Electric Generation Units Research Articles

Do Competitive Markets Clean Up the US Electricity Sector?: Evidence From the Southwest Power Pool

In the US, there has been a movement toward competitive electricity markets with system-operator auctions. However, the impact of such market reforms on non-market outcomes like emission rates remains unclear. We decompose how competition in wholesale electricity markets can affect carbon emission rates of electricity generating units (EGUs) through process, reallocation, and selection effects. Using event-study and difference-indifference strategies, we quantify the Day-Ahead Market’s (DAM) environmental impact in the Southwest Power Pool and assess the importance of each channel, with Pennsylvania, New Jersey, and Maryland interconnection serving as the comparison group. We find DAM reduced average carbon emission rates of EGUs by 0.033 tons per MWh, a roughly 4 percent reduction. This reduction is primarily driven by the selection effect: emission-intensive and uneconomical EGUs retire after the DAM market reform. This corresponds to an annual avoidance of 7.66 million tons of carbon dioxide emissions, worth approximately $383.4 million in avoided damages. JEL Classification: L51, L94, Q48, Q53

Dual functions of a microfluidic fuel cell as electricity generation and liquid pumping units

Microfluidic chip detection system serves as both electricity production and liquid pumping units.

Reducing Uncertainty in Energy Hub Operation: A Demand Response Approach for Improved Cost-Efficiency

Abstract In this paper, a daily programming was performed for an Energy Hub (EH). This EH has a typical electricity generation unit, a boiler, a Combined Heat and Power (CHP), two hectares of solar farm, three wind turbines with different capacities, a battery and a heat storage unit. This hub can purchase electricity from the upstream grid and is also responsible for fully supplying the electrical and thermal loads. Herein, power generation uncertainty by Renewable Energy Sources (RESs), the consumer's electrical and thermal demands as well as the upstream grid electricity market price are modeled by appropriate probability functions. In addition, the combined thermal and electrical energies to consumer are optimized. Moreover, the effect of uncertainty of uncertain parameters is reduced using a Demand Response Program (DRP) by load shifting method. The DRP is applied to both energy forms (electrical and thermal), which reduces hub costs by shifting the load from the hours when energy is expensive and unavailable to the hours when energy is cheap and available. Energy storage devices also shift energy from expensive to cheap hours. The integration of a Demand Response Program effectively minimizes operational costs and enhances the efficiency of the Energy Hub by optimizing energy usage in response to fluctuating prices and availability.

Multicity accountability and uncertainty assessment of the impacts of regulations on air quality in Atlanta, New York City, and Southern California

Multiple regulations have been promulgated to improve air quality, and previous studies have used an accountability chain to evaluate the effects of these regulations on emission levels, air quality, and human health. However, quantifying these impacts through the accountability chain is complex due to interactions between multiple factors that can influence the efficacy of control policies and introduce uncertainties at each step. We evaluated and quantified the impact of emission controls on electricity generating units (EGU) and motor vehicle sources on emissions and air quality via Generalized Additive Models. These GAMs have minimal bias (around 10−5 to 10−2 μg/m3 or ppbV) and r2 values for daily concentrations ranging from 0.4 to 0.7 Counterfactual air pollutant concentrations, in the absence of EGU and mobile source regulations, were calculated using estimated counterfactual emissions for the period 2005 to 2019 in Atlanta, New York City, and California's South Coast Air Basin. Counterfactual air pollutant concentrations indicated that the effects of regulations on air pollutants varied depending on the season and location. Predicted counterfactual air pollutant concentrations were generally 2–12 times higher than the measured concentrations at these sites, except for ozone. The impact of regulations on ozone concentrations typically resulted in reduced peak ozone values in the summer, but increased concentrations in the winter. Monte Carlo modeling found small to modest uncertainties, depending on the pollutant, location and regulations assessed. Counterfactual concentrations predicted in this project will be used in the assessment of the trends of toxicity in PM2.5.

