Pervasive sensing as a mechanicsm for the effective control of CHP plant in commerical buildings

A recently completed, EPSRC-funded project researched the use of low cost, pervasive sensing to monitor building environmental conditions and occupant interactions as a means to reduce the uncertainties associated with the creation of a building model for refurbishment options and smarter control appraisal. This paper gives a brief introduction to the pervasive sensing system as established within the project and describes its use to enable simulations of the multi-input, multi-output (MIMO) control of a combined heat and power (CHP) unit in a commercial building context. Within the project, data from pervasive sensing was used to calibrate a simulation model of an office building and impose occupant-related inputs at the time step level as a means to reduce modelling uncertainty. The MIMO input parameters considered include space temperatures, heat store temperatures, electricity demand and electricity tariff, while the output parameters include space heat supply, heat stored, electricity utilised locally or exported, and CHP unit fuel use. The simulation model was used to compare performance when the CHP unit is subjected to conventional and MIMO control. It is demonstrated that the pervasive sensing approach enables control that delivers enhanced energy performance

Effect of tilt angle on the performance of a thin-film photovoltaic system

Solar energy is among the cleanest and most sustainable ways to enhance electrical supply's resiliency and reliability for domestic and industrial use. A Photovoltaic (PV) system is the most effective way of capturing solar energy. Long-term warranty, low-cost maintenance, and vast resource availability, solar power generation has an advantage over other approaches. Thin-film technology PV cells are a new kind of solar cell that offers an efficient technique of generating electricity from sunlight. The thin-film PV technology (FFMAT-10, Renovagen, UK) used in this study can supply 0.9 to 1.6 kW of energy to the fast-fold energy hub. The hub’s system status and configuration display battery power input, battery’s state of charge, thin-film PV power and AC power output. Two fast-fold mats (with a surface area of 25.3 m2) were connected to the energy hub. Increasing energy demand coupled with frequent power outages, and inaccessibility of electricity in rural areas necessitates the usage of PV systems at their best performance level. The study objective, therefore, sought to assess the effect of tilt angle on the performance of the thin-film PV system. The study was conducted at Kimicha in Kirinyaga County Kenya, and Juja, Kenya at tilt angles between 0o to 30o. The results indicated that the mean peak PV power for Kimicha was 347.8±231.9 W at 5o and 517.7± 131.3 W at 15ofor Juja. The maximum solar radiation during the study period was 1086.4 ±211.4 W/m2 for Juja and 973.5±219.93 W/m2 for Kimicha. From the study, it was realized that an optimal tilt angle yields optimum solar radiation that translates to maximum power production. Even though the study was conducted in two different regions, it may be applied to any other geographical location. The outcome of the study aids in acquiring self-sustaining power in the most remote locations where electricity is scarce as well as improving energy security

Pervasive sensing as a mechanism for the effective control of CHP plant in commercial buildings

A recently completed, EPSRC-funded project researched the use of low cost, pervasive sensing to monitor building environmental conditions and occupant interactions as a means to reduce the uncertainties associated with the creation of a building model for refurbishment options and smarter control appraisal. This paper gives a brief introduction to the pervasive sensing system as established within the project and describes its use to enable simulations of the multi-input, multi-output (MIMO) control of a combined heat and power (CHP) unit in a commercial building context. Within the project, data from pervasive sensing was used to calibrate a simulation model of an office building and impose occupant-related inputs at the time step level as a means to reduce modelling uncertainty. The MIMO input parameters considered include space temperatures, heat store temperatures, electricity demand and electricity tariff, while the output parameters include space heat supply, heat stored, electricity utilised locally or exported, and CHP unit fuel use. The simulation model was used to compare performance when the CHP unit is subjected to conventional and MIMO control. It is demonstrated that the pervasive sensing approach enables control that delivers enhanced energy performance

Reduce Household Energy Consumption Using Passive Methods

Recent researches and studies demonstrate that the need for sustainable buildings which do less impact on the environment is rising in the worldwide [1], [2]. Not only the energy generator from energy supply side needs to be considered to build a sustainable building, but also the novel construction methods and materials from demand side will contribute to the energy saving. The aim of this study is to carry out an investigation of a property's energy consumption from the view of passive energy saving, and then use the results to determine the best energy saving plan. A field audit and the Design Builder software simulation of a detached house were carried out during this study. The results indicate that the simulation energy consumption (9.66MWh) is matching well with the actual energy usage (9.76MWh) and the property consumes less energy than national average (16.90MWh). From the study, it is found that the annual total household energy consumption reduced for about 33% than traditional construction materials and technology by using passive energy saving methods

Evaluation of energy and indoor environmental performance of a UK passive house dwelling

The preliminary findings of the energy and indoor environmental performance of a Passive House dwelling in North East of England is presented in this paper. This dwelling is designed to comply with the Passive House Standard (certified by the International Passive House Association) which aims to reduce energy consumption and carbon emissions. The property benefits from advanced building fabric design and materials, PV array, mechanical ventilation with heat recovery system (MVHR) and high efficiency domestic hot water storage vessel to minimise operational carbon emissions. Power generated by the PV panel, imported grid electricity and mains gas consumption of this house are monitored by a proprietary monitoring package; and data of indoor temperature, relative humidity and resident occupancy at several different locations in the dwelling are also recorded. A computational model of this property was developed using DesignBuilder software. The model was validated using the data monitored on site; and is used to predict and evaluate the performance of the house. The initial findings of this study shows the advantages of Passive House in achieving high thermal comfort and good indoor air quality with much lower energy consumption compares to the national averag

Effect of carbon coated aluminum nanoparticles as additive to biodiesel-diesel blends on performance and emission characteristics of diesel engine

This study investigates the effects of carbon coated aluminum (Al@C) nanoparticles added to diesel-biodiesel blends as additives on engine performance and emissions. The Al@C nanoparticles are added into the diesel-biodiesel fuel in the mass fractions of 30 ppm under ultrasonic mixing. The experimental tests are conducted using a Cummins diesel engine. For comparison, three kinds of fuels including diesel-biodiesel blend (B10), B10 with 4% ethanol (B10E4), and B10 with 4% ethanol and 30-ppm nanoparticles (B10E4N30) are used for the tests under the European Stationary Cycle (ESC). The results show clearly that adding Al@C nanoparticles can reduce brake specific fuel consumption (BSFC) by 6% on average; along with a drop of 6% in NOX emission and CO emission is reduced by 19%, comparing with B10. However, the presence of ethanol in fuel blend increases THC emission. Nevertheless, addition of Al@C nanoparticles reduces THC emission by 14.5% compared with B10E4. The emission of particles number (PN) is increased by 2.2 times for B10E4N30 on average but is reduced by 11.8% for B10E4 (adding ethanol only) on the contrary, compared to B10. The studies on morphology and phase structure of nanoparticles after combustion indicate that Al@C nanoparticles have been transformed into alumina nanoparticles