Cost Per Watt Research Articles

Assessment of Wind Power Potential Based on Raleigh Distribution Model: An Experimental Investigation for Coastal Zone

When compared with other renewable energy resources (RER), the wind energy share in the global energy production is increasing rapidly. Currently, the Government of Pakistan (GoP) is moving towards RER, specifically wind and solar energy. In this paper, the wind energy potential of Tando Ghulam Ali, Sindh, Pakistan is explored. For this purpose, one-year wind speed data is considered at various heights through various probability distribution functions (PDFs). Statistical comparison of Rayleigh, gamma, generalized extreme value (GEV) and lognormal PDFs have been done with two methods, namely root mean square error and (R^2) in order to select the best PDF. Results showed that the Rayleigh distribution function is the best at the above mentioned area for finding various factors like site selection and wind power cost per kWh.

Optimal scheduling strategy of district integrated heat and power system with wind power and multiple energy stations considering thermal inertia of buildings under different heating regulation modes

Utilizing multiple energy supply solutions and the thermal inertia of buildings are considered as an efficient method for improving energy conservation and the operational flexibility of Combined Heat and Power (CHP) for wind power integration in a district integrated heat and power system (DIHPS). However, to truly take advantage of these, many factors such as the energy price, the variable efficiency of devices, and especially the different heating regulation modes (the quantity regulation and the quality regulation mode) are imperative to be considered for variable situations of the practical project. Therefore, in this paper, an integrated hydraulic-thermal model of the district heating network (DHN) under the quantity regulation mode is introduced, and a novel thermal energy flow model with transmission time delay under the quality regulation mode is firstly proposed to simulate the dynamic thermal energy distribution of the DHN with multiple heat sources. Then, in terms of different heating regulation modes, the different thermal capacity of buildings to increase the flexibility of the DIHPS is studied. Moreover, an optimal scheduling method considering different energy stations and the thermal inertia of buildings under different heating regulation modes is proposed to guide the operation of the DIHPS in variable actual engineering applications for the sake of operational economics and wind power utilization. Finally, numerical cases have been compared based on a modified testing system. The results demonstrate that under the quantity regulation mode the coordination of energy stations effectively reduces the daily operation cost by 17.4%. The thermal inertia of buildings give a saving rate of 6.4% and he penalty cost of wind power is reduced by 36.3% further. Moreover, the total thermal capacity of buildings to reduce the operation cost and the wind power curtailment is less under the quality regulation mode. It results that the daily operation cost increases by 4.1%. In addition, towards the DIHPS with multiple energy stations in our case, the thermal inertia of pipes cloud not reduce the daily operation cost.

Dynamic Multi-Objective Dispatch Considering Wind Power and Electric Vehicles With Probabilistic Characteristics

Wind power and electric vehicles (EVs) can provide a clean environment for power systems; however, there are challenges in objectively evaluating the economic value of power dispatching. In view of these challenges, a multi-objective dynamic dispatching model of wind power and EVs combined with stochastic characteristics is constructed in this study. The proposed model considered the uncertain output cost of wind power as well as the characteristics of cluster control charging and discharging after the construction of a refined electric vehicle model. An improved MOEA/D algorithm is applied to correct problems in the proposed model. The rationality and validity of the proposed model were verified through joint dispatch analysis of wind power and EVs.

The behavior strategies between the government and power generation enterprises considering the learning mechanism based on evolutionary game

The Renewable Portfolio Standard (RPS) as a policy tool to promote renewable energy development has gone through more than ten years in China. In order to research the strategic interaction between governments and power generation enterprises under the background of energy system transformation and upgrading, a learning mechanism was introduced based on the dynamic reward and punishment mechanism, and an evolutionary game model between the government and power generation enterprises was established. The results showed that the evolutionary stability strategy depended on the dynamic reward and punishment mechanism, which is conducive to the gradual stability of the system. The existence of learning mechanism not only reduced the cost of wind power, but also reduced the probability of government supervision.

