Renewable Energy Incentives Research Articles

Assessing potential for policy feedback from renewable energy incentive programs

Climate advocates look optimistically to policy feedback as a mechanism for locking-in a decarbonization policy trajectory, but little research has examined whether and how climate legislation creates constituencies that could provide future political support. This article focuses on incentive programs supporting investment in solar PV and the potential for policy feedback through participating households. We first develop a framework of feedback potential that considers the volume and partisanship of incentive program beneficiaries and their distribution across electoral districts. We then apply the framework to New York State’s solar PV incentive program, which enabled over 140,000 households to install solar PV. We find that the number of solar PV incentive beneficiaries is positively associated with Republican vote share, suggesting potential for a strong pro-solar constituency in the pivotal, Republican-led districts. Within electoral districts, however, beneficiaries skew Democratic, raising questions about the direction of policy feedback. The results carry implications for the kind of politics that incentives in the Inflation Reduction Act may set in motion in the coming years.

Development of a coupled agent-based generation expansion planning tool with a power dispatch model

Power companies need to adapt their generation expansion planning in response to changing market, climate and regulatory conditions as global warming, electrification, and technology breakthroughs continue. To fortify energy system resilience, it is critical to understand the collective effects of their autonomous decisions on power systems operations and reliability. To this end, we developed an integrated framework, an agent-based model (ABM) coupled with a power dispatch model (PDM) (referred to as ABM-PDM), tested on the Texas 123-bus transmission system in the Electric Reliability Council of Texas (ERCOT) region. Agents (power generation companies) can invest in natural gas, solar, and wind technologies to maximize profits from 2021 to 2050, using market information from the PDM based on their capital budget and perceived costs, financial incentives for renewable energy, and climate risks. We applied ABM-PDM to assess how power companies respond to future technological advancements and climate change. After demonstrating model credibility, we explored 25 combinations of cost and capacity factors reflecting a variety of technological evolution trajectories. Results indicated that to replace wind over solar for replacing existing fossil-fuel power plants due to lower costs and higher capacity factors. Additionally, as more agents invest, the energy market becomes more competitive, and system-wide electricity prices drop. We also analyzed the impacts of temperature increases on investments using seven projections, from 0 to 6 °C, during the modeling period. The results showed that as temperatures rise, agents invest more to accommodate the increasing loads. ABM-PDM incorporates risk attitude and learning into companies’ decision-making, providing additional information on generation expansion for the non-optimal future of power systems.

Renewable energy policy performance and technological innovation in Africa: A Bayesian estimation

This paper examines the effect of renewable energy policy performance on innovation activity in the renewable energy sector in a sample of thirty-three African countries during the period 2010–2021. The policy performance we use covers carbon pricing, incentives for grid-connected and distributed renewable energy generation, fiscal incentives for renewable energy, legal framework for renewable energy, off-take risk, network connection and pricing, and policy design attributes. Using patent data and renewable policy performance to fit a Bayesian negative binomial, our results generally show that renewable energy policy in the region supports technological innovation in the sector. Policy initiatives focused on market-based incentives (auctions and tariffs), renewable portfolio standards, risk mitigation, network connection and pricing are largely responsible for a strong and statistically significant relationship between renewable energy policy and innovation activity. We also find evidence that intellectual property rights, renewable energy capacity, electricity prices, affordability of renewable energy, and openness to trade proxies are important drivers of innovation activity in the renewable energy sector. Our analysis finds no evidence that research and development is a significant determinant of renewable energy innovation in African countries. Our results serve to inform policymakers on the areas in which specific policy actions are most effective at promoting innovation in the renewable energy sector.