The benefits and burdens of wind power systems in reaching China's renewable energy goals: Implications from resource and environment assessment

Recognizing the economy's growing reliance on global energy landscape transformation on wind power deployment, as well as the general reality that renewable facilities require lower operational but higher up-front inputs than fossil-based power systems, this paper focuses on the life-cycle burdens of wind power systems and their substitution benefits compared with coal-fired power systems. The estimation considers the consumption of nonrenewable sources of energy, emissions of greenhouse gases, and other environmental resource factors that have received significantly less research attention, such as industrial land use, water use, PM2.5, SO2, NOX, and Hg emissions. The scope of this study differs from earlier ones in that it includes a comprehensive description of all the equipment, materials, and services used, as opposed to earlier studies that either omit crucial supporting infrastructure or just focus on the plant's physical structure as its primary materials. Results based on a typical plant in China show that the state-of-the-art onshore wind power systems can provide significant reductions in nonrenewable energy use (9.2 MJ/kWh) and GHG emissions (782.8 GtCO2/kWh). To produce an equivalent amount of electricity, wind power systems require more than three times industrial land use and almost one-third of industrial water use of that for traditional coal-fired power systems. The avoided SO2, Hg, PM2.5, and NOX emissions per unit of electricity generation account for 60.6%–89.3% of the total air pollution emissions induced by supercritical coal-fired power systems. By integrating 3797 operating plant-specific data and fixed-point wind energy information, this study scales up results of the single plant to a country level. The macro picture implies different opportunities born by wind power systems in easing multiple resource and environmental pressures, highlighting the significance of designing hierarchical strategies to improve penetration levels of wind power. By 2050, cumulative climate benefits obtained from onshore wind power technology are predicted to reach 74.2 Gt CO2, achieving around 17.2%–45.5% of the national carbon-neutral goal.

Study and Analysis thermal performance of Taza gas power plant in Kirkuk –Iraq

In this research, the concept of energy balance was implemented in one of the gas turbine electricity generation units in Iraq (Kirkuk - Taza) K1. The design operating data is taken and compared with the data calculated in the computer model used by Engineering Equation Solutions (EES), and the validity of the model used was confirmed. The results indicate the release of a large amount of thermal energy into the atmosphere due to the open Brayton cycle, as energy losses amounted to 60% of the energy input. The results based on the data of the first unit of the station demonstrated that the theoretical efficiency of the unit is a function of the two variables, which are the temperature of the air entering the compressor and the Turbine inlet temperature: Increasing the compressor inlet temperature leads to a decrease in net power output and first-law efficiency and an increase in the specific fuel consumption rate. Increasing the turbine inlet temperature to 1°C leads to an improvement in both net power output and first-law efficiency by (0.24MW, and 0.04) %), respectively. The results also showed that cooling the air entering the compressor for 1°C leads to improving power output and first law efficiency by (0.72MW, and 0.12%), respectively, and reduces specific fuel consumption by 7.8kg/MWh.

Ozone sensitivity to high energy demand day electricity and onroad emissions during LISTOS

ABSTRACT Using a high-resolution, 1.33 km by 1.33 km coupled Weather Research and Forecasting-Community Multi-scale Air Quality Model (WRF-CMAQ), we quantify the impact of emissions of nitrogen oxides (NOx) from high energy demand day (HEDD) electricity generating units (EGU) and onroad vehicles on ambient ozone air quality in the Long Island Sound Tropospheric Ozone Study (LISTOS) region covering New York City (NYC); Long Island, NY; coastal Connecticut; and neighboring areas. We test sensitivity scenarios to quantify HEDD EGU NOx contributions to ozone: (1) zero out HEDD EGU emissions, (2) dispatch HEDD EGUs starting with the lowest NOx emitting units first, (3) reduce onroad emissions by 90%, (4) combine zero out HEDD EGU emissions and reducing onroad emissions by 90%, and (5) dispatch HEDD EGUs starting with the lowest emitting units coupled with a reduction in onroad emissions by 90%. Results determine that HEDD EGUs lead to highly localized impacts on ambient concentrations of ozone while onroad emission reductions lead to large-scale regional concentration impacts. Further, reducing onroad emissions by 90% leads to spatially smaller VOC-limited regions and spatially larger transitional and NOX-limited regions around NYC. Despite the limited scale at which the EGU emission reductions occur, modifying HEDD EGU NOX emissions still provides substantial benefits in reducing ozone concentrations in the region, particularly at elevated ozone concentrations above 70 ppb. Implications: High-resolution coupled meteorology-chemistry modeling was used to quantify the impacts of high energy demand day (HEDD) electricity generating units (EGUs) and onroad transportation emissions changes on ozone air quality in the LISTOS region. Despite being highly localized and variable, HEDD EGUs NOX emissions sensitivity tests led to quantifiable changes in ozone. Further, reducing onroad emissions by 90% produced large decreases in ozone concentrations and led to a more NOX-sensitive ozone photochemical regime. With a transition to greater NOX-sensitivity, urban NOX-titration weakens and ozone is more likely to decline with the removal of additional NOX from sources like HEDD EGUs.

