Low-cost Electricity Research Articles

Thermo-economic analyses of IGCC power plants employing warm gas CO2 separation technology

Integrated gasification combined cycle (IGCC) power plant with dual-stage Selexol™ for carbon capture is compared to pressure swing adsorption (PSA)-based warm gas CO2 capture. Capture with Selexol™ was limited to 83.4% due to high syngas CH4 content while the efficiency was 31.11% HHV resulting in a 1st year cost of electricity (COE) of 148.6 $/MWh. Carbon capture can be increased to 88.6% and efficiency to 33.76% HHV with warm gas CO2 removal. When holding the same carbon capture level as the Selexol™ case, efficiency is increased to 34.20% HHV and after further optimization of the water gas shift (WGS) reactors to 35.63% HHV leading to a lower COE of 127.2 $/MWh. Reaction kinetic models are developed and applied for optimization of WGS reactors to convert syngas CO to CO2. Cost for warm gas carbon capture reduced to 47.5 $/tonne from 66.0 $/tonne for IGCC without carbon capture while CO2 avoided cost reduced from 89.4 $/tonne to 54.3 $/tonne. Carbon capture cost dropped from 88.0 $/tonne to 72.7 $/tonne while the CO2 avoided cost decreased from 112.2 $/tonne to 78.3 $/tonne over supercritical boiler plant without carbon capture. Furthermore, warm gas cleanup lowered the specific net water withdrawal/usage by 13.4%.

Overview of U.S. Department of Energy Office of Fossil Energy’s Solid Oxide Fuel Cell Program for FY2019

The U.S. Department of Energy Office of Fossil Energy (FE) National Energy Technology Laboratory (NETL) Solid Oxide Fuel Cell (SOFC) Program is currently developing efficient, low-cost electricity from natural gas distributed generation applications in FY2019. The current program includes cell development and core technology research to increase the reliability, robustness, and durability of cell, stack, and system technology; and providing the technology base to permit cost-competitive distributed generation applications. The program is a unique balance of strategically oriented research and development activities spanning fundamental research to prototype testing. The SOFC Program collaborates and coordinates with other fuel cell programs government-wide, including ARPA-E and DOE EERE’s Hydrogen and Fuel Cell Office. The accomplishments of these activities, along with the status of the program’s integrated systems tests will be presented.

Treatment and Operating Cost Analysis of Textile Wastewater by Electro-coagulation Using Mild Steel Electrodes

Conventional treatment of industrial wastewater is often ineffective in removing color, especially from highly colored textile wastewater. This research was undertaken to investigate the removal of color and COD from textile effluent using electro-coagulation process. The effects of applied current flow, different types of electrodes, age of wastewater, EC time and initial pH on the removal of color and COD were studied. Cost estimation was also been assessed. Aluminium, mild steel and stainless steel plates were used as electrodes and comparison among these plates regarding the removal efficiencies assessed. Wastewater from two different textile industries were collected four times and treated in the laboratory. Under the experimental conditions, color removal up to 98%, COD removal up to 67% and turbidity removal up to 71.5% were achieved. The results suggest that electrocoagulation process is very effective for removal of color. It was observed that slightly low pH than initial would be effective for color and COD removal and low electricity cost. Considering economical and effectiveness of the treatment process the initial pH should be lowered about 1.6–2 than the raw sample. It was also observed that the removal of color was more effective when the experimental run using fresh sample rather than old sample. As metal decomposes in this process; mild steel was found to be more economical than aluminium. The operating cost includes the energy cost of EC and the material cost. Operating cost as 0.53 US $ m−3 at 5 ampere and 15 min EC time was evaluated.