Multi-Objective Economic Dispatch of Cogeneration Unit with Heat Storage Based on Fuzzy Chance Constraint

With the increasing expansion of wind power, its impact on economic dispatch of power systems cannot be ignored. Adding a heat storage device to a traditional cogeneration unit can break the thermoelectric coupling constraint of the cogeneration unit and meet the economic and stable operation of a power system. In this paper, an economy-environment coordinated scheduling model with the lowest economic cost and the lowest pollutant emissions is constructed. Economic costs include the cost of conventional thermal power generating units, the operating cost of cogeneration units, and the operating cost of wind power. At the same time, green certificate costs are introduced into the economic costs to improve the absorption of wind power. Pollutant emissions include SO2 and NOx emissions from conventional thermal power units and cogeneration units. The randomness and uncertainty of wind power output are fully considered, and the prediction error of wind power is fuzzy treated according to the fuzzy random theory, and the electric power balance and spinning reserve fuzzy opportunity conditions are established, which are converted into the explicit equivalent. The improved multi-objective particle swarm optimization (MOPSO) was used to solve the model. With this method, the validity of the model is verified by taking a system with 10 machines as an example.

Integrated Day-Ahead Scheduling Considering Active Management in Future Smart Distribution System

Day-ahead scheduling has played a significant role in the operation of distribution systems, aiming at minimizing the total operation cost. With the excessive integration of information and communication technologies and intelligent electronic devices, distribution system operators may seek to optimally control the active management elements to increase the economic and technical performance of future smart distribution systems. This paper focuses on an integrated day-ahead scheduling scheme that is formulated as a mixed integer second-order cone programming problem to obtain the optimal solution by means of the relaxed power flow model (RPFM). The detailed technical constraints for all the elements are accommodated based on the RPFM-based optimization method. Meanwhile, active management cost and punishment cost of wind power curtailed and customer energy not supplied are also considered in the design objectives of this paper. In order to address the uncertainties, a stochastic robust optimization method is first introduced to decide the active management elements (including capacitor bank, electrical storage system, controllable load, and switch) as the robust decision scheme. Afterwards, the column-and-constraint generation algorithm is applied to solve the proposed stochastic robust two-stage optimization model. Numerical results based on the IEEE 33-bus, PG&E 69-bus, and practical 152-bus systems are obtained to verify the effectiveness of the proposed method.

In Situ Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for Cu(In,Ga)Se2 Solar Cells.

The levelized cost of electricity (LCOE) of photovoltaic (PV) systems is determined by, among other factors, the PV module reliability. Better prediction of degradation mechanisms and prevention of module field failure can consequently decrease investment risks as well as increase the electricity yield. An improved knowledge level can for these reasons significantly decrease the total costs of PV electricity. In order to better understand and minimize the degradation of PV modules, the occurring degradation mechanisms and conditions should be identified. This should preferably happen under combined stresses, since modules in the field are also simultaneously exposed to multiple stress factors. Therefore, two 'Combined Stress test with in situ measurement' setups have been designed and constructed. These setups allow the simultaneous use of humidity, temperature, illumination, and electrical biases as independently controlled stress factors on solar cells and minimodules. The setups also allow real-time monitoring of the electrical properties of these samples. This protocol presents these setups and describes the experimental possibilities. Moreover, results obtained with these setups are also presented: various examples about the influence of both deposition and degradation conditions on the stability of thin film Cu(In,Ga)Se2 (CIGS) as well as Cu2ZnSnSe4 (CZTS) solar cells are described. Results on the temperature dependency of CIGS solar cells are also presented.

<em>In Situ</em> Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for Cu(In,Ga)Se<sub>2</sub> Solar Cells

The levelized cost of electricity (LCOE) of photovoltaic (PV) systems is determined by, among other factors, the PV module reliability. Better prediction of degradation mechanisms and prevention of module field failure can consequently decrease investment risks as well as increase the electricity yield. An improved knowledge level can for these reasons significantly decrease the total costs of PV electricity. In order to better understand and minimize the degradation of PV modules, the occurring degradation mechanisms and conditions should be identified. This should preferably happen under combined stresses, since modules in the field are also simultaneously exposed to multiple stress factors. Therefore, two 'Combined Stress test with in situ measurement' setups have been designed and constructed. These setups allow the simultaneous use of humidity, temperature, illumination, and electrical biases as independently controlled stress factors on solar cells and minimodules. The setups also allow real-time monitoring of the electrical properties of these samples. This protocol presents these setups and describes the experimental possibilities. Moreover, results obtained with these setups are also presented: various examples about the influence of both deposition and degradation conditions on the stability of thin film Cu(In,Ga)Se2 (CIGS) as well as Cu2ZnSnSe4 (CZTS) solar cells are described. Results on the temperature dependency of CIGS solar cells are also presented.