A dynamic reference voltage adjustment strategy for Open-UPQC to increase hosting capacity of electrical distribution networks

Future electrical grids, particularly the distribution networks, may face more severe voltage rises/drops, and in general, more power quality problems in the presence of new loads such as electric vehicle chargers and renewable energy generation units like photovoltaic systems. This necessitates investing in additional high-cost infrastructure to increase the capability of the feeder in hosting higher levels of loads and generation units while the existing capacity is not utilized effectively. In the stated condition, effective voltage stabilization strategies in electrical distribution networks can contribute to hosting capacity improvement and the better utilization of the existing infrastructure. Accordingly, in this paper, the application of Open-UPQC in voltage profile improvement and hosting capacity enhancement is evaluated in low-voltage distribution networks. Furthermore, a dynamic reference voltage adjustment strategy is applied to the device to improve its capabilities in power quality improvement and hosting capacity enhancement. Simulation studies have been implemented to evaluate the capability of Open-UPQC either with static reference voltage or the dynamically-adjusted one in low-voltage networks with real measured data while different cases are assessed regarding the topology and the length of the feeder. The simulation results approved the capability of Open-UPQC especially with the dynamic reference voltage in hosting capacity enhancement while providing the highest level of voltage profile improvement among all the assessed custom power devices in the studied low-voltage networks.

Health benefits of phasing out coal-fired power plants in Ontario, Alberta, and Canada

Coal-fired power plants (CFPPs) in Ontario were decommissioned in a phased approach from 2003 to 2014. After Ontario's commitment to eliminate coal-based electricity generation, Alberta and Canada have planned on phasing out coal in the electricity sector. The coal regulation in Canada targets coal-free electricity generation by 2030, accelerating the criteria air pollutant emission reductions in the CFPPs nationwide. The Regulatory Impact Analysis Statement (RIAS) under the coal regulation estimated substantial health benefits based on scenario analysis. Here we use adjoint sensitivity analysis as an alternative approach to estimate the health impacts of CFPPs and non-coal electric generating units (EGUs). The adjoint of the U.S. EPA's Community Multiscale Air Quality (CMAQ) model is used to attribute PM2.5-related health impacts for primary and precursor PM2.5 emissions emitted from the CFPPs and non-coal EGUs in Canada using various epidemiological studies. Our findings suggest that the reduction of CFPP emissions yields more total benefits rather than other fuel types in EGUs. A significant amount of total health burden is estimated to occur within the province that hosts the facility, and with a larger portion of this benefit coming in warmer seasons. Our retrospective analysis of Ontario coal phase-out estimates $1B CAD total annual health benefits in 2003, or projected 2014 benefits of $1.8 B CAD. The transboundary impact of emission reductions from coal-fired power plants in the U.S. entails significant health benefits to Ontario and Canada, more than twice that of Ontario's own coal phase-out. Nationwide, total health burden estimate for CFPPs and non-coal EGUs is $418M CAD in 2014. The choice of epidemiological model has a sizeable impact on estimated burdens or benefits.

Characterizing multi-pollutant emission impacts of sulfur reduction strategies from coal power plants

Fuel combustion for electricity generation emits a mix of health- and climate-relevant air emissions, with the potential for technology or fuel switching to impact multiple emissions together. While there has been extensive research on the co-benefits of climate policies on air quality improvements, few studies have quantified the effect of air pollution controls on carbon emissions. Here we evaluate three multi-pollutant emission reduction strategies, focused on sulfur dioxide (SO2) controls in the electricity sector. Traditional ‘add-on’ pollution controls like flue gas desulfurization (FGD) reduce SO2 emissions from coal combustion but increase emissions of nitrogen oxides (NO X ), volatile organic compounds (VOCs), fine particulate matter (PM2.5), and carbon dioxide (CO2) due to heat efficiency loss. Fuel switching from coal to natural gas and renewables potentially reduces all pollutants. We identified 135 electricity generation units (EGUs) without SO2 controls in the contiguous US in 2017 and quantified the unit-level emission changes using pollution control efficiencies, emission rates, fuel heat input, and electricity load. A cost-benefit analysis is conducted, considering pollution control costs, fuel costs, capital and operation and maintenance (O&M) costs, the monetized health benefits from avoided multi-pollutant, and the social cost of carbon as the benefit for carbon reduction. We find that add-on SO2 controls result in an average annual net benefit of $179.3 million (95% CI: $137.5-$221.0 million) per EGU, fuel switching from coal to natural gas, $432.7 million (95% CI: $366.4-$498.9 million) per EGU; and fuel switching from coal to renewable energy sources, $537.9 million (95% CI: $457.1-$618.9 million) per EGU. Our results highlight multi-pollutant emission reduction strategy as a cost-effective way to synergistically control air pollution and mitigate climate change.

