (NYRGbY & NYFGbY) which has good insulation when planted in the ground and follows the provisions of PLN regarding voltage loss, which does not exceed 5% at the end of the conductor. The safety used in buildings uses MCB and also MCCB. Meanwhile, the safety of electric current in the LVMDP and SDP sections uses MCCB components. From the planning results, the total electricity demand is 159,441VA for zone 1 villas and also 142,536VA for zone 2 villas. From this calculation it is also known that the PLN power requirement in each zone is 164,000 VA. To get the convenience and reliability of the electrical system in this hotel and villa, the supply of electrical power in addition to the electricity source from PLN is also equipped with a backup power generator of 200 KVA in each zone.

A Multi-period Mixed Integer Linear Program for Assessing the Benefits of Power to Heat Storage in a Dwelling Energy System

Electricity demand forecasting constitutes a critical process in the operation and planning procedures of power networks that highly affects the decisions of utility providers and energy policy makers. Accurate forecasting is vital in reducing costs, related to excess electricity storage and infrastructures, and achieving enhanced power security and stability. A novel modeling approach for long-term electricity demand forecasting is introduced via the application of ordinal regression analysis. Annual forecasts of the total net electricity demand in the Greek interconnected power system are provided for the years 2016–2025. The Gross Domestic Product (GDP) has been identified as the greatest influential parameter on the evolution of electricity demand. Furthermore, the forecasting model has achieved a minimum Mean Absolute Percentage Error (MAPE) of 2.14%. The extracted forecasts indicate a constant increase of the total net electricity demand in Greece as a result of the expected economic growth during the upcoming years.

Long-term electricity demand scenarios for Malawi's electric power system