Feed-in Tariff Program Research Articles

Renewable Energy Support Through Feed-in Tariffs: A Retrospective Stakeholder Analysis

Abstract This study develops a generalized evaluation framework that can be used to quantify the financial, economic, stakeholder, and environmental impacts of renewable energy support programs. The application of this framework is demonstrated by evaluating the feed-in tariff (FIT) program for solar distributed energy resources (DER) in Ontario, Canada. Our analysis reveals that Ontario’s FIT program has successfully promoted the adoption of solar DER across communities. However, the program has caused inequitable societal outcomes through a cross-subsidization with a present value of 9 CAD billion, paid for by the electricity consumer base for the benefit of only the 0.06 percent of electricity consumers who could install solar systems. The cost imposed on the Canadian economy ranges from 2.86 to 5.37 CAD billion, depending on the discount rate applied. The sensitivity analysis results indicate that the burden of this program on the Canadian economy would have been reduced by 50 percent if the program had been delayed and implemented in 2016 instead of 2010 due to the declining trend in solar system investment costs. The lessons from this analysis provide insights for designing future environmental and emission reduction policies.

Performance monitoring as fault detection approach on AC power output of monocrystalline grid-connected photovoltaics system

As per the Malaysian sustainable energy development authority (SEDA), Malaysia has seen a significant growth in renewable energy thanks to the feed-in tariff (FiT) program. However, photovoltaic (PV) systems in tropical countries like Malaysia experience degradation due to technological factors and operating conditions. The effectiveness of PV systems is influenced by geographical location and weather conditions. This research study conducted a comparative analysis between the actual power output PAC_actual and the predicted power output PAC_expected, referred to as the acceptance ratio (AR). The study also assessed the yield and performance ratio (PR) of a PV system situated at the green energy research center (GERC) in Universiti Teknologi MARA, Malaysia. The actual monocrystalline grid-connected photovoltaic (GCPV) system versus predicted AC power and AR were monitored over a year, with MATLAB software used for simulating output power based on real data. According to the Malaysian Standard MS2692:2020, an AR value of 0.9 or higher is required for approval in testing and commissioning tests. The findings indicate that most AR graphs fall below this threshold, and the PR value for each month is below 0.75, suggesting a need for significant system overhaul.

When Haste Makes Waste: Fair And Equitable Treatment Violations in Canada's Feed-in Tariff Program Implementation and Lessons for Vietnam

When Haste Makes Waste: Fair And Equitable Treatment Violations in Canada's Feed-in Tariff Program Implementation and Lessons for Vietnam

Data-Driven Detection of Electricity Theft Cyberattacks in PV Generation

Most of the existing research focuses on electricity theft cyberattacks in the consumption domain. On the contrary, a high penetration level of distributed generators (DGs) may result in increased electricity theft cyberattacks in the distributed generation domain, which is the focus of this article. In these attacks, malicious customers can hack into the smart meters monitoring their DG units, which are usually photovoltaic, and manipulate their readings to report higher injected energy to the grid and claim more profit under feed-in tariff programs. This article proposes a data-driven approach based on machine learning to detect such thefts. We adopt an anomaly detection approach where a theft detection unit (TDU) based on a regression tree model is designed to detect suspicious data. Historical records of solar irradiance, temperature, and smart meter readings are utilized in the training stage of the detector. The probability density function of the error between the actual readings from DG meters and the predicted generation by the regression model is utilized as a metric to detect suspicious data. Several theft scenarios are used to assess the performance of the TDU. Furthermore, a comparison study with other detectors is presented to demonstrate the superiority of the proposed TDU.

Merit Evaluation of Peer‐to‐Peer Electricity Trading Between Prosumers

The enforcement of a feed‐in tariff (FIT) program in Japan has increased the number of installations of photovoltaic generation systems in its residential sector. After the end of an FIT program, the surplus electricity of an individual prosumer is purchased by the utility company at a reduced price, which may have an economic impact on the prosumer. To avoid this adverse effect, peer‐to‐peer (P2P) electricity transactions among prosumers based on blockchain and smart contract technologies as well as introduction of residence‐use stationary storage batteries are generating significant interest. In this study, the potential economic merit of P2P transactions and residential storage battery introduction are evaluated using a total optimization approach. For realizing a more practical perspective, this study also investigates the economic merit based on a partial optimization approach, in which an individual prosumer pursues its own profit. Furthermore, in this study, the grid‐side merit of P2P electricity transactions among prosumers is examined. Comparison of the merits determined by the total and partial optimization approaches shows that the realization of P2P transactions could provide a notable economic merit to the participants and reduce both the required facility capacity and power flow variation. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

The impact of feed-in tariff degression on R&D investment in renewable energy: The case of the solar PV industry

Feed-in tariff (FIT) is a broadly used policy instrument around the world, in which the payment level is always designed to decline gradually in order to track and encourage technological improvement in renewable energy. However, the potential adverse effects of tariff degression on renewable energy research and development (R&D) investment have not been sufficiently addressed. In this paper, we explore the impact of FIT payment degression on renewable energy R&D investment and analyze the efficient FIT payment structure for R&D investment. We form a modeling framework that captures the dynamics of FIT payment levels and the inventor's strategic reactions to tariff changes. In this framework, we model the inventor's optimal R&D investment decisions based on the canonical real option approach and simulate the impact of FIT payment degression on R&D investment and the efficient FIT payment structure under different R&D characteristics using the case of the solar photovoltaic (PV) industry. Our results emphasize the adverse effect of tariff degression on the commercial value of new renewable technology and hence the inventor's incentive in R&D investment, especially when facing more technical uncertainty and financial constraints. Our model could help policymakers to design an efficient FIT payment structure through which the cost of the FIT program is restricted to a minimum level but without influencing the inventor's R&D investment decisions. • The impact of FIT changes on renewable energy R&D investment is explored. • A real option approach is proposed to model the inventor's investment decisions. • The simulation is performed using the case of the solar PV industry. • Implications for policymakers on the design of FIT programs are provided.

