Each of the renewable energy sources has the potential to meet the global energy demand many times over, as seen from the material presented earlier in this book. The technological benefits of renewables, particularly their ability to mitigate climate change through the reduction of carbon emissions, are also well understood. These benefits, along with the limitless supply potential, should, in theory, provide sufficient impetus for transitioning to renewable energy systems. However, energy transitions are complex phenomena that have historically been driven by crises of supply or development of superior sources and accompanied by significant perturbances in societies and economies of nations over a prolonged period of time. Transitioning to the sustainable energy systems of the future that are based on renewable primary energy sources requires an understanding of the economics of energy systems and formulating policies for responsible management of the transition.
The current status of renewable energy systems across different parts of the world is presented below, followed by a discussion of the key indicators used to measure the performance of energy systems and sources. These indicators include energy balances and economics of the systems. The environmental impacts of the renewable energy systems is then presented, followed by an overview of public policies pursued to facilitate the development of renewable energy.
The contribution of renewables in the global energy market is expected to rise gradually, as shown in Figure 1.3 in Chapter 1, Introduction to Energy Systems. It is instructive to take a further detailed look into the current status of renewables with respect to the contributions of specific sources, as well as the variations across the different regions of world in terms of the energy mix. Figure 7.1 shows the total contribution of renewables in the global electricity production in 2018 and their relative position with respect to the other major sources of electricity—coal, natural gas, and nuclear .1
1. The figures are based on the data from the International Energy Agency, www.iea.org. As mentioned in Chapter 1, such energy data are available from several other sources as well, the Energy Information Administration (www.eia.gov) of the U.S. DOE being one of the most comprehensive resources for information on all aspects of energy. The IEA and EIA data correspond very well with each other, though they may not be identical.
It can be seen that globally coal is still the dominant primary energy source accounting for nearly 37% of the electricity production, while renewables (including electricity generated from waste streams) contribute nearly 25% of the electricity produced worldwide. The energy mix varies by the region, and Figure 7.2 shows the contributions of various primary energy sources for the United States, China, the European Union (EU), Asia (excluding China), and Africa.
The bars in Figure 7.2 indicate the contribution of the primary sources on the primary y-axis on the left. The markers indicate the total electricity generated in the region on the secondary y-axis on the right. It can be seen from the figure that China is the largest producer (and consumer) of electricity, and coal occupies a dominant position in its energy mix, supplying nearly two-thirds of its electricity. Coal is the predominant energy source for the rest of Asia as well, although to a lesser extent than China, accounting for only slightly over half of the electricity generated. Renewables lead the other energy sources in the EU, where nuclear ranks as the second largest electricity resource, generating more electricity than any of the carbon-based resources—coal, natural gas, or oil (not shown in the figure due to its low contribution). On the other hand, the largest primary energy source for electricity is natural gas in the United States, and renewables generate almost as much electricity as nuclear power. Nuclear and natural gas are not as significant primary resources in China, where renewables are second only to coal.
Further analysis of the electricity generation data reveals interesting patterns regarding the contributions of the various renewable energy sources across the different regions. These data are summarized in Figure 7.3, wherein the contributions of biomass, hydropower, geothermal, solar photovoltaic, solar thermal, and wind power are shown for each of the five countries/regions. Total renewable energy generated and the contribution of hydropower are shown by open square and open triangle markers, respectively, plotted against the secondary y-axis on the right. The contributions of the other sources are shown by bars plotted against the primary y-axis on the left. It should be noted that the scales of the two axes are different.
The following trends can be identified from the figure:
Hydropower is the dominant renewable electricity source for developing economies, including that of China. Hydropower accounts for more than 80% and nearly two-thirds of renewable electricity in Africa and Asia (including China), respectively. Hydropower, while not as dominant in the United States and EU, is still the largest contributor, accounting for ~33% of the renewable electricity in these regions.
Wind power is the second largest renewable energy source, contributing almost as much as hydropower in the United States and EU, and exceeding the combined contributions of the rest of the renewables everywhere except in the rest of Asia excluding China.
The contributions of geothermal energy and solar thermal power are relatively minor. Most of the solar electricity generation is through photovoltaic technology.2
2. Though not shown in Figure 7.3, the data also reveal that nearly two-thirds of the solar photovoltaic electricity is generated by utility-scale installations, the rest being produced in distributed residential and commercial systems.
Finally, contributions of ocean power are minimal and not included in Figure 7.3, as the numbers would not register on the plot.
The total electricity generation in the rest of Asia and Africa lags considerably behind that of the developed economies of the United States and the EU. Considering that Asia and Africa are the home to nearly three-fourths of humanity, the gulf between the two (Asia/Africa and the United States/EU) is even wider when the numbers are based on per capita electricity generation in 2018 as shown in Table 7.1.
Table 7.1 Population, Growth Rate, and Electricity Generation
Population Growth Rate, %
Per Capita Electricity Generation, kWh/year
Asia (excluding China)
Source: International Energy Agency, “Data and Statistics,” https://www.iea.org/data-and-statistics/data-tables?country=WORLD, accessed September 27, 2020; World Population Review, https://worldpopulationreview.com/, accessed September 27, 2020.
It can be seen that the per capita electricity generation in the less developed parts of the world is nearly an order of magnitude lower than that of the developed nations. These numbers, combined with the growth rates of the population, serve to provide an estimate of the magnitude of the challenge for the primary energy sources, particularly the renewable sources, to meet future energy needs.
As mentioned in Chapter 1, only a fraction of primary energy is utilized for electricity generation, with commercial, transportation, industrial, and residential applications accounting for the rest of primary energy needs. Figure 7.4 shows the primary consumption by source in the United States in 2019 .