Research on the Accounting and Prediction of Carbon Emission from Wave Energy Convertor Based on the Whole Lifecycle

Wave energy, as a significant renewable and clean energy source with vast global reserves, exhibits no greenhouse gas or other pollution during real-sea operational conditions. However, throughout the entire lifecycle, wave energy convertors can produce additional CO2 emissions due to the use of raw materials and emissions during transportation. Based on laboratory test data from a wave energy convertor model, this study ensures consistency between the model and the actual sea-deployed wave energy convertors in terms of performance, materials, and geometric shapes using similarity criteria. Carbon emission factors from China, the European Union, Brazil, and Japan are selected to predict the carbon emissions of wave energy convertors in real-sea conditions. The research indicates: (1) The predicted carbon emission coefficient for unit electricity generation (EFco2) of wave energy is 0.008–0.057 kg CO2/kWh; when the traditional steel production mode is adopted, the EFco2 in this paper is 0.014–0.059 kg CO2/kWh, similar to existing research conclusions for the emission factor of CO2 for wave energy convertor (0.012–0.050 kg CO2/kWh). The predicted data on carbon emissions in the lifecycle of wave energy convertors aligns closely with actual operational data. (2) The main source of carbon emissions in the life cycle of a wave energy converter, excluding the recycling of manufacturing metal materials, is the manufacturing stage, which accounts for 90% of the total carbon emissions. When the recycling of manufacturing metal materials is considered, the carbon emissions in the manufacturing stage are reduced, and the carbon emissions in the transport stage are increased, from about 7% to about 20%. (3) Under the most ideal conditions, the carbon payback period for a wave energy convertor ranges from 0.28 to 2.06 years, and the carbon reduction during the design lifespan (20 years) varies from 238.33 t CO2 (minimum) to 261.80 t CO2 (maximum).

Technical-economic evaluation of various photovoltaic tracking systems considering carbon emission trading

Renewable energy generation plays a crucial role in mitigating global climate change and achieving carbon peak and carbon neutrality targets. Photovoltaic (PV) power is an important component of renewable energy generation. With China's commitment to meet its dual carbon targets on time, the application of PV tracking systems, which significantly increase the amount of PV power generated, has become a trend for the future. However, the suitability of PV tracking systems varies significantly between regions. This paper aims to assess and compare the technical and economic performance of PV systems using different PV tracking systems in six different latitude regions in China under the consideration of carbon trading. By utilizing the PVsyst software, the monthly/yearly unit electricity generation of different tracking systems in each region is calculated. Furthermore, the technical and economic performance of these systems is assessed by computing the levelized cost of electricity (LCOE), net present value (NPV), and discounted payback period (DPP) with and without carbon benefits, taking into account sensitivity analyses. The results indicate that the dual-axis tracking (DAT) system achieves the highest electricity generation, providing a gain of 17.94 %–31.52 % compared to the fixed-tilt (FT) system. The horizontal axis tracking North-South (HATNS) system and the tilted-axis tracking (TAT) system are probably the most economically viable systems in areas with high radiation levels, with NPV values 2.02 %–25.55 % and 6.44 %–19.45 % higher, respectively, compared to the FT system. The introduction of carbon benefits significantly increases the economic viability of all tracking systems.

Smart traffic routing and service allocation strategy to reduce water consumption in data centers through power reduction

Due to the growth of communication networks, energy consumption in information and communication technology industries is increasing dramatically. Among these industries, data centers are operating with a large number of processors and other components, which, due to heavy processing and mass data transmission, in addition to consuming high electrical power, also cause high thermal losses. Since water cooling systems are used for cooling different parts of these centers as well as for cooling the electric power generation unit, these centers are among the major consumers of water and electricity resources. In this article, while examining the important factors affecting water consumption in data centers, useful methods are suggested to reduce the consumption of electrical energy and water. Optimizing energy consumption in data centers is possible in three parts: routing, servicing and use of cooling equipment. For all three parts, improvement methods are suggested in this article. For this purpose, an optimization problem is designed and an algorithm is presented to solve it. In the proposed solution, an energy-smart method based on SDN technology is used for routing, virtual machines equipped with the possibility of reducing power consumption in no-load conditions are used for servicing, and two types of water-cooled and air-cooled systems are used for cooling equipment. is used. The simulation results show that depending on the cooling system, the proposed method reduces water consumption between 24% and 32% compared to the case where the proposed solution is not used.

