Optimal sizing and siting of renewable energy resources in distribution systems considering time varying electrical/heating/cooling loads using PSO algorithm

Distributed Generation (DG) sources based on Renewable Energy (RE) can be the fastest growing power resources in distribution systems due to their environmental friendliness and also the limited sources of fossil fuels. In general, the optimal location and size of DG units have profoundly impacted on the system losses in a distribution network. In the present article, the Particle Swarm Optimization (PSO) algorithm is employed to find the optimal location and size of DG units in a distribution system. The optimal location and size of DG units are determined on the basis of a multi-objective strategy as follows: (i) the minimization of network power losses, (ii) the minimization of the total costs of Distributed Energy Resources (DERs), (iii) the improvement of voltage stability, and (iv) the minimization of greenhouse gas emissions. The related distribution system was assumed to be composed of the fuel cells, wind turbines, photovoltaic arrays, and battery storages. The electrical, cooling, and heating loads were also considered in this article. The heating and cooling requirements of the system consist of time varying water heating load, space heating load, and space cooling load. In this study, the waste and fuel cell were used to produce the required heating and cooling loads in the distribution system. In addition, the absorption chiller was used to supply the required space cooling loads. A detailed performance analysis was carried out on 13 bus radial distribution system to demonstrate the effectiveness of the proposed methodology.     

Photovoltaic-thermal (PV/t) panel to minimize electrical and air conditioning energy consumption of a typical office in Beirut

A combined photovoltaic–thermal (PV/t) panel is proposed to produce simultaneously electricity and heat from one integrated unit. The unit utilizes effectively the solar energy through achieving higher PV electrical efficiency and using the thermal energy for heating applications. To predict the performance of the PV/t at a given environmental conditions, a transient mathematical model was developed. The model was integrated in a heating application for a typical office space in the city of Beirut to provide the office needs for electricity, heating during winter season, and dehumidification and evaporative cooling during the summer season. To minimize the yearly office energy (electrical and heat) needs, the PV/t panel cooling air flow rate and the dehumidification regeneration temperature were determined for opimal unit operation. Thermal energy savings of up to 85% in winter and 71% in summer were achived compared to conventional systems at a payback period of 8 years for the panels.     

A novel objective function for optimal DG allocation in distribution systems using meta-heuristic algorithms

Meta heuristic algorithms have been introduced as a powerful method to solve the nonlinear optimization problems. These algorithms have been employed in many complex engineering problems due to their high capability in finding the solutions and reaching the optimal results within a short period of time. Optimization of distributed generation units in distribution systems, which have profoundly impacted on the system losses and voltage profile, is one of these nonlinear problems. In this study, a novel objective function was proposed for optimization procedure by meta-heuristic algorithms. The related objective function consists of the total cost of distributed generation units, cost of the purchased natural gas, cost of distribution system power losses, and penalty for greenhouse gas emissions. The electrical, cooling, and heating loads were considered in this study. In the distribution system, the waste and fuel cell were used to supply the required heating and cooling loads. The meta-heuristic algorithms including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Imperialist Competitive Algorithm (ICA) were employed to find the optimal location and size of distributed generation units in a distribution system. A detailed performance analysis was done on 13 bus radial distribution system. The performances of three algorithms were compared with each other and results showed that the PSO was the fastest; and had the best solution and optimum results. Furthermore, the PSO reached the optimum solution in a fewer number of iterations than the GA and ICA algorithms.     

Analysis of a solar photovoltaic-assisted absorption refrigeration system for domestic air conditioning

Theoretical model of a solar photovoltaic integrated water-Lithium bromide absorption system is presented for domestic air conditioning. Surplus electrical energy from photovoltaic modules is used for charging the battery, which is utilized during the periods of zero or insufficient solar radiation. Minimum solar area required for each month is calculated and October is identified as the month requiring the highest area of photovoltaic arrays for a constant cooling load of 3.5 kW. The integrated system is found to be capable of sufficient amount of surplus electrical energy generation during both summer and winter months, with a daily excess of about 815 Ah of electrical energy on average over a complete calendar year. Designed system is found to be economically viable, having an energy payback period of 2.7 years.     