The distribution of primary energy sources globally is slightly different from that of the United States. With nearly a quarter of nuclear power reactors in the world at the present time, the contribution of nuclear to the primary energy supply is higher in the United States compared to the rest of the world. Furthermore, while the combined fossil resources—coal, oil, and natural gas—account for approximately the same fraction (between 80% and 85%) of the primary energy sources, the distribution varies across the regions, with coal contributing almost 10% more for the rest of the world as compared to the United States. The contribution of renewables, however, is quite similar, accounting for 10–15% of the primary energy supply.
The second largest use of renewables is in transportation fuels, and Figure 7.5 shows the 2019 production of bioethanol and biodiesel (comprising biodiesel formulated via transesterification/alcoholysis, as well as renewable/green diesel produced by hydrotreating vegetable oil) in the top five leading countries/regions for each fuel .
The United States and Brazil are the two largest producers of bioethanol, accounting for approximately 48% and 26% of the global production, respectively. Similarly, the EU and the United States are the dominant producers of biodiesel, together accounting for more than 50% of global biodiesel production. These volumes, though large, are dwarfed by petroleum-based gasoline and diesel used in transportation applications. The United States used approximately 142 billion gallons of gasoline and 47 billion gallons of diesel for transportation in 2019, numbers that are at least an order of magnitude greater than those of biofuels.
Biofuels currently produced in the world, including the United States, belong to the first generation of biofuels, that is, the production is based on food crops. The bioethanol produced in the United States is derived primarily from corn (maize), while Brazilian bioethanol is based primarily on sugarcane. Sugar beet, wheat, and cassava are also used in addition to corn for bioethanol production in other countries. Biodiesel production in most countries typically involves conversion of used cooking oils or soybean/rapeseed oil, while palm oil is the mainstay for Indonesian biodiesel.
It is clear that renewable energy systems must expand by at least an order of magnitude simply to displace other primary energy sources based on current levels of energy consumption. The scale of expansion becomes even greater when increasing energy needs of the populations of developing economies are factored in estimation of future energy demands. The investment needed in renewable energy technologies in order to achieve such levels can easily run into tens, if not hundreds, of trillions of U.S. dollars. Policymakers need to have at their disposal key performance metrics that will allow them to compare various technologies in a fair and impartial manner and make informed decisions to invest in technologies that will ensure a sustainable, affordable, and secure energy future.
Several different types of metrics can serve as indicators of the performance of an energy system. These metrics may be based on energy flows (physical indicators), cash flows (economic indicators), impact on environment (environmental factors), or impact on society (societal indicators) .
Physical indicators are typically based on actual energy flows, and the performance of the technology may be assessed through the gross or net energy yield of the project, ratio of energy delivered to energy input to the technology (energy return on investment [EROI]), or energy payback time, which is the time needed to extract energy equivalent to that invested to implement the technology.
Environmental indicators are based on environmental impact of the project and may include metrics such as greenhouse gas (GHG) emissions, acid gas emissions, land use, and sustainability.
Economic indicators provide a measure of the cash flow, similar to the physical indicators that are based on energy flows. These indicators may involve determining the payback period, net present value of investment, benefit-to-cost ratio, rate of return, lifetime costs, levelized cost of electricity (LCOE), and so on.
Figure 7.6 shows the LCOE for various electricity generation technologies for new plants based on the data available from the Energy Information Administration (EIA) . Social indicators may be based on factors such as jobs creation, impact on human health, import substitution and self-reliance, and so on. Quantification of social indicators is more challenging than that of the other three types of indicators.
Each of these indicators provides a useful measure of the value of the energy technology, and a comprehensive analysis of an energy system needs to include all types of indicators as well as multiple measures within each indicator. Such comprehensive analysis is beyond the scope of this book. However, three key indicators that help define the worth of an energy system are discussed below in detail.
The LCOE is a very popular indicator frequently used for evaluating and comparing electrical energy generation systems. LCOE is defined as the minimum average price of electricity needed to recover all the costs incurred during the lifetime of the power plant . Equation 7.1 shows the basic formula for determining the LCOE :
The usefulness of LCOE arises from its incorporation of all the costs incurred over the lifetime of the power plant. Furthermore, it sets the lower limit on the price at which the electricity generator must be able to sell the electricity in a market to avoid any loss. Equation 7.1 takes different forms depending on the methodology employed to calculate the lifetime costs. The formula used by the U.S. Department of Energy’s (DOE) National Renewable Energy Laboratory (NREL) focuses on capital recovery annualizing the capital costs and incorporating the variable operating costs as shown in equation 7.2.
where Con is the overnight capital cost ($/kW) and V is the variable (operating) cost in $/kWh. σ is the capacity factor of the plant (the fraction of the time the plant operates at the rated capacity), and CRF is the capital recovery factor, which depends upon the interest rate (i) and the number of payments (n) made to repay the capital as shown in equation 7.3.
The formula for calculating LCOE can be modified from its basic form depending upon the assumptions made and incorporation of factors such as depreciation and taxes and so on. The overnight capital cost, also referred to as CAPEX in the economic analysis of projects, includes the cost of structures, foundations, equipment, control systems, installation costs, and so on, and is dependent upon the type of technology, plant capacity, and geographical location. Variable operating costs, OPEX, include the cost of consumables (if any), operation and maintenance, personnel costs, and so on.
It can be seen from the figure that most of the renewable sources, except for offshore wind and biomass energy, have a lower LCOE than conventional coal and advanced nuclear. Based on these values, renewable electricity is competitive with that generated from the natural gas combined cycle (NGCC) plants, which has the lowest LCOE of all the conventional power plants.
It should be noted that the estimation of LCOE is highly sensitive to the assumptions made in the calculation, and the LCOE values reported in the literature show substantial variations for each technology. Figure 7.7 shows the range of LCOE values reported in various technical reports for the different renewable electricity technologies .
Examination of Figure 7.7 reveals the following points:
There is considerable spread in the LCOE values of all renewable electricity technologies, with EIA estimates ranking at the lower end of the spread.
Tidal and wave power have the highest LCOE among renewables, indicating that ocean technologies are still emerging and evolving.
