Optimisation of stand-alone hybrid energy systems for power and thermal loads

Stand-alone hybrid energy systems are an attractive option for remote communities without a connection to a main power grid. However, the intermittent nature of solar and other renewable sources adversely affects the reliability with which these systems respond to load demands. Hybridisation, achieved by combining renewables with combustion-based supplementary prime movers, improves the ability to meet electric load requirements. In addition, the waste heat generated from backup Internal Combustion Engines or Micro Gas Turbines can be used to satisfy local heating and cooling loads. As a result, there is an expectation that the overall efficiency and Greenhouse Gas Emissions of stand-alone systems can be significantly improved through waste heat recovery. The aims of this PhD project are to identify how incremental increases to the hardware complexity of hybridised stand-alone energy systems affect their cost, efficiency, and CO2 footprint. The research analyses a range of systems, from those designed to meet only power requirements to others satisfying power and heating (Combined Heat and Power), or power plus both heating and cooling (Combined Cooling, Heating, and Power). The majority of methods used focus on MATLAB-based Genetic Algorithms (GAs). The modelling deployed finds the optimal selection of hardware configurations which satisfy single- or multi-objective functions (i.e. Cost of Energy, energy efficiency, and exergy efficiency). This is done in the context of highly dynamic meteorological (e.g. solar irradiation) and load data (i.e. electric, heating, and cooling). Results indicate that the type of supplementary prime movers (ICEs or MGT) and their minimum starting thresholds have insignificant effects on COE but have some effects on Renewable Penetration (RP), Life Cycle Emissions (LCE), CO2 emissions, and waste heat generation when the system is sized meeting electric load only. However, the transient start-up time of supplementary prime movers and temporal resolution have no significant effects on sizing optimisation. The type of Power Management Strategies (Following Electric Load-FEL, and Following Electric and Following Thermal Load- FEL/FTL) affect overall Combined Heating and Power (CHP) efficiency and meeting thermal demand through recovered heat for a system meeting electric and heating load with response to a specific load meeting reliability (Loss of Power Supply Probability-LPSP). However, the PMS has marginal effects on COE. The Electric to Thermal Load Ratio (ETLR) has no effects on COE for PV/Batt/ICE but strongly affects PV/Batt/MGT-based hybridised CHP systems. The higher thermal than the electric loads lead to higher efficiency and better environmental footprint. Results from this study also indicate that for a stand-alone hybridised system operating under FEL/FTL type PMS, the power only system has lower cost compared to the CHP and the Combined Cooling, Heating, and Power (CCHP) systems. This occurs at the expense of overall energy and exergy efficiencies. Additionally, the relative magnitude of heating and cooling loads have insignificant effects on COE for PV/Batt/ICE-based system configurations, however this substantially affects PV/Batt/MGT-based hybridised CCHP systems. Although there are no significant changes in the overall energy efficiency of CCHP systems in relation to variations to heating and cooling loads, systems with higher heating demand than cooling demand lead to better environmental benefits and renewable penetration at the cost of Duty Factor. Results also reveal that the choice of objective functions do not affect the system optimisation significantly

Prospects of Rice Husk Gasification for Power Generation in Bangladesh

Electricity is the basic requirement to promote socio-economic development. In recent years, Bangladesh is facing severe power crisis all over the country, but the rural areas are the most vulnerable. This acute electricity crisis along with the conventional fuel crunch is affecting every sector of the country and economy is being crippled. To reduce the dependency on fossil fuels, rice husk which are widely abundant agricultural waste from rice industry could play a vital role in this regards. Bangladesh is an agricultural country and produces huge quantity of rice every year. In the year 2011, the total rice production was around 50.63 million tones. Husk is the waste biomass produce during the rice processing, on average it accounts around 20% of the rice produced on weight basis (10.12 million tones). The potential of power generation from rice husk by gasification is around 310 MWe in Bangladesh. The power plant to be installed near the large rice mills `cluster area' in Dinajpur, Bogra, Naogaon, Chapainawabganj and Ishwardi with the surplus rice husk. This paper consolidates information from various studies on the availability of rice husk, its characterization and estimates possible power potential that can be realized

Economic Evaluation of the PV Micro Utilities Installed by Grameen Shakti for Rural Electrification in Bangladesh