Modelling the factors influencing carbon efficiency of consumer choice to promote energy-efficient vehicles

This study investigates the main factors influencing carbon emissions from Four Wheel Passenger Vehicles (FWPVs) in Sri Lanka, an emerging economy where the transport sector contributes 12 % of total emissions. Pioneering a new methodology, we integrate System Dynamics (SD) modeling and decomposition analysis to comprehensively map the factors affecting fuel efficiency for the first time in Sri Lanka. Employing the additive Logarithmic Mean Divisia Index (LMDI I), we analyze a comprehensive time series dataset covering all petrol, diesel, and electric-powered FWPVs registered between 2015 and 2019. Our study delves into significant drivers of CO2 emissions, including population dynamics, vehicle ownership trends, annual travel distances, fuel types, engine capacities, and technological advancements. Additionally, we quantify the impact of fiscal policies on FWPV emissions, revealing a surge in emissions in 2018 and 2019 driven by consumer preferences for high-capacity vehicles. Our findings offer critical insights for crafting effective policies to promote energy-efficient vehicles and mitigate carbon emissions in the transport sector, emphasizing the importance of targeted fiscal measures. By imposing taxes on high-capacity vehicles and incentivizing the adoption of low-emission options through tax variations and renewable energy incentives, policymakers can influence consumer behavior and drive significant emission reductions. Our study underscores the need for ongoing monitoring and evaluation of fiscal policies to refine existing measures and accelerate the transition towards a sustainable, low-carbon transportation sector in Sri Lanka.

Assessing the Impact of Renewable Energy in Mitigating Climate Change: A Comprehensive Study on Effectiveness and Adaptation Support

The objective of this study is to evaluate the effectiveness of renewable energy in combating climate change and supporting adaptation efforts. By applying the ARDL model to data from 58 countries spanning the period from 1990 to 2022, this study sheds light on the opportunities and challenges associated with this involved relationship. The results indicate that renewable energy plays a significant role in reducing greenhouse gas emissions and mitigating temperature anomalies. Specifically, wind energy, biomass, geothermal energy, solar energy, and waste utilization demonstrate a positive correlation with greenhouse gas emission reduction. Moreover, wind energy, solar energy, waste utilization, and the proportion of renewable energy in primary energy consumption are also linked to a decrease in temperature anomalies. These findings emphasize the importance of implementing concrete measures such as promoting sustainable transportation, ensuring sustainable management of natural resources, raising awareness and enhancing education, increasing subsidies and incentives for renewable energy and strengthening regulations on greenhouse gas emissions.

Renewable Energy Incentives and Future Implications for Turkey: A Comparative Bibliometric Analysis

Many countries are using incentives to increase domestic and renewable energy (RE) production, which is important for sustainable development and meeting the rising demand for energy. This also helps achieve zero-carbon emission goals and reduces dependency on foreign sources. Countries have made progress using renewable energy with provided incentives. Along with political and economic regulations, scientific research is crucial in raising public awareness to foster innovation. Through academic studies on renewable energy and policy, countries can create better policies and investments while promoting environmental awareness for a sustainable future. A comparative analysis of academic outputs on incentives and policies for green energy is important. This research examines the link between RE use and academic production. To this end, a bibliometric analysis of scientific publications from Turkey, Germany, France, Spain, and Italy was employed to understand the current state policies and suggest future studies. The academic studies that were compiled with the keywords in the RE policies and measures in the Web of Science database have revealed that academic productions increase quantitatively as RE investments increase. The thematic analysis shows that the maturity in RE use is also reflected in scientific research.

THE EFFECT OF WIND ENERGY ON CARBON EMISSIONS

The advances in economies require the need to consume more energy. Non-renewable energy resources produce high amount of carbon emissions. With global warning concerns, reducing greenhouse gas emissions is priority. The research question is how effective wind energy is for reducing carbon emissions. This study includes a panel data analysis to test the effect of wind energy on carbon emissions. The variables used in this article are installed capacity of wind energy production, the ratio of wind energy consumption to primary energy consumption, and the ratio of wind energy production to total electricity consumption, real GDP and total population. According to the results, the increase in the ratio of wind energy consumption to primary energy consumption reduces carbon emissions. There are 33 countries available in this research which are divided into two categories; countries with higher than average and countries with lower than average. The effect is more significant for countries with higher than average carbon emissions. GDP is significant for carbon emissions but population is not significant according to the results. According to short run results, Installed capacity of wind energy production is not statistically significant. Coefficient estimation for the ratio of wind energy production to total electricity consumption is negative and statistically significant for all countries. The ratio of wind energy consumption to primary energy consumption reduces carbon emissions. The results are consistent with the literature. More incentives for renewable energy and wind energy in particular, would be beneficial for environmentally and economically sound investments.