Solar thermal power tends to have a higher LCOE than solar photovoltaic (PV).
Offshore wind power is considerably more expensive than on-shore wind power.
A practically unlimited number of such analyses have been reported in the literature. While the actual numbers may show variation, most studies conform to the abovementioned qualitative trends. In general, the spread in the LCOE for renewables tends to be greater than that of conventional fossil or nuclear power generation or hydropower .
The LCOE is a very useful metric; however, it does not capture all of the factors that contribute to actual investment decisions. It is sometimes argued that LCOE tends to be used as an undiscounted metric that distorts the results disfavoring renewable sources . The biggest drawback of LCOE is that it does not correspond to actual revenue realized from the power plant or the profitability of the technology. Those quantities depend upon the market price of electricity, which does not factor in the calculation of LCOE. Direct LCOE comparison among various technologies may be misleading and should not be the sole metric for making decisions about investments in power technologies .
The EIA has developed another metric—levelized avoided cost of electricity (LACE)—that incorporates the market price of electricity in the assessment of energy technologies. LACE is based on the presumed replacement of existing electricity sources by the proposed new electricity source in a market. The new source will displace an equivalent capacity from an existing resource, realizing revenues based on the prevailing electricity price in that particular market. The newer resource is expected to be more efficient and profitable than the older, inefficient resource. Incorporating the new resource in the energy mix thus avoids the costs that would be incurred using the older technology/resource—the costs expressed as LACE. LACE is expected to be higher than LCOE, and the difference between the two indicating the net value and profitability of the new resource . LACE calculations are more complex than LCOE calculations, because unlike LCOE, which is market independent, LACE for the same technology will have different values in different electricity markets. Furthermore, the net value also depends upon the type of resource that is displaced by the new resource. For example, LACE for displacement of an inefficient coal power plant by solar PV is different from the displacement of a NGCC plant by the same renewable resource .
LCOE and LACE both offer different insights into the economic performance of the energy sources. LCOE allows a direct comparison between competing energy sources; however, it does not reflect revenue or profitability. LACE provides a market context to the economic performance of the resource, adding value to its assessment. LACE is also simplistic in its assumption of displacement of an existing resource and ignores the dynamics of the electricity market. For example, it does not account for possible changes in demand in response to additional capacity.
LCOE (or LACE) is just one economic indicator that influences the choice of the energy technology. LCOE, as with LACE, is essentially based on the life of the power plant, and thus the economic indicator is based on an extended time period. However, a power plant requires substantial capital investment up-front for the construction, equipment, and commissioning of the plant even before a single watt of electrical power is generated. Several activities, such as regulatory approval and land acquisition that precede the actual construction, also require significant capital investment. This capital is raised through a combination of debt and equity, and total investment is typically expressed in terms of capital cost per unit of power for comparison among different competing technologies [7, 11]. Obviously, these expenses are incurred over a period of time; however, they are expressed conveniently in terms of overnight costs, that is, assuming an overnight construction of the plant on the basis of current costs of contributing components. This assumption allows a simplification of analysis, as any impact of cost appreciation over time or interest charges is disregarded. As with other economic indicators, overnight costs of power plants have been analyzed and continue to be analyzed by various entities including universities, public and private organizations, research institutes, and industries. The overnight cost results for various plants as determined by EIA are shown in Figure 7.8 along with the capacities of typical power units for that technology .
The NGCC power plant has the lowest overnight cost, while the solar CSP plant has the highest cost exceeding that of the advanced nuclear plant. On-shore wind power has only slightly higher overnight cost than the NGCC plant; however, the typical capacities of wind power plants are nearly an order of magnitude lower than those of the NGCC units. Costs of offshore wind power plants (not shown in Figure 7.8) are almost three and four times higher than those of on-shore plants. Overnight costs of geothermal plants are also low, compared to other technologies, but the typical size of the plant is also much smaller, like that of biomass plants. The data shown in the figure represent plants where biomass is the sole source of fuel. The coal power plant cost shown above is for a unit operating without carbon capture and sequestration. Provision of carbon capture will increase the overnight cost by nearly $1000/kW.
Based on the overnight costs, wind power and solar photovoltaics seem to be the most promising renewable technologies for electricity production. Solar thermal power appears to be very expensive, and provision of thermal energy storage results in an even greater number. However, thermal energy storage serves to increase the capacity factor, allowing more electricity generation that may be reflected in superior LCOE/LACE numbers.
As with LCOE/LACE analyses, a large number of reports and studies are available in the literature on the overnight costs of the power plants. Perusal of such reports readily reveals the wide spreads in the overnight cost numbers, which are highly sensitive to the assumptions made in their determination. The costs are also dependent upon location, and a careful detailed assessment is needed to obtain a more accurate estimate for any specific situation before making a decision regarding the energy technology.
Electricity may be the main product of the renewable energy systems; however, it is not the only output. Heat and biofuels are the other important products of transformations of primary energy sources. The metrics LCOE/LACE are not applicable to the systems generating energy carriers other than electricity. The energy return on (energy) investment EROI or EROEI is a more general metric that can provide a basis for the comparison of various energy systems irrespective of the final energy form delivered to the consumer. EROI is the ratio of the amount of energy harvested from the system to the total amount of energy supplied to the system—energy investment—to realize the transformation .
Four types of EROIs are used in the energy system analysis arena depending upon the system boundary: (1) standard (EROIST); (2) point of use (EROIPOU); (3) extended (EROIEXT); and (4) societal (EROISOC) [13, 14]. EROIST considers all energy output and input streams but excludes labor and financial services. EROIPOU augments the energy input by accounting for the additional energy needed to transform, refine, enhance, and transport the energy/fuel extracted. Clearly, EROIPOU is smaller than the standard EROI, due to increased energy requirements for these additional process steps. Further extending the system boundary to include energy costs associated with infrastructure and the use of energy yields an even lower EROIEXT. EROISOC is essentially a composite indicator that is defined for a region (city, state, country, etc.) on the basis of all the energy/fuels delivered to the region and the total energy consumed to acquire this energy/fuel. As most regions get an energy mix from different technologies, EROISOC is not associated with a particular energy source, fuel, or system.