Optimal Dispatch of Microgrid with Combined Heat and Power System Considering Environmental Cost

With the rapid development of wind power generation and photovoltaic power generation, the phenomenon of wind and solar abandoning becomes more and more serious in the operation of power systems, and the microgrid is a new operating mode of power systems which provides a new consumption mode for wind power generation. With the increasingly close connection among energy resources and people’s increasing awareness of environmental protection, this paper establishes a microgrid optimal scheduling model with a combined heat and power system, in consideration of environmental costs. This model aims at the lowest comprehensive cost, at the same time taking into account the emission reductions of SO2 and NOx, considering the cost of power generated by the micro-generator, environmental cost, the related cost of battery, operation and maintenance cost of wind power, and photovoltaic power generation. The related constraints of thermal balance and power balance are also considered during microgrid system operation. The established model is solved with an improved particle swarm algorithm. At last, taking a microgrid system as an example, the validity and reliability of the proposed model are verified.

A Hybrid Bat Algorithm for Economic Dispatch With Random Wind Power

We present a hybrid metaheuristic optimization algorithm for solving economic dispatch problems in power systems. The proposed algorithm, based on bat algorithm, combines chaotic map and random black hole model together. Chaotic map is used to prevent premature convergence, and the random black hole model is helpful not only in avoiding premature convergence, but also in increasing the global search ability, enlarging exploitation area and accelerating convergence speed. The pseudocode and related parameters of the proposed algorithm are also given in this paper. Different from other related works, the costs of conventional thermal generators and random wind power are both included in the cost function because of the increasing penetration of wind power. The proposed algorithm has no requirement on the convexity or continuous differentiability of the cost function, although the effect on fuel cost, caused by the underestimation and overestimation of wind power, is included. This makes it feasible to take more practical nonlinear constraints into account, such as prohibited operating zones and ramp rate limits. Three test cases are given to illustrate the effectiveness of the proposed method.

The economic value of imports of combustible waste in systems with high shares of district heating and variable renewable energy

This study analyses the socio-economic value of trade of combustible waste, taking Denmark as an example for importing countries with large district heating networks and already high shares of variable renewable energy. An integrated systems analysis framework allowed to assess under which circumstances import of wastes leads to less expensive waste management and energy, accounting for increasing ambitions for a circular economy and renewable energy. The dynamics of both systems are captured through two optimization models, which are solved simultaneously. OptiFlow optimizes Danish waste management and transport, and Balmorel, the Northern European energy system.Results show that waste import to cover the existing Danish incineration overcapacity during wintertime has definite economic value. Conversely, summertime import can have negative value unless a gate fee is received, with the exception of imports of waste with high calorific content (>16.2 GJ/t). In some cases, mothballing of up to 14% of the existing incineration plants is a cost-efficient alternative to decrease the level of over-capacity. In the longer term, results show a socio-economic value of importing waste, being mainly sensitive to assumptions regarding biomass prices and wind power cost, as the technologies would compete with incineration plants.The present methodology can be applied to other countries where waste-to-energy participates in district heating, and where variable renewable electricity and constraints on biomass resources are becoming important. A pan-regional approach regarding waste management planning to maximize the value from combustible waste might be desired, along with a coherent taxation to avoid competition based on tax differences.

Demand-Pull Instruments and the Development of Wind Power in Europe: A Counterfactual Analysis