Improve the Electric Power Generation Issue by Cognitive Thinking

The enormous increase in power demand due to the prevalent heat wave, the worst power shortage in the last decades, and lack of sufficient fossil fuels like natural gas, coal, oil, etc. has attracted the attention of researchers worldwide. One of the main reasons behind the problem is the mismanagement of proper regulation of the electrical power generation unit. This paper looks at cognitive thinking to address and improve this issue by noting that it is the process of gaining knowledge and understanding through thought, experience, and the senses that have enabled researchers to infer cognitive processes. Highly controlled and rigorous methods of study have always been employed to enable the work. Thermal energy power plants have been taken as the source of power generation and genetic algorithm (GA), fuzzy, and PID (Proportional, Integral, Derivative) controllers are used. All these controllers handle and control sudden changes in load frequency and power. For better and more effective results of the system, combined feedback has been obtained with the help of MATLAB Simulink software. The results obtained from the combined feedback are tabulated, which shows that all the controllers improve the electrical power generation issue by modulating the changes in load frequency and power, but the GA controller produces effective, efficient, and better results by adjusting to the changes in less time. The use of this cognitive thinking of the controller helps in the proper management of power demand which automatically improves and controls the power generation.

Investigation of the influence of the heterogeneity of the load node on its comparability with the power of the energy source in an autonomous energy system

The article considers the investigation of the influence heterogeneity of the load node on the required power of the power source and on their comparability. By checking fulfillment of loading conditions of the electric generator unit, the obtained analytical dependencies in relation to determining parameters of an autonomous power supply source for a multi-motor load are solved. The criterion of comparability was proposed for matching the power of the source with the installed power of consumers of the autonomous energy system. A dependency for determining the comparability coefficient was given for the system the electric generator unit and the load node. The analysis of the permissible solution the comparability coefficient has been carried out for ensuring rational loading of the electric generator unit in the continuous operating. The necessity of using devices for reducing or compensating the reactive power of individual electric loads was assessed to reduce the power of the electric generator unit.

A Comparative Study Of Reliability-Centered Maintenance And New-Based Maintenance Approaches On A Working-Hours Engine: A Case Study

Maintenance is an important system in operation. In an era where the electricity generation industry focuses on 24-hour operations to maximize the production of electrical energy, which is needed for development and as a driving force for office equipment and the economy of the people in Timor- Leste, it is pushed to its absolute limit to meet this demand. With the increase in the operation of the electric energy generation unit, the wear and tear of the engine components will increase. So, the need for increased engine parts, to prevent failure. To remedy this situation and guarantee the machine’s continued peak performance, preventative maintenance is executed. Preventive maintenance (PM) is one subfield of maintenance that aims to forestall failures before they manifest. The maintenance, production, and management teams will need to work closely together to make PM a success. This article is a case study of Electrical Diesel Timor-Leste (EDTL), a firm with two power production facilities located in Hera and Betano, and it examines the causes of inefficient PM activity and the ramifications this has for the organization.

Prospective life cycle environmental impact assessment of renewable energy-based methanol production system: A case study in China

Integrating renewable electricity and green hydrogen with CO2 utilization to produce chemicals has drawn much attention due to its low carbon emission characteristics. The goal of this paper is to investigate the environmental sustainability of producing a steady hourly output of methanol by utilizing electricity and hydrogen produced via renewable energy resources, and CO2 captured from a coal-fired power plant located in Inner Mongolia, China. Six renewable energy-based electricity and hydrogen systems are considered based on photovoltaic, wind turbines and combinations thereof, including battery and grid technologies. The environmental impact indicators of these system are compared comprehensively through life cycle assessment approach, including not only global warming potential but also fossil fuel depletion, water & soil & air pollution indices and human health index. The results indicate that the most environmentally friendly system is Case B2 which uses photovoltaic to produce hydrogen and electricity, with battery for energy storage and excess electricity sold back to grid. It shows apparently the best sustainability performance in global warming potential, which is 0.105 kg CO2-eq per kg methanol. In general, the proposed six systems outperform conventional methanol production systems in terms of global warming potential and abiotic depletion potential, with reductions ranging from 74% to 92% and 51.1%–73.8% respectively, but they have high levels in other environmental sustainability indicators such as human toxicity, eutrophication potential, and ozone layer depletion potential due to the photovoltaic electricity generation unit. The findings highlight that it is essential to consider a comprehensive range of environmental sustainability indicators when developing renewable energy-based methanol systems on a large scale.