Economic policy uncertainty and carbon neutrality in China: Do sustainable energy and eco‐innovation make a difference?

AbstractSimilar to many other developing and developed countries, China grapples with the challenge of balancing economic growth and environmental preservation. This study, anchored in Sustainable Development Goals (SDGs) 7, 11, 12, and 13, investigates the impact of eco‐innovation and sustainable energy on CO2 emissions (CE) in China from 1980 to 2020, using the STIRPAT model. Employing the autoregressive distributed lag (ARDL) model with bootstrap rolling window causality analysis, we uncover causal relationships between CE and its determinants, assessing them in sub‐sample periods. ARDL estimates reveal that economic policy uncertainty, economic growth, and urbanization increase CE, while eco‐innovation and sustainable energy decrease it. Time‐varying causality analysis demonstrates predictive capabilities of all independent variables at various sub‐periods. The study recommends substantial increases in subsidies and tax incentives for renewable energy, emphasizing stable ecological policies, irrespective of economic conditions, for lasting benefits.

Household willingness to pay for various attributes of residential solar panels: Evidence from a discrete choice experiment

The predominant approach in the US environmental policy so far has been to offer financial incentives for renewable energy as a more politically palatable alternative to market based policies. The policies around residential rooftop solar have generally aligned with this approach. However, recent years have witnessed a reversal in the once favorable financial terms for residential solar energy in many states largely due to concerns regarding unfair cost shifting and efficiency. Consequently, solar vendors appear to increasingly hinge their marketing strategies on the narrative of “self-reliance”. A pertinent question is whether there is enough willingness to pay for such non-market, private benefits to sustain the growth of residential solar. To address this, we designed and implemented a discrete choice experiment within a stated preference framework. Respondents were asked to make a choice among different home energy options offering varying financial terms and other attributes such as self-reliance and home battery. Notably, a random subset of the respondents was presented with the net present value (NPV) of the dollar cost of each alternative, while this information was withheld from the rest of the sample. We estimated the utility coefficients through hierarchical Bayes (HB) mixed logit and subsequently derived the marginal willingness to pay (mWTP) for each attribute, along with their individual-level confidence intervals. Our findings indicate substantial heterogeneity in preferences among decision-makers. On average, the willingness to pay for self-reliance falls short of supporting residential solar growth without financial incentives. Furthermore, respondents exposed to NPV information exhibited significantly lower mWTP values, underscoring the potential efficacy of NPV information in improving willingness to pay estimates within investment-oriented settings.

Study on sustainable development of electricity resources in the United States

Relying on renewable electricity generation is critical to combating climate change and meeting long-term environmental objectives. In addition to discussing the Triple Bottom Line approach’s practical applications, this essay delves into the approach’s theoretical underpinnings. Companies like Tesla and the financial industry play crucial roles in encouraging the responsible growth of the nation’s electrical power grid. This essay argues that sustainable behaviours and investments in renewable energy can benefit from fiscal and economic policies that give incentives in these areas. In addition to contributing to Tesla’s market leadership and financial success, sustainable business practices can also help set an example for other companies. Incentives for renewable energy, increased energy efficiency, and a receptive regulatory environment are all recommended in this essay. The competitiveness of electric power companies may be increased, and their contributions to sustainable development may be increased via the incorporation of sustainability principles, circular economy practices, and stakeholder engagement.