The differences among the various EROIs can be understood by examining the system for bioethanol production and application. The various steps where energy inputs are required are : (1) growth of biomass (corn, wheat, sugar beet, energy crops, etc.) including farming operations, fertilizers, pesticides, and so on; (2) harvesting of biomass; (3) storage and transportation of raw material to biorefineries; (4) pretreatment, processing, and refining of the product; (5) transportation and distribution to retailers; and (6) acquisition and utilization by the consumer. EROI values will be heavily influenced by the choice of the system boundary.
The EROI of fossil fuels is typically quite high, with the value for coal being 46. Oil and natural gas also have a high EROI of around 20. The EROI of hydropower is 84, more than four times that of oil and natural gas, while wind power with an EROI of 183 is comparable to these two [14, 16].
3. EROI values in this paragraph are from Reference . As emphasized in the text, there are considerable variations in the values of EROI and other metrics reported in the literature, and these numbers should not be considered the exact EROIs for the particular technology.
As with the other indicators, the estimation of EROI is highly dependent upon the assumptions made in the analysis, the definition of system boundaries, geographical location, and many other factors. Literature review of the topic reveals a wide spread of values, similar to the spread of LCOE values shown in Figure 7.7. Reported EROI values for solar PV range from 5 to 34, while EROIs up to 60 have been reported for wind .
A large number of studies have attempted to answer the questions about EROI for biofuels—ethanol and diesel. Several studies report an EROI of <1 for bioethanol, suggesting that it is, in fact, an energy sink rather than an energy source. On the other hand, an equal number of studies indicate a higher EROI that ranges from being marginally >1 to nearly 9 . An optimistic assessment of lignocellulosic bioethanol suggests that an EROI of ~36 is achievable . Biodiesel typically has an EROI slightly >1 (2–5), though the spread in the EROI is not as large for bioethanol .
EROI is a useful indicator based on a fundamentally sound concept. However, EROI analysis is highly dependent upon system boundaries, assumptions made, and the accuracy of the data used in its determination. It is widely believed that an EROI of at least 3.0 is required for an energy system to be sustainable, and a ratio below this value often implies that the energy system is being subsidized by fossil fuels [19, 20]. Based on this criterion, very few of the biofuel systems, as an example, bioethanol from sugarcane, could be considered truly sustainable .
The indicators discussed in this section—LCOE/LACE, overnight cost, and EROI—are just a few of the scores of different indicators used on the analysis of the energy systems. Each of these indicators provides useful information that helps the policy and decision-makers evaluate different energy technologies.
Renewable energy, while often thought of as a low-carbon or zero-carbon energy, is not devoid of any effects on the environment, primarily associated with the construction and installation of power plants, as well as transportation, and end use. For biofuels such as bioethanol and biodiesel, significant environmental impact occurs during the growth and harvesting of biomass. Sustainability assessment of renewable energy systems needs to include a comprehensive analysis of the impacts of the technology on the environment . The framework for such analysis is provided by the environmental life cycle assessment (LCA) methodology, which evaluates the environmental impacts of a product or service throughout its entire life cycle, from cradle to grave (i.e., from resource extraction to its final disposal). The LCA process is defined in the ISO 14040 series of standards and includes goal and scope definition (defining the system under consideration), inventory analysis (identifying and quantifying system input and output), impact assessment (assessing the effects of the activities), and interpretation (evaluating the results) . The net environmental impacts for the LCA can be measured with the help of the following indicators : (1) Global Warming Potential (GWP): The GWP is calculated in carbon dioxide equivalents (CO2 equivalents), that is, the greenhouse potential of an emission is given in relation to CO2; (2) Acidification Potential (AP): AP results predominantly through the transformation of air pollutants, sulfur dioxide and nitrogen oxides, into their respective acids (H2SO4 and HNO3). The AP is given in sulfur dioxide equivalents (SO2 equivalents); (3) Eutrophication Potential (EP): Air pollutants, wastewater, and fertilization in agriculture all contribute to eutrophication, which mainly refers to enrichment of nutrients in a certain place. The EP is calculated in phosphate equivalents (PO4 equivalents); (4) Ozone Depletion Potential (ODP): Measured in terms of chlorofluorocarbon (CFC) equivalents, ODP refers to the depletion of the ozone layer leading to increased incidence of ultraviolet radiation at earth’s surface; (5) Photochemical Ozone Creation Potential (POCP): Photochemical ozone production in the troposphere, also known as summer smog, is suspected to damage vegetation and material. High concentrations of ozone are toxic to humans. POCP is referred to in ethylene (C2H4) equivalents; (6) Abiotic Resource Depletion Potential (ADP): Measures the depletion of nonrenewable materials in the units of the masses of involved elements; and (7) Radioactive Radiation (RAD): Affecting human health, the effect is expressed in terms of the disability-adjusted life years (DALY). Ultimately, the environmental impacts translate into ecotoxicity, that is, effect on aquatic and terrestrial life and human health, and these also may be quantified, typically in terms of 1,4-dichloribenzene equivalents.
As with energy ratios, the definition of system boundaries has a significant impact on the results of the LCA. Particularly for biofuels used in transportation applications, the cradle-to-grave analysis may reflect well-to-tank (WTT, all activities including growing the biomass until filling the fuel tank of the vehicle) or well-to-wheel (WTW, all activities including burning of the fuel) results. Figure 7.9 illustrates the definition of a system for conducting LCA of a bioethanol process . As can be seen from the figure, significant inputs of fertilizers, fuels, and other agrochemicals are needed to grow and harvest the biomass. The emissions of GHGs and other species may be significant, particularly for the first-generation food crop–based bioethanol production. Emissions are incurred during the transportation of biomass to the chemical plant where chemical conversion of carbohydrates to alcohol is effected through processes described in Chapter 4, Transformations and Chemical Processes in Biomass Energy Systems. Finally, the ethanol fuel is transported through the distribution chain to the end user. Comprehensive accounting of the environmental impact of bioethanol production and use involves consideration of emissions and other impacts during each step of the process. Similar systems can be defined for biodiesel and other biofuels, as well as for LCA of electricity generating renewable energy systems.