STRATIFICATION VARIABILITY IN THREE MORPHOMETRICALLY DIFFERENT LAKES UNDER IDENTICAL METEOROLOGICAL FORCING1

ABSTRACT: Synoptic water temperature measurements were taken in three temperate lakes located within 25 km of one another to study the effects of morphometry (and changes in weather) on seasonal and short-term thermal stratification characteristics. Two of the lakes had nearly the same surface areas and two had nearly identical mean depths; all were exposed to identical weather conditions. The dominance of weather over morphometry on the water surface temperature response was illustrated by the synoptic measurements in two different years. Stratification structure was also found to be dominated by weather for sufficiently deep lakes. Surface area effects were most subtle but explainable as sheltering effects. The onset of stratification was not, as traditionally described, a simple, gradual response of a lake to the annual solar radiation cycle. Rather it depends on a series of alternating heating, cooling, and mixing cycles similar to annual and diel cycles but with a period of approximately five days. These were in direct response to the passage of major weather systems and displayed no apparent time lag. No comparable synoptic water temperature data set could be found in the literature.     

A Heat Dynamic Model for Intelligent Heating of Buildings

This article presents a heat dynamic model for prediction of the indoor temperature in an office building. The model has been used in several flexible load applications, where the indoor temperature is allowed to vary around a given reference to provide power system services by shifting the heating of the building in time. This way the thermal mass of the building can be used to absorb energy from renewable energy source when available and postpone heating in periods with lack of renewable energy generation. The model is used in a model predictive controller to ensure the residential comfort over a given prediction horizon.     

RIPARIAN MICROCLIMATE AND STREAM TEMPERATURE RESPONSE TO FOREST HARVESTING: A REVIEW1

Forest harvesting can increase solar radiation in the riparian zone as well as wind speed and exposure to air advected from clearings, typically causing increases in summertime air, soil, and stream temperatures and decreases in relative humidity. Stream temperature increases following forest harvesting are primarily controlled by changes in insolation but also depend on stream hydrology and channel morphology. Stream temperatures recovered to pre‐harvest levels within 10 years in many studies but took longer in others. Leaving riparian buffers can decrease the magnitude of stream temperature increases and changes to riparian microclimate, but substantial warming has been observed for streams within both unthinned and partial retention buffers. A range of studies has demonstrated that streams may or may not cool after flowing from clearings into shaded environments, and further research is required in relation to the factors controlling downstream cooling. Further research is also required on riparian microclimate and its responses to harvesting, the influences of surface/subsurface water exchange on stream and bed temperature regimes, biological implications of temperature changes in headwater streams (both on site and downstream), and methods for quantifying shade and its influence on radiation inputs to streams and riparian zones.     

Indirect carbon reduction by residential vegetation and planting strategies in Chicago, USA

Concern about climate change has evoked interest in the potential for urban vegetation to help reduce the levels of atmospheric carbon. This study applied computer simulations to try to quantify the modifying effects of existing vegetation on the indirect reduction of atmospheric carbon for two residential neighborhoods in north-west Chicago. The effects of shading, evapotranspiration, and windspeed reduction were considered and were found to have decreased carbon emissions by 3.2 to 3.9% per year for building types in study block 1 where tree cover was 33%, and -0.2 to 3.8% in block 2 where tree cover was 11%. This resulted in a total annual reduction of carbon emission averaging 158.7 (+/- 12.8) kg per residence in block 1 and 18.1 (+/- 5.4) kg per residence in block 2. Windspeed reduction greatly contributed to the decrease of carbon emission. However, shading increased annual carbon emission from the combined change in heating and cooling energy use due to many trees in the wrong locations, which increase heating energy use during the winter. The increase of carbon emission from shading is somewhat specific to Chicago, due in part to the large amount of clean, nuclear-generated cooling energy and the long heating season. In Chicago, heating energy is required for about eight months from October to May and cooling energy is used for the remaining 4 months from June to September. If fossil fuels had been the primary source for cooling energy and the heating season had been shorter, the shading effects on the reduction of carbon emission would be greater. Planting of large trees close to the west wall of buildings, dense planting on the north, and avoidance of planting on the south are recommended to maximize indirect carbon reduction by residential vegetation, in Chicago and other mid and high-latitude cities with long heating seasons.     