Renewable energy technologies are called to play a crucial role in the reduction of greenhouse gas emissions. Since most of these technologies did not yet reach grid parity, public policies have been implemented in order to foster their deployment. The approach that has been privileged in Europe is the demand-pull approach that aims at creating a demand for these new technologies and at stimulating their diffusion. This paper examines the effect of demand-pull policies on the diffusion of onshore wind power technology in six European countries: Denmark, France, Germany, Italy, Portugal and Spain. In a first step, a micro-founded model of diffusion is calibrated in order to replicate the observed diffusion of wind power in these six countries. In a second step, a counterfactual analysis is conducted by investigating several scenarios. By taking into account the complex self-sustained dynamics of diffusion and the learning spillovers that operate in the wind power sector, we can derive several insights about demand-pull policies. First, the impact of a demand-pull policy on the diffusion of wind power is determined by the stage at which it comes to support it. The effect seems to be stronger at the beginning of the diffusion. Second, international spillovers do operate in the wind power sector. These international spillovers however are not strong enough to foster the diffusion of wind power in a country having no demand-pull support. We can derive from these two statements that a strategy consisting in not implementing any demand-pull policy, with the expectation that international spillovers will reduce the cost of wind power and foster the diffusion of the technology that then shall become competitive, is not a good option for a country targeting a high share of wind power in its energy mix.

Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources

Nowadays, there is a growing interest in the microgrid systems with a high penetration of renewable sources. In this paper, the modified harmony search (MHS) algorithm is proposed to solve the combined economic emission dispatch (CEED) problem of the microgrid taking into account the solar and wind power cost functions. The proposed algorithm can be derived by not only adjusting the parameters but also improving the structure and operation of the original harmony search (HS) algorithm. The solution of the CEED problem of the microgrid taking into account the solar and wind power cost functions is obtained for different scenarios using the MHS algorithm and some recently published algorithms. The results of all scenarios show the effectiveness of the MHS algorithm over other published algorithms employing same data.

An integrated approach for wind turbine gearbox fatigue life prediction considering instantaneously varying load conditions

Abstract Wind power is a significant clean energy source. Operation & maintenance (O&M) costs account for about 25% of the cost of wind power, and it is critical to improve the reliability of wind power generators to reduce the overall cost and increase wind power competitiveness comparing to other power sources. Wind turbines are subject to instantaneously varying load due to wind turbulence, which challenges the prognostic study for predicting equipment future health conditions and remaining useful lives. With existing prognostics methods, the average constant load is typically used to approximate the varying external load. In this paper, an integrated varying-load approach is proposed for predicting wind turbine gearbox remaining useful life by specifically considering instantaneously varying external load, which is more realistic. Fatigue crack damage is focused on. The method integrates gear physical models and available health condition data, and the distribution of uncertain material parameter modeled in crack degradation process is updated via Bayesian inference once new health condition data become available. Examples are provided to demonstrate the effectiveness of the proposed varying-load approach. A comparative study is conducted between the proposed approach and existing constant-load approximation method, and the results show that the proposed varying-load approach can provide more accurate prediction.

Selection of optimal access point for offshore wind farm based on multi-objective decision making

This paper analyzes the problem of selecting the optimal access point in power grid for the offshore wind farm (OWF), which is increasingly integrated into the onshore power system by use of voltage-source converter based high voltage direct current (VSC-HVDC) transmission. The development of the selecting method includes three steps. First, three major factors, which have significant impacts on deciding the optimal location of the onshore VSC, are introduced, i.e., voltage support from onshore VSCs, voltage fluctuation caused by the change of wind power and construction costs of the VSC-HVDC transmission system. Secondly, three evaluation indexes that are corresponding to the three factors are put forward. Thirdly, in the face of this multi-objective programming problem, a linear weighted model is proposed in this paper and the comprehensive weight method based on the theory of information entropy and the analytic hierarchy process (AHP) method is adopted to get the weight coefficients. The method is carried out in a practical power system in China. The results demonstrate that the proposed methodology is an effective way for selecting the optimal access point of the OWF.

From the Lab to Scaling-up: Case Studies of Electrodeposition Processes in the Photovoltaic Industry