Sharing expensive technology can serve many users, even poor users. Grameen Shakti has developed a special programnamed PV micro utility to make it easier for those who cannot afford SHSs individually. Under this program, GrameenShakti allows people to share the cost and the subsequent benefit of using a SHS. In this study, operation and financialmechanism, analysis of cost of systems, tariff system, simple payback period, NPV and IRR of the micro utility systemshave been analyzed to show the financial viability of PV MU from the PV MU owner’s perspective. Results suggest thatthese systems have simple payback period of around 4-6 years. The NPV of systems varied from 27,000 BDT to 144,000BDT. The levelized electricity cost of PV MU systems is 70 BDT (~0.86 $)/kWh in Bangladesh. The owner has to spendonly 7.50 BDT/day but can earn at least 30-40 BDT per day, and up to 130-200 BDT/day.Keywords - Rural Electrification, Solar PV, Grameen Shakti, Bangladesh, Economic Evaluation

A Partial Backlogging Inventory Model for Deteriorating Item under Fuzzy Inflation and Discounting over Random Planning Horizon: A Fuzzy Genetic Algorithm Approach

An inventory model for deteriorating item is considered in a random planning horizon under inflation and time value money. The model is described in two different environments: random and fuzzy random. The proposed model allows stock-dependent consumption rate and shortages with partial backlogging. In the fuzzy stochastic model, possibility chance constraints are used for defuzzification of imprecise expected total profit. Finally, genetic algorithm (GA) and fuzzy simulation-based genetic algorithm (FSGA) are used to make decisions for the above inventory models. The models are illustrated with some numerical data. Sensitivity analysis on expected profit function is also presented. Scope and Purpose. The traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However, to keep sales higher, the inventory level would need to remain high. Of course, this would also result in higher holding or procurement cost. Also, in many real situations, during a longer-shortage period some of the customers may refuse the management. For instance, for fashionable commodities and hightech products with short product life cycle, the willingness for a customer to wait for backlogging is diminishing with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But in the past, the economic situation of most of the countries has changed to such an extent due to large-scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any more. The purpose of this paper is to maximize the expected profit in the random planning horizon

A Partial Backlogging Inventory Model for Deteriorating Item under Fuzzy Inflation and Discounting over Random Planning Horizon: A Fuzzy Genetic Algorithm Approach

An inventory model for deteriorating item is considered in a random planning horizon under inflation and time value money. The model is described in two different environments: random and fuzzy random. The proposed model allows stock-dependent consumption rate and shortages with partial backlogging. In the fuzzy stochastic model, possibility chance constraints are used for defuzzification of imprecise expected total profit. Finally, genetic algorithm (GA) and fuzzy simulation-based genetic algorithm (FSGA) are used to make decisions for the above inventory models. The models are illustrated with some numerical data. Sensitivity analysis on expected profit function is also presented. Scope and Purpose. The traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However, to keep sales higher, the inventory level would need to remain high. Of course, this would also result in higher holding or procurement cost. Also, in many real situations, during a longer-shortage period some of the customers may refuse the management. For instance, for fashionable commodities and high-tech products with short product life cycle, the willingness for a customer to wait for backlogging is diminishing with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But in the past, the economic situation of most of the countries has changed to such an extent due to large-scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any more. The purpose of this paper is to maximize the expected profit in the random planning horizon

Initial‐valued first‐order fuzzy differential equation in Bi‐level inventory model with fuzzy demand

In the present paper, two methods for the solution of an initial valued first ordered fuzzy differential equation are presented and applied in a fuzzy EOQ model. The constructed model is a bi‐level inventory problem involving wholesaler‐retailers‐customers. The wholesaler buys and sells the item instantaneously to several retailers. In the next level, the retailers sell the units to customers with a time dependent imprecise demand, which introduce the fuzzy nature in the differential equation. The selling price of the item is a step‐wise time dependent decreasing function. The fuzzy objectives are transformed into crisp one following fuzzy extension principle and centroid formula. The model is illustrated through Interactive Fuzzy Decision Making (IFDM) and Multi Objective Genetic Algorithm (MOGA) and the results from two methods are compared. First Published Online: 14 Oct 201

Optimum design, socioenvironmental impact, and exergy analysis of a solar and rice husk-based off-grid hybrid renewable energy system

