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Various problems often arise in high-rise buildings during the winter months due to the stack effect. In this study, the high-rise building of interest, located in South Korea, was experiencing constant loud noises in the winter due to the stack effect. Thus, we created a noise level reduction plan by creating a method for pressurizing the high-rise zones of the building according to outdoor conditions. To discover the appropriate pressurization operating modes, we applied a two-year commissioning process to the 50-story building of interest. The 1st- and 47th-floor elevator halls were identified to have the highest noise levels of all other floors. Prior to applying the reduction plan, the maximum noise level on the first floor with the HVAC system turned off was 85 dB(A) and with the HVAC system turned on it was 70 dB(A). Both values exceeded the criteria of 57 dB(A) for a lobby space of a commercial building. In the case of the 47th floor, the maximum noise level with the HVAC system turned off was 58.7 dB(A) and with the HVAC system turned off was 56.0 dB(A), despite the latter having increased airtightness performance and applying preliminary pressurization (i.e., HVAC operation mode 2). These values exceeded the criteria of 48 dB(A) for an elevator hall in a commercial building. Following this initial data, we determined to pressurize the high/mid-rise zones of the building according to the outdoor air temperature and wind velocity conditions, which we categorized into four types (i.e., HVAC operation mode 4). To this effect, the first-floor elevator hall’s maximum noise level was 56.6 dB(A), meeting the criteria, and the 47th-floor elevator hall’s maximum noise level was 49.5 dB(A), still exceeding the criteria but by an insignificant amount. Although the HVAC pressurization operation we utilized resulted in favorable results for the target building A, it may not be as effective in other new high-rise buildings, creating changes to the indoor air environment or to the energy costs in maintaining a building. However, for the purposes of resolving the stack effect, we believe that the commissioning process we took to optimize the HVAC operation that is presented here can be applied to other new and existing high-rise commercial buildings.

Maintaining high facility reliability in power plants is essential to secure long-term electricity supply. This paper applies the survival analysis to the actual unit level power generation data in Korea to estimate the relationship between facility reliability and the preventive maintenance. Duration of generators between forced outages is used to measure plant reliability. the empirical analysis shows that preventive maintenance cost, planned outage for maintenance, use rate, and reserve margin lead to the longer duration of generators and, in turn, the lower forced outage rates. We uncover that the marginal benefit of the preventive maintenance cost is decreasing at an increasing rate. It indicates that the marginal benefit of the “current” maintenance cost is minimal. Results in the paper imply that power plants in Korea might be spending unnecessarily high maintenance costs considering already having world’s lowest forced outage rates.

Global issues are such that we should assess and manage a variety of risks and uncertainties. Due to increasing world complexity, the development of an adequate and innovative conceptual framework, anchored in the literature, is required. This article contributes to this effort with an approach particularly relevant to decision-makers dealing with threats of different natures, limited heterogeneous information, and experts’ assessments tainted by doubts. Our approach is based on two pillars: 1) An “acuity scale”, based on the probability of the occurrence of an event, its impact and the experts’ degree of doubt; 2) A taxonomy focused on the concepts of risk, uncertainty, gamble and butterfly ambiguity. Accordingly, we present in a second step the major management implications of such approach. Global policy trends (e.g., sustainability transition) put energy sector decision-makers at the forefront of risk and uncertainty management. Consequently, we carry out a case study focused on Swiss energy policy since the 1980s, including its inception, the turnaround provoked by the Fukushima accident, and the government’s 2050 energy strategy. Our investigation shows that the proposed conceptual framework allows for the development of an original analysis of the main drivers that influence governmental policies and stakeholder strategies.

This paper reports on an experimental study of a top-lit updraft cook stove with a focus on gasification. The reactor is operated with primary air only. The performance is studied for a variation in the primary airflow, as well as reactor geometry. Temperature in the reactor, air flow rate, fuel consumption rate, and producer gas composition were measured. From the measurements the superficial velocity, pyrolysis front velocity, peak bed temperature, air fuel ratio, heating value of the producer gas, and gasification rate were calculated. The results show that the producer gas energy content was maximized at a superficial velocity of 9 cm/s. The percent char remaining at the end of gasification decreased with increasing combustion chamber diameter. For a fixed superficial velocity, the gasification rate and producer gas energy content were found to scale linearly with diameter. The energy content of the producer gas was maximized at an air fuel (AF) ratio of 1.8 regardless of the diameter.