Photovoltaic (PV), with more than 300 GW of cumulative capacity installed by the end of 2016, represents about 1.5% of the world electricity production. It is now obvious that the growth of PV will not only continue but even accelerate, as a key player for the energy transition, reaching up about 5 TW by 2050, as projected by the International Energy Association. The main reason for this development is due to a reduction by 10 of PV electricity cost in ten years. This trend makes PV electricity competitive with classical fossil or nuclear electricity in many regions of the world. The decrease in cost has resulted from improvement in materials and methods, an increase in solar energy conversion efficiency and in volume production. Research and Development plays a major role in this process proposing innovation and scientific breakthroughs in existing PV technologies and introduction of new technologies. Scaling effects have played a key role in decreasing the production costs but further progress along with innovative technologies will be needed to lower costs. The comparison between thin film technologies and wafer based technologies is typical of this paradigm. Thin film technologies are basically coating technologies which are inherently better adapted for large area processing (thousands of km2) compared to slicing individual crystalline wafers and assembling them as a mosaic. However, any defect on a part of a large area process induces a huge impact on the whole panel where the slices of Silicon are sorted to produce module. Moreover, the cost reduction of the wafer technology with scaling and the industrial maturity of silicon technology is so rapid that this technology is cost leading. As a consequence, the PV industrial sector is dominated at more than 90% by Silicon solar cells. The remaining 10% is composed of vacuum based thin films. Electrodeposition, despite intrinsic advantages, with real success in industry with, among numerous other examples, damascene copper in semiconductor or permalloys in thin film head, is almost absent of this PV industrial landscape. However, introduction of plating will be easier and more probable for new cell technologies, where new investment has to be done and for which stringer requirements emerge. In this context, we will discuss and make some prospective about two case studies involving electrodeposition in PV: plating contacts on Silicon and Cu-In-Ga based plating for thin films solar cells. On Silicon PV market, Copper represents an alternative to Silver screen printing. Copper has a much lower price than Silver with an equivalent bulk resistivity. Interdigited Back Contact (IBC) and Heterojonction (HJT) solar cells with Cu plating already exists for years. Nonetheless, Cu being a lifetime killer in c-Si, a Ni diffusion barrier is usually used. This approach has been demonstrated for front side metallization, based on Light Induced Plating. The case of emerging bifacial solar cells will be specifically discussed with the use of Ni/Cu or Ni/Ag plating. The remaining challenges will be discussed, including specificity of plating on both sides simultaneously, surface roughness issue and his impact on adhesion, ghost plating linked to surface passivation defects. For producing thin film solar cells, an alternative to vacuum based deposition methods (co evaporation, sputtering), which are presently used, is to use electrodeposition or printing. We will make a comprehensive description of the scale-up of the electrodeposited CIGS precursor layers from the laboratory scale of a rotating disk electrode to a full-size 60 cm x 120 cm compatible with 1 m2/min production of solar panels. More specifically, we will discuss the different fabrication approaches for electrodeposited precursor CIGS materials, development and recycling of solution chemistries for Copper, Indium and Gallium. Resulting fabrication of solar cells will be described. We will also present applications and devices which specifically take advantage from electrodeposition approach that is localized deposition on patterned substrate. The specific mechanism of electrodeposition in microelectrode array configuration and the challenge of upscaling will be discussed. References L. Tous et al, Energy Procedia 124, 922–929 (2017). Q. Huang, et al, Journal of The Electrochemical Society, vol. 158, issue 2, 2011, D57-D61 P.-P. Grand et al, WO 2012/052657 C. Broussillou et al, IEEE, New Orleans (2015) A. Duchatelet et al, Applied Physics Letters, 109 (2016), 253901

Carbon Price in China: A CO2 Abatement Cost of Wind Power Perspective

ABSTRACTAs a result of rapid development of industrialization and urbanization, energy (especially fossil fuels) demand growth is increasing. Hence, China is facing the huge pressure of environmental protection and CO2 emission reduction. The feed-in tariff (FIT) policy that promotes more wind power to substitute for thermal power and a well-functioning carbon price mechanism can significantly affect CO2 abatement, and both can work in coordination to achieve emission reduction. Using panel model, we prove that FIT policy is more effective than other policies in promoting more wind power. Also the slowdown of economic growth, energy substitution, technological progress, and CO2 mitigation requirement can stimulate the expansion of wind power. Additionally, based on the calculation of real abatement cost of wind power, we obtain the provincial and national average of carbon prices (239 CNY/ton and 242 CNY/ton). Specifically, 233-251 CNY/ton will be the range for reasonable carbon price in the future. We find that the carbon prices in this article are higher than those of the emissions trading scheme pilots in 2014 and 2015, due to the relatively high proportion of free allowance. Based on the above conclusions, we proposed some policy suggestions.

The new power supply!