Electrifying the Transportation Sector: Implications for the Oil and Gas Industry

This review article explores the implications of electrifying the transportation sector for the oil and gas industry. The current state of the transportation sector and the role of oil and gas in it are discussed, followed by an introduction to the concept of electrification and its potential benefits and challenges. The article analyzes the potential impacts of electrification on the oil and gas industry, including changes in demand for oil and gas and opportunities for investing in renewable energy and developing new technologies. Several case studies of companies in the oil and gas industry that are adapting to the transition to electrification are presented, including those investing in renewable energy and developing electric vehicle charging infrastructure. The role of government policies and regulations in the transition to electrification is also discussed, including incentives for electric vehicles and renewable energy and their potential impact on the oil and gas industry. The article concludes with a summary of the potential implications of electrifying the transportation sector for the oil and gas industry, along with recommendations for how companies in the oil and gas industry can adapt to the transition to electrification. Overall, the article provides a comprehensive overview of the electrification of the transportation sector and its impact on the oil and gas industry, offering insights and recommendations for industry stakeholders.

Renewable energy incentives for project owners representing communities with heavily subsidised fossil fuel-based electricity

The significance of renewable energy (RE) as an essential component of sustainable cities is widely acknowledged. Nevertheless, the global transition towards RE faces numerous hurdles, including RE financing, particularly in regions where electricity generation from fossil fuels is heavily subsidized. This necessitates the formulation of effective incentives that can encourage project owners to invest in the transition towards RE. This manuscript proposes a comprehensive framework for incentivizing RE project owners and offers three types of incentives: capital-based, production-based, and grid support incentives. The effectiveness of the proposed set of incentives is evaluated through a detailed techno-economic analysis which aims to minimize Net Present Cost while considering power balance and grid constraints. It encompasses various aspects of RE systems, including optimal sizing of photovoltaics, batteries, inverters, and optimal power flow, at different levels of RE penetration. Additionally, the framework explores the possibility of achieving 100 % RE through off-grid systems, shedding light on potential challenges and opportunities. Further, economic indicators such as the Cost of Energy, Payback Period, Return on Investment, and Internal Rate of Return are also analyzed to evaluate the acceptability of the proposed framework. Results demonstrate that the presented incentivizing framework has the potential to facilitate RE adoption, positioning it as a valuable policy and investment opportunity for RE project owners. This yields substantial benefits including reduced financial burdens, improved return on investment, and access to diverse revenue streams.

Digital trade growth and mineral resources In developing countries: Implications for green recovery

In this study, the influence of e-commerce market size and the consumption of mineral resources on sustainable growth in 15 developing Asian countries from 1995 to 2021 is evaluated using the Arellano-Bond dynamic Generalized Method of Moments (GMM). The findings indicate that a 1% increase in mineral consumption could result in a 0.25% reduction in green growth due to ecological harm. Similarly, a 1% growth in the urban population may lead to a 0.14% decline in green growth owing to heightened resource demand and emissions. Conversely, a 1% rise in unemployment rates might lead to a 0.29% decrease in green growth. On the other hand, a 1% increase in foreign direct investment (FDI) could correspond to a 0.15% increase in green growth, and a 1% growth in the e-commerce market could result in a 0.54% increase due to improved resource utilization. To encourage green growth, developing economies can enhance their digital trade infrastructure, enforce resource efficiency standards, provide incentives for renewable energy, foster progress in green technology, and establish markets for green finance.

Reinvestigate the significance of STRIPAT and extended STRIPAT: An inclusion of renewable energy and trade for gulf council countries

The rapid growth experienced by the Gulf Council countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) has placed significant strain on their ecological footprint due to extensive energy consumption. Consequently, it becomes necessary to examine the factors contributing to the high ecological footprint and explore potential solutions for its reduction. This study aims to analyze the key factors influencing the ecological footprint in the GCC countries from 1995 to 2020. Through an extensive review of existing literature, it is evident that economic growth, urbanization, and trade can disturb ecological balance, while environmental technology and renewable energy offer potential remedies for environmental challenges. Thus, these variables have been selected as independent factors for investigation. The results obtained from advanced panel techniques emphasize the significance of adopting environmental technologies and increasing the utilization of renewable energy sources in order to decrease the ecological footprint. Conversely, economic growth, urbanization, and trade are identified as crucial drivers of environmental degradation. Considering that the GCC countries heavily rely on oil and petroleum exports, as well as non-renewable energy sources for their economic activities, the positive relationship between economic growth and trade is to be expected. The results propose multifold recommendations: (i) providing incentives for renewable energy and (ii) prioritizing the implementation of clean technology over traditional technologies.