Simulation of biogas utilization effect on the economic efficiency and greenhouse gas emission: a case study in Isfahan, Iran

Biomass is a type of renewable energy that, in despite of its potentials and advantages including simple production technology, decreasing environmental issues, and energy generation capacity at the consumption site, has not been sufficiently utilized in Iran. Since, due to statistics, Isfahan enjoys remarkable prospects in terms of wind, solar and biomass energies, a combined system of indigenous energy sources for powering a cattle farm has been investigated and evaluated in this study. To evaluate the possibility of the optimal system for comparative reasons, the HOMER software was used. The designed hybrid system was a wind-solar-biomass generator that used a battery saver as backup. Although it seems that wind and solar energies have the highest potential for energy generation in Isfahan, the results showed that biomass, by itself, can provide the required power for a cattle farm. In fact, biomass energy was more economically efficient than wind and solar energies. Owing to the low electricity cost, generated from fossil fuels, in Iran, relative to a large number of countries, the findings revealed that using biomass for generating the electricity of a cattle farm will compensate the expenses by the mid-15th year and will generate profit for 9.5 years later. The results also showed that the solar cell-based hybrid system is cheaper than the wind turbine-based one. Regarding the price of per kWh of electricity produced, the results showed that the biomass generator system with the price 0.12 $/kWh is the cheapest, and the solar cell-based and wind turbine-based hybrid systems are 3.33% and 10.83% more expensive, respectively. The results can be used for electricity generation with minimum pollution and expenses in the same regions. ©2019. CBIORE-IJRED. All rights reserved

Optimal Load Management in a Shipyard Drydock

With the proliferation of enabling smart grid technologies, industries are increasingly looking to reduce their electricity costs through the adoption of renewable energy sources and efficient load management strategies. In this context, the realization of lower electricity costs requires the design of efficient energy management systems (EMSs). An EMS needs to factor in the unique operational requirements of the industry for which it is designed. Consequently, there has been a lot of research interest in designing EMSs for various industrial applications. However, the existing EMS formulations and models are not suitable for a shipyard drydock. Shipyard drydocks may be treated as grid-connected microgrids containing pump loads, interruptible loads, critical loads and heterogeneous generation sources. This paper proposes three modules, which can constitute a shipyard drydock energy management system (SEMS). A load forecasting module generates short term and medium term load forecasts using historical load demand data and ship arrival schedules as inputs. A multilayer feed-forward neural network with backpropagation is used to perform the load forecasting. A contracted capacity optimization module uses the medium term load forecast to find the optimal contracted capacity for the drydock. The short term load forecast and the optimal contracted capacity are used by an optimal scheduling module to reduce the total electricity cost incurred by the shipyard drydock. Case studies performed using data from a local shipyard demonstrate the efficacies of the proposed load forecasting and optimal scheduling modules in improving the accuracies of the load forecasts and reducing the overall electricity cost, respectively.

Operation of a 50-kWth chemical looping combustion test facility under autothermal conditions

The United States Department of Energy is developing transformational fossil fuel combustion technologies that result in more efficient power cycles and/or substantial reductions in GHG emissions. Chemical Looping Combustion (CLC) has the potential to achieve a lower cost of electricity than a supercritical pulverized coal power plant with an amine absorption system. Although the concept and research on chemical looping has a long history, CLC has numerous technical issues that must be addressed prior to a commercial debut. This effort is directed toward the following major issues for CLC: (1) demonstrating continuous solids handling, operability, and reactor performance at autothermal conditions and (2) preliminary assessments of oxygen carrier attrition and relative material make-up costs. These are critical issues that should be addressed under realistic conditions prior to directing resources toward larger scale demonstrations. This paper will also describe NETL’s small 50-kWth natural gas circulating CLC test facility located in Morgantown, WV. Despite its small size, this experimental test unit has operated at autothermal conditions for 11 h using a copper-iron-alumina oxygen carrier developed at NETL. This paper will describe the test facility and operating experiences using NETL’s “Gen 2.0” oxygen carrier material. Natural gas conversion to CO2 ranged from 70 to 90% over approximately 75 oxidation-reduction cycles during the autothermal operating period. Estimates for the process specific attrition rate during autothermal operation are also presented. Finally, estimates for the oxygen carrier makeup cost, specific to the NETL process configuration, are several orders of magnitude greater than the NETL target. Future work should focus on reducing the oxygen carrier material cost and improving the attrition resistance of the oxygen carrier material under autothermal test conditions.