Thanks to many qualified authors, Energy Science and Engineering has contained papers of good quality and on relevant topics during the past year. When 2017 started, we had seen the falling costs of solar and offshore wind power during the preceding year. Many of the technologies and systems issues then identified have been addressed in the in the journal. During 2017, industrial development has progressed further. We have seen procurement of offshore wind by Germany resulting in winning bids, offering to produce electricity without any subsidies. But the most remarkable news came from Saudi Arabia, where solar power was offered at 1.79 US¢ per kWh. While it was possible a year ago, to say that new renewable sources of electricity could outcompete any other kind of new power plant, we are about to reach the point where new solar and wind plants provide cheaper electricity than existing thermal plants. This will speed up the transition. But when doing so, opportunities to utilize the characteristics of the new power supply will come fast as well. Electricity-intensive industries may maximize their competitiveness by power price-optimizing strategies, departing from traditional continuous operation process technologies. There is increased use of power control techniques automatically managing any electricity consumption in relation to real-time price information. New developments of microgrid, storage, and direct current technologies are finding customers as disconnecting from large electricity grids becomes economically feasible and often in demand before that solution is really economically superior. As the supply of solar and wind electricity has become cheaper, many have started to disregard energy efficiency options. This is a mistake for at least three reasons: First, energy-efficient technologies have developed fast, too. The obvious example is that while solar photovoltaic technologies making light into electricity have developed, light-emitting diodes, making electricity into light, have demonstrated improved efficiency and falling costs. Sometimes, the development is faster than the implementation so that the economic efficiency potential is actually increasing. Second, when looking for ways to adapt to fluctuating availability of solar and wind power, traditional energy efficiency measures often appear as cost-efficient options to minimize system costs. Finally, lower cost electricity has made electrification competitive with fuel-based systems, almost always providing higher energy efficiency and better controllability at the same time. No doubt, Energy Science and Engineering has a wide range of topics to cover during this period of rapid progress. The ambition is to contribute to the rapid transfer of science into industrial engineering and utilization. To this end, being an open-access journal is a vital feature. Global, immediate access for anybody with Internet is avoiding many barriers previously delaying implementation. With its first impact factor of 2.172, this should be more attractive than ever!

A capacity-investment model of wind power with uncertain supply-price under high penetration rate

Abstract With the rapid development of renewable energy, the proportion of wind power in power supply has grown significantly. Also, it influences the power price fluctuation. Since the marginal cost of wind power is almost zero, the growth of wind power's penetration rate has led to a crowding-out effect and challenged traditional power generation technology, substantially reducing the power price in the market. In perfect competition market, the real-time balance between supply and demand of power is regulated by the real-time power price fluctuation. So this paper models the intermittence of wind power as uncertain supply, and develops a capacity-investment model under the uncertainties of both supply and demand. We introduce priority dispatch elasticity to describe the crowding-out effect and take the power price to be endogenous in order to model the situation of high penetration rate. We compare the optimal wind power capacity decision under the strategy of priority grid connection and abandoned power management. Our results show that optimal capacity investment is inversely related to priority dispatch elasticity under both strategies. However, the profit from power generation is always higher when adopting the abandoned power management strategy.

Simulation and Feasibility Studies of Rooftop PV System for University Campus Buildings in Surabaya, Indonesia

Present work simulates and analyzes the rooftop photovoltaic (PV) system on buildings roofs of the University of Surabaya, Indonesia for electricity power generation. The work also to calculate greenhouse gas (GHG) emission reduction that can be obtained by PV system mounted on the building roofs. The surface area of the roofs was determined using Polygon feature of Google Earth TM . The energy output of the system was simulated with SolarGIS pvPlanner software program. The grid-connected PV system type was chosen in the simulation. Greenhouse gas (GHG) emission reduction analysis was carried out using RETScreen program simulation. It was found that about 10,353 m 2 of the rooftop of the university buildings could be used for panel installation. The total capacity of the panels is found about 2,070 kWp with total electricity production is about 3,180 MWh per year and could supply up to 80% of the campus energy demand. The system would serve as a means of reducing 3,367.6; 2,477.2, or 1,195.7 tons of CO 2 to the atmosphere in comparison to the same amount of electricity produced by burning coal, oil, or natural gas respectively. The unit cost of PV electricity was found ranging from 0.10 – 0.20 USD/kWh. From economic aspects, the rooftops PV system has the potential to provide power at a competitive cost in comparison to other alternative options of power generation.