The importance of classification in reducing the congestion price in peerto-peer energy trading

Peer-to-peer energy trading is a model in which energy can be exchanged directly betweenenergy producers and consumers. This model offers an innovative approach to energy markets. Intraditional energy trading models, energy producers collect energy at a single point and then distribute it toconsumption points. However, with peer-to-peer energy trading, energy producers can offer energy directlyto consumers, thus reducing the costs of intermediaries and distribution networks. [1], [12]The importance of the peer-to-peer energy trading model comes from several aspects: Energy Efficiency,Renewable Energy Incentives, Flexibility and Reliability etc.Peer-to-peer energy trading allows the energy system to become more decentralized and more sustainable.However, an appropriate classification and regulation is necessary for peer-to-peer energy trading to workeffectively. [2]The most important of these classifications is the distance category. Distance and peer-to-peer energytrading offers a new paradigm for efficient and sustainable energy distribution. Compared to traditionalenergy distribution models, this new approach allows energy consumers to exchange energy amongthemselves. This aims to provide a more flexible, efficient, and environmentally friendly energydistribution. [3], [13]In this study, I made simulations to see how the distance could have an effect on the energy trade betweenpeers, and as a result of the simulations, the distance and arrangement of consumers from each other wasexamined. As a result, the regulation of consumers has proven to have an effect on trade, and theclassification of consumers shows that it has a large effect on lowering the congestion price.

Feed-in tariffs and the carbon emission trading scheme under China's peak emission target: A dynamic CGE analysis for the development of renewable electricity

Thermal power industry is one of China's leading sources of carbon emissions. China has launched a national carbon emissions trading scheme (ETS) and renewable energy incentive programs to achieve its peak emission target by 2030. However, since 2021, China no longer provides a central feed-in tariff (FIT) for new centrally located solar photovoltaic (PV) power plants, commercial and industrially distributed PV projects, and newly approved onshore wind power projects. This change in policy may threaten China's carbon reduction targets and economic development. Using a dynamic computable general equilibrium (CGE) model, we assess the combined effects of carbon ETS and FIT on China's electricity sector, carbon emission peak target, renewable energy and economic development. In terms of policy overlap and integration, we analyze the impact of these policies and estimate how to coordinate FIT and carbon ETS policies to ensure their effectiveness. Results show that the overall effects of FIT subsidies are superior to phasing-out FIT scenarios. The fiscal pressure caused by FIT is lower than its actual expenditure because it stimulates economic activity and boosts government revenue. However, considering the multiplier effect of the FIT on promoting government revenue growth and GDP growth, the most effective FIT should be terminated in 2025, followed by subsidies ending in 2030 and 2035.

Techno-economic optimization of a renewable micro grid using multi-objective particle swarm optimization algorithm

Global warming and energy security concerns have attracted research efforts toward renewable micro grids. Since micro grids possess multiple energy sources with different availability states and required costs, optimization practices could be helpful in their sizing and scheduling. In this study, multi-objective particle swarm optimization algorithm was employed on three renewable micro grid configurations for Shiraz climate, Iran. The considered micro grid configurations were wind turbine (WT) and combined heat and power (CHP) system, photovoltaic (PV) and CHP and PV, WT and CHP. The micro grid was assumed to be connected to gas and electricity networks and excess produced electricity was considered to be sold to the grid. Loss of power supply probability and the cost of energy per unit were considered as the optimization objective functions. The acquired results revealed that only employing WT could significantly increase the reliance on the power grid due to the low availability of wind energy in the climate. Since the climate possesses high levels of solar insolation, adding a PV system to the configuration significantly decreased the electrical load supplied by the grid. The cost of energy per unit for each scenario was acquired to be 0.266 USD, 0.235 USD, and 0.247 USD. The calculated optimum loss of power supply values were 0.285, 0.3218, and 0.207 for the three scenarios, respectively. While the cost of each energy unit was higher for the third scenario as compared to the second scenario by 5%, the share of demand load supplied by renewable sources increased by 20%. Simultaneous utilization of wind and solar energy was shown to be more beneficial, especially if carbon tax policies or renewable energy incentives were to be considered for future applications.