This study examines the optimal sizing of an off-grid hybrid system comprising solar photovoltaic (PV), rice husk-based biomass, and lead-acid battery for meeting the electric demand of a rural community. Considering a selected remote village in Bangladesh as a case study, the proposed optimized system is primarily compared with the diesel generator and the micro gas turbine (MGT)-based options in techno-economic and environmental terms. The potential social benefits, such as the employment creation and the improvement in the human development index in the locality, have been investigated in this study. Moreover, the impacts of operational greenhouse gas emissions on the human health damage and the surrounding ecosystem have been examined. Additionally, an exergy analysis of the hybrid system and the components has been carried out. Results indicate that in addition to being the environmentally preferable option, the proposed PV/biomass/battery system offers a lower cost of energy of 0.314 $/kWh compared to the MGT-based system (0.377$/kWh). Although the diesel-based system offers a marginally better economy (9.55% less energy cost), it comes with the expense of probable damages to human health and the ecosystem worth of $15,211 and$6,608, respectively, making biomass the best option with no such damages. Exergy analysis reveals higher loss from PV than biomass and 13.09% system exergy efficiency. The assessment of the social indicators testifies to the potential of promoting the human development index from its current value and the formation of 1.41 jobs to as high as 15.15 full-time permanent jobs with the installation of hybrid systems in the community

Development of a day-ahead solar power forecasting model chain for a 250 MW PV park in India

Due to the steep rise in grid-connected solar Photovoltaic (PV) capacity and the intermittent nature of solar generation, accurate forecasts are becoming ever more essential for the secure and economic day-ahead scheduling of PV systems. The inherent uncertainty in Numerical Weather Prediction (NWP) forecasts and the limited availability of measured datasets for PV system modeling impacts the achievable day-ahead solar PV power forecast accuracy in regions like India. In this study, an operational day-ahead PV power forecast model chain is developed for a 250 MWp solar PV park located in Southern India using NWP-predicted Global Horizontal Irradiance (GHI) from the European Centre of Medium Range Weather Forecasts (ECMWF) and National Centre for Medium Range Weather Forecasting (NCMRWF) models. The performance of the Lorenz polynomial and a Neural Network (NN)-based bias correction method are benchmarked on a sliding window basis against ground-measured GHI for ten months. The usefulness of GHI transposition, even with uncertain monthly tilt values, is analyzed by comparing the Global Tilted Irradiance (GTI) and GHI forecasts with measured GTI for four months. A simple technique for back-calculating the virtual DC power is developed using the available aggregated AC power measurements and the inverter efficiency curve from a nearby plant with a similar rated inverter capacity. The AC power forecasts are validated against aggregated AC power measurements for six months. The ECMWF derived forecast outperforms the reference convex combination of climatology and persistence. The linear combination of ECMWF and NCMRWF derived AC forecasts showed the best result

Renewable energy snapshot and prospect in Bangladesh

This paper addresses the snap of renewable energy and the need for effective progress strategies linked with sustainable energy development along with prospect of renewable energy in Bangladesh. Our country is gifted with vast renewable energy resources such as biomass and solar. Approximately 73% of total energy demand of the country is supplied by local biomass based fuels. Bangladesh is endowed with abundant supplies of solar energy. Annually about 1.9 MWh energy is received per square meter of horizontal area in Bangladesh. Besides, hydro and wind as well as geothermal power can be considered as potential renewable energy resources. Karnafuli Hydro Station is the merely hydro energy power generation plant of the country that generates 230 MW. The annual wind speed at a height of 25m at some coastal locations is above 5 m/s and much higher in the pre-monsoon and monsoon periods

Abatement of energy loss by insulating system and designing automatic water heater

The most suitable temperature range for domestic purposes is about 200C to 260C .Besides, both cold and hot water appear to be essential frequently for industrial purposes. In summer bringing down the water temperature at a comfortable range causes significant energy consumption. This project aims at saving energy to control water temperature by making water tank insulated .Therefore applying better insulation system which would reduce the disparity between the desired temperature and the actual temperature and hence saving energy significantly. Following the investigation, this project used cotton jacket to insulate the tank and the tank was placed under a paddy straw shade with a view to attaining the maximum energy saving. Finally, it has been found that reduction in energy consumption is to be about 50-60% which is quite satisfactory. Since comfortable temperature range varies from person to person this project thus combines insulating effect with automatic water heater