Several open source models are available for conducting LCA of any process, system, or product. Most commonly used models include the GREET developed by the Argonne National Laboratory of the U.S. DOE, GHGenius developed in Canada, and BioGrace developed in the EU . Pereira and coworkers used these models as well as the virtual sugarcane biorefinery (VSB) platform to conduct LCA of ethanol production from sugarcane, corn, and wheat. Different models yield different estimates for GHG emissions, with sugarcane having the lowest emissions, ranging from 16 to 45 g CO2-eq/MJ. Wheat and corn had higher emissions that ranged from 45 to 68 and 43 to 62 g CO2-eq/MJ, respectively. A comprehensive compilation of results of a large number of studies for bioethanol production from both first- and second-generation systems has been reported in Reference . The emissions from the first-generation systems are typically higher, with GHG emissions estimates ranging from 20 to 120 g CO2-eq/MJ. Interestingly, higher numbers have been reported for sugarcane and sugar beet. Lignocellulosic biomass–based systems are estimated to have lower emissions that may range from as low as 1.5 g CO2-eq/MJ to 40 g CO2-eq/MJ. Agricultural waste, though, seems to have higher emissions, estimated at 70 g CO2-eq/MJ. Similarly, a process for renewable diesel synthesis from sorghum was simulated by Larnaudie and coworkers  for assessing the environmental impact. The “optimal case” emissions, where a yield of 95% was assumed for each of the processing steps, were estimated to be ~ 69 g CO2-eq/MJ.
In comparison, GHG emissions associated with conventional fossil gasoline and diesel are typically considered to be 93 g CO2-eq/MJ . The vast majority of biofuel environmental impact studies available in the literature indicate that switching to renewable fuels from fossil fuels will result in a reduction of GHG emissions. The reduction may be marginal (<10%) or substantial (>90%), depending upon the definition of the system boundary and assumptions involved in the assessment.
It should be noted that the GHG emissions, or more accurately, the GWP, while possibly the most important one, is just one of the many metrics in the LCA methodology. Renewable energy, biofuels in particular, may have significant impact with respect to the acidification and eutrophication of the environment. The AP and EP of biofuels may be substantially higher than that of conventional fossil fuel, particularly for the first-generation biofuel systems, due to the use of fertilizers and other chemicals in the production of biomass . LCA allows one to identify the major emission points and develop strategy and technologies to improve the performance with respect to the impact on environment.
Electricity-generating renewable energy technologies have also been assessed with respect to their environmental impact, mainly from the perspective of their superior GWP characteristics with respect to the fossil electricity. Figure 7.10 shows the mean and the range of GHG emission values from various sources reported in the literature .
It can be seen that all renewable sources offer significant advantages over the fossil sources, with far lower GHG emissions, and consequently much lower GWP. Wind energy has the greatest potential to reduce the GHG emissions and hence to mitigate climate change. The mean value reported for solar PV, though higher than that for wind, is still an order of magnitude lower than that of coal. However, some studies have estimates of GHG from solar PV that exceed the mean emissions of natural gas power plants. It should be recognized that the estimates of the emissions are highly dependent upon system definition, assumptions made, local conditions, and many other factors.
Environmental impact of hydropower is being examined in greater detail to ascertain whether it can truly be considered a “green and clean” energy source, in light of the large amounts of methane and other GHGs that are emitted during reservoir creation, turbine operation, and dam decommissioning . The GHG emissions for hydropower are the result of emissions during construction, operation, decommissioning, and reservoir emissions stemming from the decomposition of flooded biomass and organic material. The reservoir emissions that include both carbon dioxide and methane, which has twenty-fold higher GWP than carbon dioxide, are the main contributors to the GHG of hydropower dams. Incorporating these emissions in the life cycle emissions for the dams can lead to significantly different results for the GWP of hydropower as shown in Figure 7.11.
The hydropower GHG emissions depend upon not only the type of hydropower but also on the geographical location. The river-in-stream and diversion type of hydropower plants are actually better than wind power. However, the larger hydropower plants are invariably the reservoir type, and reservoir-hydropower plants in tropical regions can be significantly worse than even coal, possibly emitting as much as six times more GHG in their lifetime. These numbers suggest that reservoir-based hydropower would not be a suitable replacement for a fossil power plant in tropical regions from the perspective of reducing GHG emissions. Of course, hydropower is usually not the sole reason for the construction of dams that offer many other benefits including irrigation, water supply, and so on. In any case, detailed analyses should be conducted to obtain more accurate estimates of GHG emissions and other environmental impacts of the dams.
An alternative approach for quantification of environmental impact of energy technologies involves estimating the external costs of energy—costs that are external to the energy market but arise due to deterioration of the environment caused by the emissions from the energy technology. Each type of emission, or pollutant, for example, particulates, CO2, SO2, NOx, and so on, is assigned a monetary value per unit. Estimation of quantity emitted then enables one to assign a total damage cost on that technology. The framework for such analysis has been developed over the last three decades, and Figure 7.12 shows the damage cost of power technologies in the EU .
It can be seen that coal has the highest damage costs arising from both impact on human health and climate change. Wind power and hydropower have the lowest damage costs. Solar thermal is better than solar PV, which has the highest damage cost among all nonfossil sources. Most of this cost is dominated by the impact on human health, and incurred not during the operation of the power plant but during upstream and downstream processing, that is, during the manufacturing and disposition operations. Nuclear, even including the potential costs of accident and waste disposition, is less damaging than solar PV according to this analysis.