Blockchain adoption and security management of large scale industrial renewable-based systems: Knowledge-based approach

Smart networks, e.g., smart grids (SGs) as complex interconnected systems have become more complex and require greater processing and communication capabilities due to the growing use of renewable energy (RE). In addition to being a reliable method for collecting and managing information, wireless networks (WNs) are capable of enhancing the performance of RE management. As a result of wireless data transfer risks and centralized power trades, SGs using WNs are unable to provide the security of the electricity market or ensure a high level of RE utilization. Blockchains (BCs), which are new technologies that enable data sharing, are gaining popularity, and it is thought to be able to address these issues. A BC-based, reliable power-exchange scheme is presented for SGs using WNs in this study. Using the BC for recording power data obtained from the WNs allows the smart contract for making appropriate trades according to the information. Energy trading and RE consumption are more efficient in a dual-chain architecture that consists of local energy trade BCs and RE trade BCs. A BC-based RE incentive framework is designed to have greater stability and scale among RE producers. Overall, the proposed technique not only can provide higher security and reliability to the system but also can mitigate fraud, as well as providing less operation cost for the system. Ultimately, the 56-bus test feeder layout is used to validate the framework.

A Principal-Agent Approach for the Effective Design of a Renewable Energy Incentive for a Heavily Subsidized Residential Sector: The Case of Qatar

Qatar’s per capita electricity consumption is one of the highest in the world, mainly due to the availability of heavily subsidized electricity. The residential sector alone accounts for 60% of produced electricity. The effectiveness of imposing regulatory measures that aim to reduce consumption, such as carbon pricing and rebates, depends on the design of the introduced policy, region dynamics, and population characteristics. Using principal-agent theory, this study addresses the agency problem between the government and households by proposing a policy that aims to incentivize households to shift towards renewable energy sources and reduce their overall energy demand. The study quantifies the potential impact of the policy over a period of five years and estimates that 495 GWh of electricity could be saved, resulting in a significant reduction of 203,710 Tons of CO2e emissions. The cost of implementing the policy is estimated to be 0.838 billion Qatari riyals. The effect of varying model parameters on incentive design is investigated, and a detailed financial analysis is conducted based on the redirection of saved energy resources from domestic consumption to international exports of gas and electricity.

Um modelo baseado em blockchain para ofertas de certificados token de energia renovável

ABSTRACT This article proposes an investment model for a renewable energy generator that allows it to earn the right to issue Renewable Energy Certificates (RECs) and sell them through quarterly sales auctions promoted by the blockchain. Blockchain technology can further promote the RECs market, as it enables tokenization and distribution of certificates. We did not find articles in the literature that analyze the decision to invest in decentralized autonomous organizations (DAOs) that have rules for issuing and trading RECs specified in smart contracts, which are executed and validated by the blockchain. This article contributes to the literature on blockchain technology applications in the renewable energy market by proposing issuing and selling RECs tokens through a DAO. The relevance of this research is that it shows that simple real option pricing methods can help decision-makers evaluate investment opportunities under uncertainty and flexibility. The tokenization and distribution of RECs via blockchain can promote transaction agility, reduce or eliminate bureaucracy in the means of payment, and increase the security and transparency of transactions. We propose a model for issuing and selling RECs in smart contracts. We assume that the generator has the flexibility to invest now or in one year to enter the platform, considering the energy generated in one year by a single typical 4MW wind turbine. Our model assumes that the price of the REC token follows an inverse demand function subject to stochastic shocks. The results contribute to the understanding of the performance dynamics of digital products under uncertainty and flexibility and show that distributed ledger technology (DLT) may be a viable alternative for renewable energy incentives.