Triple-objective optimal sizing based on dynamic strategy for an islanded hybrid energy microgrid

A triple-objective optimal sizing method based on a dynamic strategy is presented for an islanded hybrid energy microgrid, consisting of wind turbine, solar photovoltaic, battery energy storage system and diesel generator. The dynamic strategy is given based on a dynamic complementary coordination between two different master-slave control modes for maximum renewable energy utilization. Combined with the proposed strategy, NSGA-II-based optimization program is applied to the sizing optimization problem with triple different objectives including the minimization of annualized system cost, the minimization of loss of power supply probability and the maximization of utilization ratio of renewable energy generation. The sizing results and the proposed strategy are both compared and analyzed to validate the proposed method in a real case of an islanded hybrid energy microgrid on Dong’ao Island, China.     

Sizing and performance analysis of standalone hybrid photovoltaic/battery/hydrogen storage technology power generation systems based on the energy hub concept

In this study, the optimal sizing and performance analysis of a standalone integrated solar power system equipped with different storage scenarios to supply the power demand of a household is presented. One of the main purposes when applying solar energy resource is to face the increasing environmental pollutions resulting from fossil fuel based electricity sector. To this end, and to compare and examine two energy storage technologies (battery and hydrogen storage technology), three storage scenarios including battery only, hydrogen storage technology only and hybrid storage options are evaluated. An optimization framework based on Energy Hub concept is used to determine the optimum sizes of equipment for the lowest net present cost (NPC) while maintaining the system reliability. It was determined that the most cost effective and reliable case is the system with hybrid storage technology. Also, the effects of solar radiation intensity, the abatement potential of CO₂ emissions and converting excess power to hydrogen on the system’s performance and economics, were investigated and a few noticeable findings were obtained.     

Thermoeconomic installation limit of PV/WT hybrid energy systems for Off-grid islands

An ideal off-grid island can become 100% energy-sufficient if one installs renewable energy systems such as solar photovoltaic (PV) and wind turbine (WT) systems. However, the intermittent and uncertain nature of the power supply from renewable energy systems hinders a 100% autonomy level (AL) without an infinite energy storage capacity. The thermoeconomic installation limit (TEIL) of a PV/WT hybrid energy system was studied using hourly weather data and the energy demand profile for off-grid islands. An appropriate battery size for the TEIL was also determined. Given the current installation cost of the hybrid energy system and the battery unit, the AL for a PV/WT hybrid energy system at the TEIL is calculated to be approximately 70%. Above the limit, the size of the energy storage unit and, correspondingly, the total annual cost of the PV/WT hybrid energy system increase sharply.     

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.     

Higher-efficiency for combined photovoltaic-thermoelectric solar power generation

Solar energy application in a large spectrum has the potential for high-efficiency energy conversion. Though, solar cells can only absorb photon energy of the solar spectrum near their band-gap energy, and the remaining energy will be converted into thermal energy. The use of the thermoelectric generator becomes a necessity for convert this thermal energy dissipated so as to increase efficiency conversion.

This paper analyses the feasibility of photovoltaic-thermoelectric hybrid system and reviews their performance in order to optimize harvested energy. Regarding the thermoelectric effect, a new method of the ambient energy harvesting is presented. This method combines thermoelectric generators and the effects of heat sensitive materials associated to photovoltaic cells in phase change for generating both energy day and night. Experimental measures have been conducted primarily in laboratory conditions for a greater understanding of hybridization phenomena under real conditions and to test the actual performance of devices made. Results show that the hybrid system can generate more power than the simple PV and TEG in environmental conditions. This hybrid technology will highlight the use of renewable energies in the service of the energy production.     

Comparative study on performances of a heat-pipe PV/T system and a heat-pipe solar water heating system

The heat-pipe solar water heating (HP-SWH) system and the heat-pipe photovoltaic/thermal (HP-PV/T) system are two practical solar systems, both of which use heat pipes to transfer heat. By selecting appropriate working fluid of the heat-pipes, these systems can be used in the cold region without being frozen. However, performances of these two solar systems are different because the HP-PV/T system can simultaneously provide electricity and heat, whereas the HP-SWH system provides heat only. In order to understand these two systems, this work presents a mathematical model for each system to study their one-day and annual performances. One-day simulation results showed that the HP-SWH system obtained more thermal energy and total energy than the HP-PV/T system while the HP-PV/T system achieved higher exergy efficiency than the HP-SWH system. Annual simulation results indicated that the HP-SWH system can heat the water to the available temperature (45°C) solely by solar energy for more than 121 days per year in typical climate regions of China, Hong Kong, Lhasa, and Beijing, while the HP-PV/T system can only work for not more than 102 days. The HP-PV/T system, however, can provide an additional electricity output of 73.019 kWh/m², 129.472 kWh/m², and 90.309 kWh/m² per unit collector area in the three regions, respectively.     