Evaluation of energy systems should include quantification of environmental impacts of the system. An overview of various techniques and methodologies used for this purpose have been discussed in this section. It should be realized that the results of the environmental impact analysis are highly dependent upon system definition and assumptions made in the analysis. The numerical results presented above should serve only as broad indicators, and an accurate, detailed analysis must be performed for the specific system(s) under consideration before making any decision regarding the selection of energy technology.
As mentioned in Chapter 1, the energy systems of the future are envisioned to be based on the renewable sources. Climate change concerns are increasingly playing a bigger role, driving the transition from current energy systems to renewable energy systems of the future. Global discussions on this issue over the past few decades have culminated in the Paris Agreement, which exemplifies the consensus reached on the actions needed for countering the effects of climate change through successfully transitioning to renewable energy systems (see the text box).
Significant economic costs are associated with this transition requiring a substantial investment of capital, as well as time and labor, for transforming the vision of renewable energy systems into reality. Energy policies of governments at all levels ranging from local to global have a big role to play in the adoption and acceptance of renewable energy by societies . A brief overview of energy policies of some of the countries/regions is presented below, followed by a discussion of potential strategies to promote the development of renewable energy technologies.
Under the Paris Agreement, the United States had pledged to achieve a 26%–28% reduction in the GHG emissions by 2025 compared to 2005 levels, with the higher reduction level being the preferred target. Such agreed targets are called nationally determined contributions (NDCs) under the UNFCCC. It has several programs to provide incentives for the growth of renewable energy including :
Government financial incentives: The federal government provides incentives, or credits, through programs such as the Renewable Electricity Production Tax Credit (PTC), the Investment Tax Credit (ITC), the Residential Energy Credit, and the Modified Accelerated Cost-Recovery System (MACRS). Federal and state governments have grant, loan, or subsidy programs for the installation of renewable energy equipment.
Renewable portfolio standards (RPSs) and state mandates or goals: Various states have mandatory or voluntary goals requiring a specified percentage of electricity to be generated from renewable energy sources. Electric utilities may use renewable energy certificates or credits (RECs) that can be traded to comply with the RPSs.
Feed-in-tariffs (FITs) and green power purchasing: FITs are special rates, generally higher than electricity rates otherwise available to the generator, that are offered for purchasing electricity from certain types of renewable energy systems. Effectively, this results in the higher rate of revenue for renewable electricity.
Biofuel requirements and incentives: Biofuel (bioethanol, biodiesel, etc.) use for transportation applications is encouraged through federal and state programs. The Energy Independence and Security Act (EISA) of 2007 requires that 36 billion gallons of biofuels be used in the United States per year by 2022. These programs provide financial support and incentives for ethanol and other biofuels producers.
Independent of the policies and goals at the federal level, several states have set their own goals regarding GHG emission reductions, renewable electricity percentages in the energy mix, or transportation fuel usage. For example, the state of California, through the executive order of its governor, committed to the phaseout of fossil fuel vehicles in the state by 2035.
Broadly, the energy policy in the United States operates through financial incentives and local/state/federal mandates or voluntary goals to promote the growth of renewable energy. Overall, the renewable energy sector is showing a consistent and gradual growth in the United States.
The EU energy and climate policies provide a guiding framework for the policies and plans of its individual member nations. The EU updated its energy policy in 2019, stating a goal of energy union of the member nations. Its goal is to have clean energy for all Europeans, with a quantitative objective of achieving 32% renewable energy in its energy mix by 2030, a substantial increase over the share of 18% as of 2018. It is a part of the ambitious European Green Deal (EGD), a set of 50 actions to achieve climate neutrality by 2050 . The member states submitted in early 2020 their National Energy and Climate Plans (NECPs) to the EU, laying out the strategy in their country in order to meet the goals of the EGD. An overview of the plans of Germany and France, the two biggest economies in the EU, is presented below.
Energiewende (energy transformation) is the defining feature of the German energy policies. It involves transforming the German energy system into primarily renewable-based resources and nuclear-free electricity by 2022 . Germany’s Climate Action Plan 2050 sets out to reduce GHG emissions from the 1990 levels progressively by 40% in 2020, 55% by 2030, 70% by 2040, and 80%–95% by 2050. The share of nuclear power in Germany has indeed declined rapidly from a high of ~30% in 2000 to <15% currently, with renewables taking its place. Wind energy is the second largest primary energy source for electricity production in the country. Germany needs to address the electricity transmission issue related to wind power, with most of the generation capacity located in the northern parts of the country, while demand is concentrated in metropolitan and industrial areas in the south and west. While Germany has accomplished a significant reduction in the GHG emissions over the 1990 levels, it remains far from its goal of 40% reduction by 2020, mainly due to coal being the largest primary source of electricity . Natural gas is not a significant energy source for electricity in Germany, and the position is unlikely to change with the instituted energy policies. It is also worth noting that Germany is an energy importer, with domestic production covering only ~30% of the domestic energy consumption .
Recognizant of the fact that it lacked major fossil and other energy sources that left it vulnerable to external suppliers, France aggressively developed nuclear power in the wake of oil crises of the 1970s. It is the only country in the world to generate the majority of its electricity by nuclear energy, which accounts for nearly 75% of all the electricity produced. It is the world’s largest electricity exporter, mainly to other European nations, including Germany, Spain, United Kingdom, Switzerland, and Italy . Renewable electricity generation, primarily hydropower, has increased in France, accompanied by a decrease in fossil—coal, oil, and natural gas—electricity .
In response to the Paris Agreement, France enacted in 2019 the Law on Energy and Climate, committing itself to the goal of climate neutrality by 2050. The law aims to reduce fossil fuel consumption by 60% over the 2012 levels by 2030 in order to reduce the GHG emissions. It has planned the phaseout of coal power plants by 2022. The law also requires France to reduce its nuclear electricity contribution to 50% from the current levels; the target date for this reduction is now set at 2035, revised from the original planned date of 2025 [34, 35]. The law also establishes a High Council for the Climate, an independent body to assess the effectiveness of the government’s climate policies in meeting the energy and climate goals.