In this paper, petroleum product (mainly petrol and diesel) consumption in the transportation sector of China is analyzed. This was based on the Bayesian linear regression theory and Markov Chain Monte Carlo method (MCMC), establishing a demand-forecast model of petrol and diesel consumption introduced into the analytical framework with explanatory variables of urbanization level, per capita GDP, turnover of passengers (freight) in aggregate (TPA, TFA), and civilian vehicle number (CVN) and explained variables of petrol and diesel consumption. Furthermore, we forecast the future consumer demand for oil products during “The 12th Five Year Plan” (2011–2015) based on the historical data covering from 1985 to 2009, finding that urbanization is the most sensitive factor, with a strong marginal effect on petrol and diesel consumption in this sector. From the viewpoint of prediction interval value, urbanization expresses the lower limit of the predicted results, and CVN the upper limit of the predicted results. Predicted value from other independent variables is in the range of predicted values which display a validation range and reference standard being much more credible for policy makers. Finally, a comparison between the predicted results from autoregressive integrated moving average models (ARIMA) and others is made to assess our task.

The design of a solar thermal installation is based on the lowest irradiance levels that occur during winter. However, there are consecutive days with irradiance levels well below those used for the design, which are called in this work “critical irradiance levels”. To solve this challenge, a statistical analysis is carried out to find a representative percentile of 22 years of consecutive days with “critical irradiance levels”. A case study of a cotton-dyeing industrial process requires 18.5 m3 of hot water and operates for 2.75 h at temperatures between 40 and 90 °C. Environmental variables for 22 years were analyzed and validated to design a solar thermal installation (solar collector network and storage system) and a coupled heat pump. The fifth percentile, with three consecutive days and low irradiance levels, was the most repetitive. For this case, a storage system of 46.5 m3 guaranteed heat load at target temperature. The simple payback was 14.1 years, and the energy cost was 0.094 USD/kWh, which was competitive against the energy cost from using fossil fuels, 0.064 USD/kWh. The design based on critical environmental conditions guarantees a continuous supply of energy to the industrial process and defines the minimum availability of solar energy to supply a process.

To reduce the influence of wind power output uncertainty on power system stability, demand response (DRPs) and energy storage systems (ESSs) are introduced while solving scheduling optimization problems. To simulate wind power scenarios, this paper uses Latin Hypercube Sampling (LHS) to generate the initial scenario set and constructs a scenario reduction strategy based on Kantorovich distance. Since DRPs and ESSs can influence the distribution of demand load, this paper constructs a joint scheduling optimization model for wind power, ESSs and DRPs under the objective of minimizing total coal cost, and constraints of power demand and supply balance, users’ demand elasticity, thermal units’ startup-shutdown, thermal units’ output power climbing and wind power backup service. To analyze the influences of ESSs and DRPs on system wind power consumption capacity, example simulation is made in a 10 thermal units system with a 1000 MW wind farm and 400 MW energy storage systems under four simulation scenarios. The simulation results show that the introduction of DRPs and ESSs could promote system wind power consumption capacity with significantly economic and environment benefits, which include less coal consumption and less pollutant emission; and the optimization effect reaches the optimum when DRPs and ESSs are both introduced.

With the proliferation of large-scale grid-connected wind farms, subsynchronous oscillation (SSO) incidents associated with Type-4 wind turbines (WTs) with a permanent magnet synchronous generator (PMSG) have occurred frequently. These incidents have caused severe reliability risks to the power grid. Conventionally, P-Q capability charts are utilized to ensure the safety operating region of a synchronous generator. However, a PMSG WT exhibits completely different and dynamic P-Q capability characteristics due to the difference in energy conversion technique and several critical factors related to the WT power converters. This paper presents a comprehensive dynamic P-Q capability study of a PMSG WT with sufficient and accurate considerations of the WT control and operation in the dq reference frame, its power converter constraints, and grid dynamics. Models of a PMSG WT are first developed based on its control principle in the dq reference frame. Then, algorithms for obtaining the P-Q capability charts of the WT are developed with the considerations of complete WT constraints in different aspects. The study analyzes the root cause of many abnormal operations of grid-connected PMSG WTs, reported in the literature, from the dynamic P-Q capability perspectives. The proposed study is verified via an electromagnetic transient (EMT) model of a grid-connected Type-4 WT.