Investigation of the effects of battery types and power management algorithms on drive cycle simulation for a range-extended electric vehicle powertrain

Fuel cell (FC) hybrid vehicle power trains are an attractive technology especially for automotive applications because of their higher efficiency and lower emissions compared to conventional vehicles. This study focuses on the design of an FC hybrid power train system and evaluation of its simulations for a given speed profile through two alternative power management algorithms (PMAs). Parameters suitable for a small vehicle were taken into consideration in the mathematical model of the vehicle. The proposed hybrid power train consists of an energy storage system, composed of a 4-kg battery pack (either lithium-ion (Li-ion) battery, nickel metal hydride, or nickel–cadmium) and a direct methanol fuel cell (DMFC) as the range extender. The PMAs basically aim to fulfill the power requirements of the vehicle and decide how to command the power split between the battery and the FC. The model comprising a DMFC, a battery, and PMAs was developed in MATLAB/Simulink environment. The polarization curve of the FC was obtained using a one-dimensional DMFC model. Vehicle power requirements for a drive cycle were calculated using the equations of longitudinal dynamics of vehicle, and the results were integrated into MATLAB/Simulink model. As a result of the simulations, methanol consumption, state of charge of the battery, and power output of the FC were compared for the PMAs. This comparison shows the effect of PMAs on the hybrid vehicle performance for three battery types. The results indicate that the vehicle range could be increased when proper strategy is used as PMA.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Performance of a diesel engine with water emulsified diesel prepared with optimized process parameters

An attempt has been made to produce stable water–diesel emulsion with optimal formulation and process parameters and to evaluate the performance and emission characteristics of diesel engine using this stable water–diesel emulsion. A total of 54 samples were prepared with varying water/diesel ratio, surfactant amount and stirring speed and water separation was recorded after 24 and 48 hr of emulsification. The recorded data were used in artificial neural network (ANN)-particle swarm optimization (PSO) technique to find the optimal parameters to produce water–diesel emulsion for engine testing. The predicted optimal parameters were found as 20% water to diesel ratio, 0.9% surfactant and 2200 rpm of stirrer for a water separation of 14.33% in one day with a variation of 6.54% against the actual value of water separation. Water–diesel emulsion fuel exhibited similar fuel properties as base fuel. The peak cylinder gas pressure, peak pressure rise rate and peak heat release rate for water–diesel were found higher as compared to diesel at medium to full engine loads. The improved air-fuel mixing in water–diesel emulsion enhanced brake thermal efficiency (BTE) of engine. The absorption of heat by water droplets present in water–diesel emulsion led to reduced exhaust gas temperature (EGT). With water–diesel emulsion fuel, the mean carbon monoxide (CO), unburned hydrocarbon and oxides of nitrogen (NO_x) emissions reduced by 8.80, 39.60, and 26.11%, respectively as compared to diesel.     

Accurate power-sharing,voltage regulation,and SOC regulation for LVDC microgrid with hybrid energy storage system using artificial neural network

ABSTRACT

In this paper, an artificial neural network-based control strategy is proposed for low voltage DC microgrid (LVDC microgrid) with a hybrid energy storage system (HESS) to improve power-sharing between battery and supercapacitor (SC) to suit the demand-generation imbalance, maintain state-of-charge (SOC) within boundaries and thereby to regulate the dc bus voltage. The conventional controller cannot track the SCs current rapidly with the high-frequency component that will place dynamic stress on the battery, further resulting in shorter battery life. The significant advantage is that in the proposed control strategy, redirections of unwaged battery currents to SCs for fast compensations enhance battery life span. The proposed control strategy effectiveness was investigated by simulations, including a comparison of overshoot/undershoot and settling time in dc bus voltage with a conventional control strategy. The results have been experimentally verified by hardware-in-loop (HIL) on a field-programmable gate array (FPGA)-based real-time simulator.     

HYDROLOGIC IMPACTS OF ALTERNATIVE APPROACHES TO STORM WATER MANAGEMENT AND LAND DEVELOPMENT1

Low impact development (LID) and other land development methods have been presented as alternatives to conventional storm water management and site design. Low impact development encourages land preservation and use of distributed, infiltration‐based storm water management systems to minimize impacts on hydrology. Such systems can include shallow retention areas, akin to natural depression storage. Other approaches to land development may emphasize land preservation only. Herein, an analysis of four development alternatives is presented. The first was Traditional development with conventional pipe/pond storm water management and half‐acre lots. The second alternative was Cluster development, in which implementation of the local cluster development ordnance was assumed, resulting in quarter‐acre lots with a pipe/pond storm water management system and open space preservation. The “Partial” LID option used the same lot layout as the Traditional option, with a storm water management system emphasizing shallow depression storage. The “Full” LID used the Cluster site plan and the depression storage‐based storm water management system. The alternatives were compared to the hydrologic response of existing site conditions. The analysis used two design storms and a continuous rainfall record. The combination of land preservation and infiltration‐based storm water management yielded the hydrologic response closest to existing conditions, although ponds were required to control peak flows for the design storms.     