China is the single most important country with respect to the impact on the global energy and climate situation. Data presented earlier in the chapter provided the context for China’s share of global energy production/consumption. With respect to the impact on climate, China accounted for ~24% of global GHG emissions in 2012 . As a part of its commitment to the Paris Agreement, China pledged to source 20% of its energy from low-carbon sources by 2030 and to cut emissions per unit of GDP by 60%–65% of 2005 levels by 2030. Carbon dioxide emissions from China are planned to peak by 2030.
Coal is the primary energy source for electricity production in China; however, the share of fossil energy in the primary energy mix has been steadily decreasing. This decrease is being compensated for by the growth of renewables as well as nuclear energy, with the share of renewable increasing from 9.7% to 12.7%, and the share of nuclear increasing from 5.4% to 7.4% from 2014 to 2018 .
China is a planned economy, with its 13th Five Year Plan on energy development formulated in 2017. The renewable energy plan is organized according to the sources—hydro-, wind-, solar, biomass, and geothermal energy . Overall, China plans to have an energy revolution, with cleaner, high-efficiency technologies that counter pollution. China will account for 40% of the global renewable capacity expansion between 2019 and 2024, becoming a leader in distributed solar PV capacity and biofuel production.
The biggest challenge to the reduction of GHG emissions is the large share of coal in electricity generation. Globally, nations are moving toward replacing older, inefficient coal plants with less polluting natural gas plants. However, China’s coal fleet is newer and highly efficient, which results in a lack of incentive to replace units with natural gas or other technologies.
India is third largest energy consumer in the world behind China and the United States. India’s primary energy consumption, driven by its large growing population, modernization, and dynamic economic growth, has nearly tripled over the last three decades. Coal dominates the energy supply, accounting for approximately 45% of India’s total energy consumption in 2018, followed by petroleum and other liquids (26%), and traditional biomass and waste (20%) . Renewables contributed to nearly 16% of the ~1583 TWh of electricity produced in India in 2018. The per capita electricity production is ~1200 kWh, significantly smaller than the levels for China, the EU, and the United States, as can be seen from Table 7.1.
India is a net energy importer, with the domestic supply accounting for only 58% of the total primary energy consumed in the country. India’s energy needs will continue to grow with government policies that emphasize infrastructure development, market liberalization, and energy security. The electricity consumption in India is projected to reach 15,240 TWh in 2040, and the Indian government is planning a 50% contribution from the renewable energy sources. The installed capacity of renewable electricity is ~90 GW as of 2020, dominated by wind and solar sources. India has set ambitious targets for renewable energy production: 227 GW by 2022 (which is greater than commitment to 175 GW under the Paris Accord) and 500 GW by 2030. Of the 225 GW, 114 GW are planned to be from solar, 67 GW from wind, and the rest from hydro- and biopower . India’s ambitious plan also aims to set up 5000 compressed biogas plants by 2023.
Overall, India is making a sustained effort to move away from traditional biomass and waste over the past several years, as well as to boost the natural gas market share at the expense of other fossil sources to reduce air pollution and use cleaner-burning fuels. India’s Ministry of New and Renewable Energy (MNRE) is developing policies and initiatives to incentivize the growth of renewables and substitution of fossil plants, as well as development of clean fossil utilization. India is making great strides toward a cleaner, sustainable, and renewable energy future. With its population of 1.4 billion, India will have a major impact on the global energy market .
Brazil is a key member of the group of countries collectively termed BRICS (Brazil, Russia, India, China, and South Africa) that are expected, along with the United States, to be among the largest economies of the 21st century. A growing middle class and increasing energy demands have resulted in a doubling of the primary energy consumption in Brazil since 1990. However, blessed with abundant natural resources, Brazil is self-sufficient with respect to its energy needs. The domestic electricity production in Brazil was ~600 TWh in 2018, translating into a healthy per capita value of ~2900 kWh , Furthermore, more than 80% of the electricity produced was from renewable sources, most of it from hydropower sources. Hydropower expansion underway would see an addition of 20GW capacity, with a potential to provide a further 175 TWh per year at maximum capacity. The remoteness of the remaining hydropower resource and environmental sensitivity at the locations are likely to constrain further expansion of hydropower. Overall, renewables meet nearly 45% of all the primary energy needs in Brazil, making it one of the least carbon-intensive economies in the world.
As seen from Figure 7.5, Brazil is among the top producers of transportation biofuels—both bioethanol and biodiesel. Successive governments in Brazil have consciously pursued a policy of promoting the use of bioethanol in the transportation section, for both reducing the dependence on imported petroleum and solving the problem of ethanol overproduction from sugarcane. The ethanol blending level in gasoline was fixed at 20% v/v by the government in 1979. Since 2003, the flex fuel vehicles (FFV) can operate with any mixture of hydrous ethanol (up to 4.9% v/v water) and gasohol, which itself is a blend of 18–27.5% v/v anhydrous alcohol and gasoline . Nearly 80% of the automobile fleet in Brazil is expected to consist of FFVs by 2030. It should be noted that while Brazil is a major producer of bioethanol, this production is seasonal with the highest production during the period of sugarcane harvest (October–December). It generally imports some ethanol at other times, primarily from the United States. Recent large offshore oil and gas discoveries and successful development of these fields have turned Brazil into a major producer and net oil exporter, with exports expected to be >1 million barrels per day by 2022.
Brazil’s NDC under the Paris Agreement has a stated goal of reducing the GHG emissions by 43% of its 2005 levels by 2030. It plans to increase the share of biofuels to 18% of the energy mix, increase the capacities of nonhydropower renewables, and implement policies for protecting the Amazon rainforest .