Risk Based Maintenance in the Hydroelectric Power Plants

In this study, maintenance planning problem is handled in one of the hydroelectric power plants which directly affect Turkey’s energy supply security with a fifth share in the total generation. In this study, a result is obtained by taking into consideration the multi-objective and multi-criteria structure of the maintenance planning in the hydroelectric power plants with thousands of complex equipment and the direct effect of this equipment on uninterrupted and low-cost electricity generation. In the first stage, the risk levels of the equipment in terms of the power plant are obtained with the combination of AHP (Analytical Hierarchy Process) and TOPSIS (technique for order preference by similarity to ideal solution) which are frequently used in the literature due to their advantages. Department-based maintenance plans of all equipment for periodic and revision maintenance strategies are formed by integrating these values into the time allocated for maintenance and the number of employees constraints. As a result of the application of this methodology which is designed for the first time in the literature with the integration of multi-criteria decision-making methods for the maintenance planning problem in a hydroelectric power plant, all elements that prevent the sustainable energy supply in the power plant are eliminated.

Exergoeconomic analysis of a combined solar-waste driven power plant

In this work, a thorough exergoeconomic analysis of a hybrid solar-waste driven power plant is presented. The objective is to give a clearer picture of the main irreversibilities, their corresponding costs and to find some effective yet feasible solutions to improve the efficiency and cost-effectiveness of the power plant. For this, the power plant is exergetically modeled, the exergoeconomic assessment is accomplished, the exergy losses are weighted, the cost of these losses are estimated and finally, the solutions are given. The cost of electricity was improved from 0.202 US$/MJ to 0.137 US$/MJ, after the application of the recommendations. Results show that electricity cost decreases in daily hours from a maximum of 10% in winter to the maximum of 26% in summer. Furthermore, the results of sensitivity analysis on the plant indicates that a hybrid cycle with turbine isentropic efficiency of 0.85, steam extraction ratio of 0.36 and inlet turbine temperature of 400 °C offers a 32% lower electricity cost compared to a cycle with a turbine isentropic efficiency of 0.75, steam extraction ratio of 0.16 and inlet turbine temperature of 500 °C.

An Accuracy-Efficiency-Power Consumption Hybrid Optimization Method for CNC Milling Process

This study proposes a hybrid optimization method which can help users to find optimal cutting parameters which will provide better efficiency and lower power consumption for a milling process. Empirical models including performance-power consumption characteristic curves of servo motors were built, and an optimization algorithm adopting the empirical models with procedure guiding function was developed. The empirical models were built based on the measurements from planned machining experiments with different combination of machining parameters including spindle speed, feedrate, and chip load, etc. After integrating the models and algorithm, an optimization system with human machine interface, which has procedure guiding function, was developed. The system can recommend optimal machining parameters for a milling process for shorter machining time and lower electricity costs based on the original machining parameters. Finally, cutting experiments were conducted to verify the proposed system, and the results showed that the proposed method can effectively enhance efficiency by 42.06% and save 34.74% in machining costs through reducing machining time and electrical power consumption.

Techno-Economic Analysis of an Integrated Gasification Combined Cycle (IGCC) Plant with Carbon Capture Storage

Although the efficiency and energy contribution of renewable energy are rapidly growing, coal is still an important fuel to meet the global energy demand. The integrated gasification combined cycle (IGCC), which is one of the coal power plants, has high efficiency and minimum cost penalties and has a high potential for further technological improvements. In this study, a technoeconomic analysis of the entire syngas process including carbon capture unit was conducted for a 500 MW-class IGCC with Shell gasifier using a sub-bituminous coal. Comparative performance evaluation of two different types of sub-bituminous coals (Montana and Wyoming)) was conducted. The performance including overall plant efficiency was evaluated. And the cost of electricity (COE) including CO2 transport and storage costs by geological location was estimated. The higher overall plant efficiency of 31.23% (HHV basis) could be achieved by using the Montana coal than Wyoming coal, 30.57%. However, the lower cost of electricity of 88.51 $ per net MWh was estimated from the Wyoming coal than Montana coal, 96.54 $ per net MWh.