Optimal Design Methods for Hybrid Renewable Energy Systems

Renewable and hybrid energy systems (HESs) are expanding due to environmental concerns of climate change, air pollution, and depleting fossil fuels. Moreover, HESs can be cost effective in comparison with conventional power plants. This article reviews current methods for designing optimal HESs. The survey shows these systems are often developed on a medium scale in remote areas and stand-alone, but there is a global growing interest for larger scale deployments that are grid connected. Examples of HESs are PV–wind–battery and PV–diesel–battery. PV and wind energy sources are the most widely adopted. Diesel and batteries are often used but hydrogen is increasing as a clean energy carrier. The design of an efficient HES is challenging because HES models are nonlinear, non-convex, and composed of mixed-type variables that cannot be solved by traditional optimization methods. Alternatively, two types of approaches are typically used for designing optimal HESs: simulation-based optimization and metaheuristic optimization methods. Simulation-based optimization methods are limited in view of human intervention that makes them tedious, time consuming, and error prone. Metaheuristics are more efficient because they can handle automatically a range of complexities. In particular, multi-objective optimization (MOO) metaheuristics are the most appropriate for optimal HES because HES models involve multiple objectives at the same time such as cost, performance, supply/demand management, grid limitations, and so forth. This article shows that the energy research community has not fully utilized state-of-the-art MOO metaheuristics. More recent MOO metaheuristics could be used such as robust optimization and interactive optimization.     

Techno-economic and environmental analysis of an integrated standalone hybrid solar hydrogen system to supply CCHP loads of a greenhouse in Iran

The techno-economic and environmental performance of hybrid solar hydrogen energy systems was investigated to provide combined cooling, heating and power (CCHP) demands of a standalone greenhouse in Iran to achieve sustainable agriculture based on an optimization procedure. From the environmental point of view, by deploying hybrid energy systems, 83%, to 100% of emissions can be avoided. Also a sensitivity analysis was performed on the hybrid energy systems in order to study the effect of major parameter variation on the systems justification. It was concluded that hybrid solar systems are economically competitive with conventional systems, for high solar intensity locations with high diesel fuel prices and decreased prices for PV and hydrogen storage technology.     

Electrification of rural areas by solar PV

More than 2000 million people, mostly in developing countries, live in rural areas without access to grid connected power. Conventional approaches to supplying power, whether through extension of existing grids or through stand-alone 'minigrids' based on diesel generator sets, or even on renewable energy minigrids, require large investments which are unlikely to receive priority in competition with more economically and politically attractive investments in urban areas. Domestic PV lighting and broadcast reception kits (DLKs), comprising, typically, a 30–60 W panel, an automotive battery, a charge indicator, and dc fluorescent lamps can be furnished and installed for about $500. DLKs are now used in the Dominican Republic, Kenya, Sri Lanka and many other countries. DLKs provide a minimum essential service with low overheads. Given the necessary credit facilities, they can give better service at comparable costs in comparison with kerosene lamps and dry cell powered radios. They also permit a substantial degree of local manufacture, thus saving on foreign exchange. This movement is starting in many countries on a purely commercial basis. The process could be greatly accelerated if 'seed money' in the form of revolving funds could be made available.     

Analysis of Feedstock Supply Costs for Wood-fired Electric Power Plants in Liberia, West Africa

In Liberia, as in many developing countries, electrification of towns and cities throughout the country has long been a major development goal. However, fuel expenditures by the Liberian Electricity Corporation (LEC) for its rural public stations represent a major and growing burden on the financially hard-pressed utility. In this paper we evaluate the economics of supplying wood to rural electric power plants utilizing different sources of feedstock. We also evaluate the cost implications of differences in wood supply requirements based on the use of steam or gasifier technology, and from variation in plant utilization level.
The wood supply we consider as sources are: (1) retired rubber trees; (2) the harvesting of secondary-growth forest just before the land is returned to temporary cultivation; (3) the establishment of commercial short-rotation wood energy plantations; and (4) adding to the system of shifting agriculture the planting of fast-growing wood species. The results indicate that wood can probably be supplied under a wide range of supply and demand conditions for US$1.00–1.70 per GJ. We estimate that wood steam plants can generate power for about $0.09-0.14 per kWh and gasifier plants for $0.10-0.18 per kWh. These costs are well below the present cost of oil-based rural electric power generation in Liberia (about $0.20–0.27 per kWh).     