集中供热锅炉烟气脱硝技术的开发与应用

通过锅炉结构的改进、SCR工艺装置的优化、快速跟踪负荷变化的还原剂制备及控制调节技术的开发和应用等系统性的工作,有效满足了集中供热锅炉房烟气脱硝工程的技术要求,成功开发了集中供热锅炉烟气脱硝技术。在实际工程应用中,确保了在不同负荷段下,锅炉至SCR装置入口段的温度满足脱硝要求,SCR工艺装置能够在不同负荷下连续稳定运行并很好地跟踪负荷的变化,确保氨逃逸率满足设计要求,保证锅炉的安全稳定运行。     

Modeling of Low Temperature Geothermal District Heating Systems

Abstract

In this work, low temperature geothermal district heating systems with heat pumps have been studied and compared with fuel-oil boiler heating systems for intermittent and continuous regimes according to the optimum indoor air temperature and operational cost. Izmir Institute of Technology (IZTECH) Campus is taken as a case study. Various heat pump and boiler configurations are studied to meet required duty. Operational cost analysis for each alternative is conducted. According to the results, for IZTECH Campus the best alternative, which gives the optimum indoor air temperature and the lowest operational cost, is heat pump continuous regime.     

An experimental-computational study of DPF soot capture and heat regeneration

ABSTRACT

A diesel particulate filter (DPF) can effectively reduce the exhaust emissions of particulate matter (PM) and meet emission regulations. We report herein an experimental-numerical study to investigate the soot capture and regeneration behavior in a commonly used DPF. Simulations are performed using the AVL FIRE software that considers a fairly detailed DPF model. The model is validated using measured pressure drop history during soot capture, and temperature history during regeneration from a parallel experimental study using a diesel engine equipped with a DPF. Then, a detailed numerical study is performed to examine the soot capture and heat regeneration processes, and characterize the effects of various parameters on these processes and on DPF performance. Results indicate that the pressure drop during soot loading can be reduced by increasing the CPSI (channels per square inch), minimizing the amount of residual soot in each regeneration cycle, and using moderate gas flow rates. The DPF regeneration performance is characterized in terms of the rates of temperature rise and soot oxidation. Results indicate that these rates are enhanced, as the oxygen content in the exhaust stream is increased to about 12%, the rate of thermal heating is moderately increased, and as the exhaust gas flow rate is increased. Thus, the regeneration efficiency can be significantly improving by optimizing these parameters.     

Tri-generation investment analysis using Bayesian network: A case study

The increasing energy demand, increasing energy dependency, energy supply security, and environmental concerns have become a part of business policies since COP21 agreements in Paris, 2015. Combined cooling, heating, and power (CCHP or tri-generation) systems play an important role in paying the necessary attention to these policies. Tri-generation investment is a complex decision with hybrid use of energy resources. This article aims to reduce the complexity of this decision by the use of Bayesian belief networks in pre-investment stage of tri-generation investment project cycle. The proposed model gives an insight into decision analysis and helps the decision-makers either generate or purchase from it in order to meet the energy demand with different scenarios. The model is studied for a university case. The investment decision for a CCHP (tri-generation) system will be discussed as an alternative for purchasing the electricity and natural gas from the national grids.     

Managing the cooling capacity of the upper rhine: A case study

In most industrialized countries, environmental standards exist which prescribe the maximum allowable man-made increase in water temperature of a river. Together with flowrate and weather conditions, these standards determine the rate at which waste heat may be discharged into a river at any moment. Power generating stations with variable cooling systems can adjust their heat discharge into the river in compliance with environmental standards and by doing so exert an influence on power generation capacity. In this paper, a scheme is developed that allows a chain of power stations discharging into the same river to operate their cooling systems such that the output of total electricity is maximized and water temperature standards are accomodated. The optimum balance between stations is determined through dynamic programming. From the results of a simulation model using historical data, simple decision rules for day-to-day operation are abstracted. These rules are based solely on the river flow rates at each power station.     

Numerical estimation of photovoltaic–electrolyzer system performance on the basis of a weather database

We performed a numerical simulation to investigate the performance of a photovoltaic (PV)–electrolyzer on the basis of a simulated weather database during the summer solstice (SS), autumnal equinox (AE), and winter solstice (WS), and all year round. First, we selected a location in southern Taiwan (latitude: 22.65°N) to create a local weather simulation database that included daily solar radiation, wind speed, and ambient temperature. The I–V curves of a PV system and an electrolyzer were obtained numerically by using Simpson integration computation. Subsequently, the optimal configuration of a PV driving system comprising the electrolyzer and the PV panel was determined. The database of weather conditions was input into the numerical estimation model of the PV–electrolyzer system, and the hydrogen generation rates and hydrogen production volumes under both clear skies and changeable weather conditions were obtained.     