Economic assessment of nuclear electricity from VVER-1000 reactor deployment in a developing country

The decision of policymakers in developing countries to introduce nuclear power to their energy mix has been mainly conversant with the low generation cost of nuclear electricity and its competitiveness with alternative conventional and renewable sources. This paper presents an economic assessment of the levelized cost of VVER-1000 reactors deployment in a newcomer developing country, taking Jordan as an example. This paper applies recent engineering procurement and construction (EPC) cost; observed construction time and plant performance, cost escalation rates, owner cost, and real discount rates in developing countries to calculate the levelized cost of electricity. The obtained results estimate the levelized cost of nuclear generation to be between $212.32 and $277.56 per MWh. However, evidence and sensitivity analysis presented in this paper suggest that the levelized cost vary considerably and may endup being as high as $610.09 per MWh or as low as $144.81 per MWh, this is mainly due to its sensitivity to unpredictable input parameters, which in turn has significant policy implications.

Carbon dioxide direct air capture for effective climate change mitigation based on renewable electricity: a new type of energy system sector coupling

Pathways for achieving the 1.5–2 °C global temperature moderation target imply a massive scaling of carbon dioxide (CO2) removal technologies, in particular in the 2040s and onwards. CO2 direct air capture (DAC) is among the most promising negative emission technologies (NETs). The energy demands for low-temperature solid-sorbent DAC are mainly heat at around 100 °C and electricity, which lead to sustainably operated DAC systems based on low-cost renewable electricity and heat pumps for the heat supply. This analysis is carried out for the case of the Maghreb region, which enjoys abundantly available low-cost renewable energy resources. The energy transition results for the Maghreb region lead to a solar photovoltaic (PV)-dominated energy supply with some wind energy contribution. DAC systems will need the same energy supply structure. The research investigates the levelised cost of CO2 DAC (LCOD) in high spatial resolution and is based on full hourly modelling for the Maghreb region. The key results are LCOD of about 55 €/tCO2 in 2050 with a further cost reduction potential of up to 50%. The area demand is considered and concluded to be negligible. Major conclusions for CO2 removal as a new energy sector are drawn. Key options for a global climate change mitigation strategy are first an energy transition towards renewable energy and second NETs for achieving the targets of the Paris Agreement.

Utilizing demand-side management as tool for promoting solar water heaters in countries where electricity is highly subsidized

ABSTRACT In many countries, especially those that produce petrol, electricity consumption is often subsidized. This policy leads to very low electricity costs and precludes the widespread use of solar water heaters, which have proven to be economically viable and are extensively utilized in other countries. Herein, we propose a new demand-side planning methodology to deal with such cases and perform an experimental finding–based economic assessment to study the feasibility of reducing subsidies in return for providing brand new solar water heaters to consumers. Specifically, solar water heaters are proposed to be supplied and installed free of charge as part of a demand-side management program in the Erbil province (Kurdistan region, Iraq). Assuming a duration of ten years, we show that the proposed project has a net present value of approximately US$776.6 million and requires an investment of US$90 million, further demonstrating that the successful launch of this project should dramatically reduce the winter peak load of 54 MW.

If You Build It, Will They Consume? Key Challenges for Universal, Reliable, and Low-Cost Electricity Delivery in Kenya

Kenya’s rapid electrification in the past decade has improved the lives of millions, and can serve as a template for other countries that are growing their electricity systems and coverage. However, significant challenges remain: many more remain without access, there is low consumption among those that are connected, and the electricity supply has poor reliability and quality. This paper provides analysis that shows electrification can be improved by considering cheaper options that still meet the needs of low consumers and that low consumption is a first-order problem for the sustainability of utilities.