A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.     

Conditions for a 100% renewable energy supply system in Japan and South Korea

In the wake of the Fukushima nuclear accident, alternative energy paths have been discussed for Japan, but except for a few studies the assumption is usually made that Japan is too densely populated to be suited for a near-100% sustainable, indigenous energy provision. The studies emphasizing renewable energy have proposed the use of photovoltaic power as the main source of electricity supply, in combination with diurnal battery storage and supplemented by other renewable sources such as wind, hydro, and geothermal power. Here, an alternative approach is explored, with wind and derived hydrogen production as the main energy source, but still using solar energy, biofuels, and hydropower in a resilient combination allowing full satisfaction of demands in all sectors of the economy, i.e., for dedicated electricity, transportation energy as well as heat for processes and comfort. Furthermore, the possible advantage of establishing a regional energy system with energy interchange and coordinated management of the mix of renewable energy resources across a wider region is discussed. As the closest neighbor, the energy system of South Korea is considered, first regarding the possibility of a similar full renewable energy reliance, and then for possible synergetic effects of connecting the Korean and the Japanese energy systems, in order to be able to better cope with the intermittency of renewable energy source flows.     

Processing of Straw/Corn Stover: Comparison of Life Cycle Emissions

The LCA emissions from four renewable energy routes that convert straw/corn stover into usable energy are examined. The conversion options studied are ethanol by fermentation, syndiesel by oxygen gasification followed by Fischer Tropsch synthesis, and electricity by either direct combustion or biomass integrated gasification and combined cycle (BIGCC). The greenhouse gas (GHG) emissions of these four options are evaluated, drawing on a range of studies, and compared to the conventional technology they would replace in a western North American setting. The net avoided GHG emissions for the four energy conversion processes calculated relative to a “business as usual” case are 830 g CO₂e/kWh for direct combustion, 839 g CO₂e/kWh for BIGCC, 2,060 g CO₂e/L for ethanol production, and 2,440 g CO₂e/L for FT synthesis of syndiesel. The largest impact on avoided emissions arises from substitution of biomass for fossil fuel. Relative to this, the impact of emissions from processing of fossil fuel, e.g., refining of oil to produce gasoline or diesel, and processing of biomass to produce electricity or transportation fuels, is minor.     

Effective application of ethanol in diesel engines

This work aimed to prove the effects of adding different proportions of ethanol with diesel (DE) and ethanol–water mixture with diesel (DEW) in a single-cylinder diesel engine on the performance, emissions, and combustion parameters. The blends were stabilized by tetra methyl ammonium bromide (TMAB) as the additive. The study was conducted at two operating conditions initially on a normal diesel engine and in the second case the engine piston, valves, and cylinder head coated with zirconia (ZrO₂) alumina (Al₂O₃). The results showed that the addition of 10% ethanol with diesel performed almost equivalent to neat diesel with 29.2% BTE and a 17.7% decrease in smoke and an 11.4% increase in NOx emission at peak load compared to that of the base fuel. Modified engines with thermal barrier coating (TBC) performed superior to normal engines with 4% and 5.5% increase in BTE, respectively, for DE- and DEW-type fuels with reduced exhaust emissions. A 5% addition of water with diesel–ethanol blends favors a higher proportion of ethanol to be employed in diesel engines.     

Multi-criteria PSO-based optimal design of grid-connected hybrid renewable energy systems

ABSTRACT

Human-induced climate change through the over liberation of greenhouse gases, resulting in devastating consequences to the environment, is a concern of considerable global significance which has fuelled the diversification to alternative renewable energy sources. The unpredictable nature of renewable resources is an impediment to developing renewable projects. More reliable, effective, and economically feasible renewable energy systems can be established by consolidating various renewable energy sources such as wind and solar into a hybrid system using batteries or back-up units like conventional energy generators or grids. The precise design of these systems is a critical step toward their effective deployment. An optimal sizing strategy was developed based on a heuristic particle swarm optimization (PSO) technique to determine the optimum number and configuration of PV panels, wind turbines, and battery units by minimizing the total system life-cycle cost while maximizing the reliability of the hybrid renewable energy system (HRES) in matching the electricity supply and demand. In addition, by constraining the amount of conventional electricity purchased from the grid, environmental concerns were also considered in the presented method. Various systems with different reliabilities and potential of reducing consumer’s CO₂ emissions were designed and the behavior of the proposed method was comprehensively investigated. An HRES may reduce the annualized cost of energy and carbon footprint significantly.