The benefits of renewable energy over other energy sources are well understood by societies and nations. However, widespread acceptance and growth of renewable energy are heavily dependent upon the affordability, reliability, security, and accessibility of the energy for the general population. Several tools are available to policymakers and governing entities to encourage the public to adopt renewable energy. Some of these tools, mentioned briefly in Section 7.4.1, are elaborated upon below.
FITs are effectively guaranteed contracts that ensure the renewable energy generators are able to receive a specified rate from the utilities for the power supplied. The rate is typically higher than the retail price of electricity in that market, providing the incentive for shifting to a renewable energy source from other sources. FITs are characterized by long-term contracts that ensure a guaranteed access of renewable electricity to the grid at attractive prices . FITs are highly effective in facilitating the growth of distributed PV systems by providing a guarantee to the customers who own such systems that they will be able to receive a set price from their utility for the electricity they generate in excess of their demand. FITs are used commonly internationally, but only to a limited extent in the United States. The high price guaranteed in FITs may result in excess capacity, making the program economically unsustainable, as was experienced in Spain in 2012 .
Governments and regulatory agencies can institute RPSs, also called renewable electricity standards (RESs), that specify a minimum threshold for the share of renewable energy in the energy mix in their jurisdiction. RPS can be mandatory and enforceable or voluntary, with the contribution of renewables encouraged. Several U.S. states have such RPSs, though there is no RPS at the federal level. The state of California, for example, has an RPS of 65% by the year 2030, with a goal of carbon-free electricity by 2045. Many state policies also provide a trading mechanism for generators who exceed their RPS requirements to sell their renewable electricity credit (REC) to other generators who are unable to meet their own RPS requirements.
Individuals and corporations earn tax credits for the generation of renewable electricity, investments into such technologies, or purchase of equipment. In addition to the federal taxes in the United States, all the states offer various other incentives. The number of such programs offering financial incentives ranges from a low of 10 to a high of 148 across the different states.
Several countries (also local governments) use a carbon pricing mechanism to shift the cost of damage on to the producers of carbon or GHG emissions. The two most common avenues employed in carbon pricing include a carbon tax, wherein a direct cost is imposed on the carbon content of emissions or source fuel, and an emissions trading system, wherein the total GHG emissions are capped and the interplay of supply–demand forces establishes a market price for the emissions. The emission cap ensures that the damage due to GHG emissions is limited, and the cost associated with the emissions may incentivize the generators to transition to a less emitting source. Other carbon pricing techniques involve indirect fuel taxes, removal of subsidies, and so on. Presumably, carbon pricing will set in motion the market forces that will drive innovation and accelerate the development of renewable energy technologies.
Several other policy tools are available for facilitating the growth of renewable energy systems. The applicability of any tool is dependent upon the specific conditions prevailing in the particular energy market.
Renewal energy sources account for nearly one-fourth of the electricity generated worldwide. However, the energy mix varies widely across the countries and the different regions of the world. Renewables lead the other sources in electricity generation in the EU, while its share lags behind those of coal and natural gas in the United States and most other countries/regions. The energy mix of China, the largest energy producer/consumer in the world, is dominated by coal. Hydropower is the largest source of renewable electricity worldwide, followed by wind power. Biofuels synthesis is primarily based on the first-generation systems, with the United States and Brazil being the two major bioethanol producers. The top two positions for biodiesel/renewable diesel are occupied by the EU and United States.
The performance of the renewable energy system can be quantified on the basis of physical, economic, environmental, and societal indicators. Some of the important indicators include LCOE, LACE, overnight cost, and EROI. The values of these indicators for various energy systems are highly dependent upon system boundaries and the assumptions made in the analysis. The results of the analysis are invariably specific to the particular geographical location and situation.
Environmental impacts of the energy systems can be analyzed through the LCA methodology. Such analysis typically focuses on the GHG emissions; however, there are several other impact categories that must be included in a comprehensive analysis of any system. The impact could be valorized for establishing a basis for comparison among different competing energy technologies by assigning monetary values to the environmental damage caused by the specific pollutants.
Practically all the countries of the world have expressed their commitment to an energy future where renewable energy systems play a major role. Most of the countries have formulated their goals toward this energy transition and have developed/are in the process of developing plans to accomplish these goals. Energy policy has a critical role to play in the transition to renewable energy systems, and policymakers and governments have a number of tools at their disposal to incentivize/force this transition. Continuous evolution of technologies, coupled with the strategic policies of the nations, will help realize the renewable energy future.
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7.1 Discuss the similarities and differences in primary energy sources used for generating electricity across the various regions/countries as shown in Figure 7.2. What have been the changes in the distribution of primary sources since 2018? Obtain the latest data from the information sources mentioned in the book. What discernible trends can be identified?
7.2 Comment upon the importance of various renewable energy sources for electricity generation for different regions. Use the information presented in Figure 7.3 or the latest data obtained from the energy information sources.
7.3 What would be the increase in the world electricity demand if the per capita generation in the rest of the world is to reach the same level as the United States? What would be the increase if the generation in Asia (excluding China) and Africa is to reach 50% of the per capita generation as the EU?
7.4 What would be the % growth needed in biofuels for complete substitution of fossil fuels by biofuels? Refer to Reference 4 (or another latest resource) for the data needed.
7.6 Comment upon the merits and demerits of LCOE and LACE.
7.7 Calculate the capital investment needed for a 1000-MW power plant using the overnight cost information presented in Figure 7.8. A single plant of such capacity may not be possible with some of the primary sources. In that case, how many identical units will be needed to achieve the desired capacity?
7.8 Compare the different EROIs used in the energy systems analysis.
7.9 What are the principles of LCA? Define system boundaries for (1) biodiesel, (2) renewable diesel, (3) wind power, and (4) geothermal electricity based on an organic Rankine cycle for conducting LCA.
7.10 Is hydropower a clean energy alternative? Discuss.
7.11 How will the answer to question 7.5 change if the damage cost is included in the analysis?
7.12 Discuss the relative merits of incentives and penalties as strategies for promoting renewable energy.