The Practice and Potential of Renewable Energy Localisation: Results from a UK Field Trial

The adaptation of electricity demand to match the non-despatchable nature of renewable generation is one of the key challenges of the energy transition. We describe a UK field trial in 48 homes of an approach to this problem aimed at directly matching local supply and demand. This combined a community-based business model with social engagement and demand response technology employing both thermal and electrical energy storage. A proportion of these homes (14) were equipped with rooftop photovoltaics (PV) amounting to a total of 45 kWp; the business model enabled the remaining 34 homes to consume the electricity exported from the PV-equipped dwellings at a favourably low tariff in the context of a time-of-day tariff scheme. We report on the useful financial return achieved by all participants, their overall experience of the trial, and the proportion of local generation consumed locally. The energy storage devices were controlled, with user oversight, to respond automatically to signals indicating the availability of low cost electricity either from the photovoltaics or the time of day grid tariff. A substantial response was observed in the resulting demand profile from these controls, less so from demand scheduling methods which required regular user configuration. Finally results are reported from a follow-up fully commercial implementation of the concept showing the viability of the business model. We conclude that the sustainability of the transition to renewable energy can be strengthened with a community-oriented approach as demonstrated in the trial that supports users through technological change and improves return on investment by matching local generation and consumption.

Energy Saving System by Means of Electrical and Geo-Referential Identification of Load

In this project you have the control of the passage of the current in each outlet, for example, in a house where each outlet will be registered with a certain continuous electrical power for appliances, computers, among others. Every electrical device that has been registered and is connected to any outlet will work, if any other device that has not been registered is connected, it will not work in any socket. In addition, once any power outlet is connected, the system will detect where it is connected and we will know the place where it was connected. With this project, we will have a lower cost of electricity and economic savings. Keywords: Arduino, Sensor, Electric Current, Saving, Hall.

Size Optimization and Sensitivity Analysis of Hybrid Wind/PV Micro-Grids- A Case Study for Bangladesh

This paper presents a feasibility and sensitivity analysis of renewable energy-based off-grid and grid-connected microgrids by investigating the potentials of wind and solar energy at different areas, namely, Kuakata, Sitakunda, Magnama, Dinajpur and Rangpur in Bangladesh - a country that experiences a tropical climate. A specialized neural network algorithm has been employed to track the wind speed and solar irradiance all year round in two salient regions and the promising results have been analyzed for making the decision whether the data are reliable for forecasting or not. Four different types of models including PV-Grid, Wind-Grid, Wind-PV-Grid, and off-grid hybrid renewables are designed using the Hybrid Optimization of Multiple Energy Resources (HOMER Pro) software. By considering the key factors: net present cost, cost of energy, renewable fraction, local load demand, availability of renewable energy resources, system economics and greenhouse gas emissions, the optimal hybrid renewable energy system (HRES) configurations (Wind/PV/Grid/Battery) for the mentioned regions are determined. Various sensitivity and optimization variables, such as RE resources, local load demand, grid energy price, nominal discount rate, the life-time of wind turbine, the capacity of wind turbine, PV arrays, converter, and battery are used to make the decision. Detailed sensitivity analyses are performed to investigate how the optimal system configurations change with a tiny variation in input variables and results show output results are more sensitive on the variations in long-term average wind speed and solar irradiance, nominal discount rate, and the lifetime of wind turbines than the other inputs which is definitely a vital finding of this investigation. Finally, considering several decision making factors, a detailed feasibility chart is presented for two distinct nominal discount rates, i.e., 9% and 10%, which depicts the economically viable renewable energy based plant size in the mentioned regions. Although the crux of this paper is based on providing low-cost electricity to people living in rural areas of Bangladesh, our propositions carry with them certain concomitant benefits, not least of which are environmental and social benefits.