Electricity systems with near-zero emissions of CO2 based on wind energy and coal gasification with CCS and hydrogen storage

Emissions from electricity generation will have to be reduced to near-zero to meet targets for reducing overall greenhouse gas emissions. Variable renewable energy sources such as wind will help to achieve this goal but they will have to be used in conjunction with other flexible power plants with low-CO₂ emissions. A process which would be well suited to this role would be coal gasification hydrogen production with CCS, underground buffer storage of hydrogen and independent gas turbine power generation. The gasification hydrogen production and CO₂ capture and storage equipment could operate at full load and only the power plants would need to operate flexibly and at low load, which would result in substantial practical and economic advantages. This paper analyses the performances and costs of such plants in scenarios with various amounts of wind generation, based on data for power demand and wind energy variability in the UK. In a scenario with 35% wind generation, overall emissions of CO₂ could be reduced by 98–99%. The cost of abating CO₂ emissions from the non-wind residual generation using the technique proposed in this paper would be less than 40% of the cost of using coal-fired power plants with integrated CCS.     

Effect of steam hydration on performance of lime sorbent for CO2 capture

Lime is considered a feasible sorbent for the capture of CO₂ from large stationary sources. The positive attributes of a natural source material, low cost and lack of harmful by-products are offset by rapid deterioration in performance and high regeneration temperature. Performance can be improved by hydrating the lime using steam. We investigate a steam hydration process wherein lime is hydrated for 5 min at 300 °C and atmospheric pressure in a mixture of steam and CO₂. The experiments consisted of 10 capture cycles with 60% of the lime active at the end. Extrapolation using a decay model suggests a residual carbonation level of 48%, significantly higher than the 8% achieved by dry lime cycles. The cost of replacement sorbent under these conditions is less than $1/t of CO₂ captured. The hydrated lime process also reduces the thermal load, for heating and cooling, by half as well as the inventory, and therefore solids handling, by a factor 5 over dry lime. The introduction of the hydration reaction provides another exothermic reaction for heat management.     

Electric load management in developing countries

Energy planners in developing countries have traditionally sought to meet their nations' growing electricity demands by adding more generation and transmission capacity. But as the foreign investment situation became critical in the 1980s, private investment and system efficiency improvement programmes began to garner interest. One of the most promising system efficiency improvement options is load management, which uses a variety of techniques to utilize the electricity system's existing capacity more efficiently. However, to date, only three countries have seriously considered implementing large load management programmes: Pakistan, Peru and Costa Rica. This paper describes a 1987-89 load control demonstration programme in Costa Rica, sponsored by the US Agency for International Development (AID), in which participating industries were able to reduce their peak demand by 14%.     

温度冲击试验设备实现途径及热负荷分析

结合试验指标要求,对温度冲击试验设备实现途径进行分析比较,选择两箱式作为试验设备的实现方式;对设备组成结构及制冷、加热流程进行阐述,并对温度冲击试验过程中两种制冷状态下的热负荷进行了分析计算。     

DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

Integrated energy management strategy of powertrain and cooling system for PHEV

ABSTRACT

Energy management strategy (EMS) is crucial in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). Existing studies on EMS mostly manage powertrain and cooling system separately which cannot get the minimum total energy consumption. This paper aims to propose a novel EMS for a new type of dual-motor planetary-coupled PHEV, which considers cooling power demand and effect of temperature on fuel economy. Temperature-modified engine model, lithium-ion battery model, two motors, and cooling system models are established. Firstly, the separated EMS (S-EMS) is designed which manages powertrain and cooling system separately. Sequentially, after the analysis of thermal characteristics of the powertrain and cooling system, the thermal-based EMS (T-EMS) is then proposed to manage two systems coordinately. In T-EMS, cooling power demand and the charging/discharging energy of motors are calculated as equivalent fuel consumption and integrated into the object function. Besides, a fuzzy controller is also established to deicide the fuel-electricity equivalent factor with consideration of the effect of temperature and state of charge on powertrain efficiency. Finally, the hardware-in-loop experiment is carried out to validate the real-time effect of EMS under the New European Driving Cycle. The result shows that cooling power demand and temperature can significantly affect the fuel economy of the vehicle. T-EMS shows better performance in fuel economy than S-EMS. The equivalent fuel consumption of the cooling system of T-EMS decreases by 27% compared with that of S-EMS. The total equivalent fuel consumption over the entire trip of PHEV using T-EMS is reduced by 9.7%.