Water consumption of electric power system in China: from electricity generation to consumption.

Understanding the water requirement of electricity generation is critical to the development of both electricity and water systems, while the water consumption of the whole electric power system remains unrevealed. Here, we examine the water consumption driven by electricity generation, transmission, and consumption in China, finding that 14 billion m3 of freshwater is consumed by electricity generation in 2019 and that 2.5 billion m3 of freshwater was virtually transferred via electricity transmission. Nationally, the freshwater consumption per unit of electricity generation was 1.9 m3/MWh. Based on the state-of-the-art electricity transmission data, we find that 59% of the transported electric power was from water-scarce provinces and 0.7 billion m3 of freshwater was lost due to the electricity loss in transmission lines in China. It is essential to link water resources with the whole electric power system (production, transmission, and consumption) rather than only part of the power system as in previous research.

Changes in ambient air pollutants in New York State from 2005 to 2019: Effects of policy implementations and economic and technological changes

Over the past 20 years, a number of regulatory efforts have been applied to improve air quality in the United States and specifically in New York State. These measures generally focused on mobile emissions through emissions controls and improved fuel quality, and controls on electricity generation to reduce emissions from older, uncontrolled electricity generation units (EGUs). In addition, economic drivers such as the major recession in 2007–2009 and the change in the relative costs of natural gas and coal also drove changes in the mixture of EGU technologies. To assess the effects of these changes and to define the baseline for future changes as the economy further decarbonizes through renewable electricity generation and electric vehicles, the concentrations of all pollutants measured at all regulatory monitoring sites in New York State were assessed for their trends. Trends were examined using seasonal-trend decomposition with local regression smoothing (STL), Mann-Kendall trend analysis with the Theil-Sen nonparametric slope estimation, and piecewise regression analysis to identify breakpoints in the slopes of the time series data. The concentrations of primary gaseous pollutants, CO, NO2, and SO2 have decreased substantially in step with the declining emissions. PM2.5 has substantially declined largely due to the reductions in particulate sulfate. However, in recent years, the rate of decline has diminished due to relatively constant or increasing particulate nitrate and secondary organic aerosol. O3 has also generally increased at the urban sites likely as a result of reduced NOx emissions, while it declined or remained constant at the rural sites. Thus, the promulgated regulations assisted by the economic drivers have improved air quality, but additional actions will be needed to further reduce urban O3 and PM2.5.

Quantifying the local economic supply chain impacts of renewable energy investment in Kenya

Improved electricity access in developing countries can offer an array of economic and environmental benefits. In Kenya, much attention has been devoted to the array of end-user benefits from electrification; however, there are also potential supply-side benefits from building and operating electricity generating units (EGU). This study focuses on the latter by examining supply chain impacts of recent renewable energy construction projects in Kenya tracked by the U.S. Agency for International Development's (USAID) Power Africa program and construction projected in Kenya's Least Cost Power Development Plan (LCPDP). By combining construction cost estimates with information on expenditure shares across economic sectors combined with data on wages and jobs, this study provides an assessment of the direct and indirect wage and job benefits of past and future EGU construction and operations. On-grid electrification projects tracked by Power Africa have increased domestic spending in Kenya by $1.3 billion and increased direct and indirect wages by $344 million over the ten years from 2012 to 2021. This impact could expand to $18.9 billion in domestic spending and $5 billion in nominal wages from 2022 to 2040 if the Kenyan government's LCPDP projected capacity and operations goals are met. The direct jobs required to support new LCPDP power sector construction out to 2040 could be 177,000 jobs in an average year, or 3.5 times higher than the average over the past ten years (2012−2021). Meanwhile, direct and indirect jobs supporting new power plant operations and maintenance would be 46,000 jobs in an average year, or 7 times the average over the past ten years. These findings suggest the high potential of renewable energy projects for supporting employment in Kenya, and thus the importance of creating an enabling environment that allows these projects to succeed.