Economic feasibility of combined cooling, heating, and power (CCHP) systems considering electricity standby tariffs

This study examines economic viability of combined cooling, heating, and power (CCHP) systems when applied to the Department of Energy (DOE) reference large office building in three locales in the U.S.: San Francisco, Boston, and Miami. For realistic power generation unit (PGU) sizes, annual, monthly, and hourly operation costs are estimated using local utility tariffs and compared to those of conventional separate heat and power systems. The results show that compared to conventional systems, CCHP systems reduce operation cost by 0.11–0.42 million $/y in San Francisco and Boston, whereas they increase the cost by 0.16–0.29 million $/y in Miami. The cost savings are mainly attributed to electricity savings; therefore, be maintained unless electricity costs drastically decrease. Considerable cost savings are attributed to both energy and demand charges if tariff structures estimate demand charges as much as energy charges (e.g., San Francisco). Under time-of-use rates, the largest cost saving occurs during peak periods because of high utilization of PGUs that significantly reduces energy and demand charges. Although a larger PGU capacity yields a greater cost saving, an over-sized PGU decrease profitability. The results suggest that for regions with relatively expensive natural gas and low electricity cost, CCHP systems would not be profitable.

Design and Implementation of an IoT-Oriented Energy Management System Based on Non-Intrusive and Self-Organizing Neuro-Fuzzy Classification as an Electrical Energy Audit in Smart Homes

Smart cities are built to help people address issues like air pollution, traffic optimization, and energy efficiency. Electrical energy efficiency has become a central research issue in the energy field. Smart houses and buildings, which lower electricity costs, form an integral part of a smart city in a smart grid. This article presents an Internet of Things (IoT)-oriented smart Home Energy Management System (HEMS) that identifies electrical home appliances based on a novel hybrid Unsupervised Automatic Clustering-Integrated Neural-Fuzzy Classification (UAC-NFC) model. The smart HEMS designed and implemented in this article is composed of (1) a set of IoT-empowered smart e-meters, called smart sockets, installed as a benchmark in a realistic domestic environment with uncertainties and deployed against non-intrusive load monitoring; (2) a central Advanced Reduced Instruction Set Computing machine-based home gateway configured with a ZigBee wireless communication network; and (3) a cloud-centered analytical platform constructed to the hybrid UAC-NFC model for Demand-Side Management (DSM)/home energy management as a load classification task. The novel hybrid UAC-NFC model proposed in DSM and presented in this article is used to overcome the difficulties in distinguishing electrical appliances operated under similar electrical features and classified as unsupervised and self-organized. The smart HEMS developed with the proposed novel hybrid UAC-NFC model for DSM was able to identify electrical household appliances with an acceptable average and generalized classification rate of 95.73%.

Techno-Economic Evaluations of Copper-Based Chemical Looping Air Separation System for Oxy-Combustion and Gasification Power Plants with Carbon Capture

Energy and economic penalties for CO2 capture are the main challenges in front of the carbon capture technologies. Chemical Looping Air Separation (CLAS) represents a potential solution for energy and cost-efficient oxygen production in comparison to the cryogenic method. This work is assessing the key techno-economic performances of a CLAS system using copper oxide as oxygen carrier integrated in coal and lignite-based oxy-combustion and gasification power plants. For comparison, similar combustion and gasification power plants using cryogenic air separation with and without carbon capture were considered as benchmark cases. The assessments were focused on large scale power plants with 350–500 MW net electricity output and 90% CO2 capture rate. As the results show, the utilization of CLAS system in coal and lignite-based oxy-combustion and gasification power plants is improving the key techno-economic indicators e.g., increasing the energy efficiency by about 5–10%, reduction of specific capital investments by about 12–18%, lower cost of electricity by about 8–11% as well as lower CO2 avoidance cost by about 17–27%. The highest techno-economic improvements being noticed for oxy-combustion cases since these plants are using more oxygen than gasification plants.