Performance Analysis Of Grid Tie Inverter With Power Limiter To Increase Utility Power Reduction In One Way kWh Meter Circuit

The use of grid tie inverter (GTI) in household electricity is intended to reduce the use of electricity from utilities. The configuration of GTI usually does not use batteries and the excess power from PV will be sent to the grid so that it will substitute utility electricity with electricity from GTI. However, this can occur when follow net metering program by installing a export-import kwh meters (two-way kwh meter) or follow feed in tariff program. If the kwh meter used does not support this capability or not following both program, the electric power of GTI will not substitute power from the utility. GTI with power limiter allows the inverter to work like a GTI in general but does not send excess power to the utility. The excess power from PV can be stored into the battery so that when the power shortage of PV will be substituted with power stored in the battery is not from the utility. In this research, conducted a study of the performance of the GTI with a power limiter and compared it with the GTI without a power limiter that works on an electricity network. The results of the study show that the use of GTI with a power limiter can increase the reduction in power usage from utilities by up to 40%.

Development of an Optimization Model to Manage Imbalances in Power Systems by Local Power Retail Companies

The feed-in tariff (FIT) programs resulted in rapid growth of renewable power sources in various countries. In Japan, the program particularly triggered explosive growth of solar power generations because of its short lead-time and high tariff level. Although mass introduction of renewable power sources certainly contributes to reduce CO2 emissions, it causes serious instability issues in power systems. One of the most serious issues is management of imbalances resulting from forecast errors in solar power generations. These imbalances must be compensated so as to keep stable operation in power systems. On the other hand, local power retail companies are increasing nowadays in various countries including Japan. These companies are mainly procuring renewable power sources such as solar power systems.Taking these circumstances into consideration, this article aims at exploring measures to manage the imbalances of power systems by local power retail companies. For this purpose, we developed a model in mixed integer linear programming to operate power systems dealing with the imbalances. Evaluated results using the model indicated the followings; appropriate adoption of stationary or home batteries is shown to economically compensate the imbalances by local power retail companies.

Antidumping and Feed-In Tariffs as Good Buddies? Modeling the EU-China Solar Panel Dispute

The paper analyzes the interactions between trade and renewable energy policies based on the EU-China solar panel dispute which is the most significant antidumping (AD) complaint in Europe. We build a price competition duopoly model with differentiated products and intra-industry trade in photovoltaic (PV) equipment. We show that an optimal antidumping duty always increases with the feed-in tariff (FIT) program set in the home country. An appropriate antidumping duty—nullifying the dumping margin—decreases with the FIT program. We show that optimal FIT increases with the AD duty. Therefore, trade and renewable energy optimal policies may complement one another. Lastly, we introduce R&D activities in the PV sector, and international spillovers. We show that R&D makes the optimal FIT lower and increases the dumping margin. These effects are reinforced by technological spillovers.

Feed-in tariffs with minimum price guarantees and regulatory uncertainty

The feed-in tariff (FIT) program is a popular policy for incentivizing new renewable energy projects because it establishes a long-term contract with renewable energy investors. This paper presents a novel model to analyze a FIT contract with a minimum price guarantee (i.e., a price-floor regime) from an investor's perspective. The results show that a perpetual guarantee only induces investment for prices below the price floor when offering a risk-free investment opportunity. In contrast, the finite guarantee may induce investment even when the revenue from the guarantee is lower than the investment cost. When an investor faces a scenario with regulatory uncertainty, a higher and more likely reduction in the price floor induces earlier investment. For all cases, investors postpone an investment decision when market conditions present a higher price volatility.

Optimal design of a coproduction system of electricity and hydrogen to manage imbalances resulting from forecast errors in photovoltaic outputs

Renewable power sources are increasing mainly because of economic institutions such as renewable portfolio standard or feed-in tariff program. In Japan, the feed-in tariff program triggered explosive growth of photovoltaic systems because of its high tariff level. Although mass introduction of photovoltaic systems certainly contributes to reduce CO2 emissions, it causes instability issues in power systems. One of the most serious issues is management of imbalances resulting from forecast errors in photovoltaic outputs. On the other hand, power-to-gas technologies are attracting our attention, since these technologies could convert surplus of renewable energy to other energy carriers. In particular, hydrogen is efficiently produced from electricity using electrolysis. We could use hydrogen to manage the imbalances by the system, in which uncertain parts of photovoltaic outputs are used to produce hydrogen. In this paper, we propose a coproduction system of electricity and hydrogen to reduce the imbalances. For this purpose, a novel mathematical model is developed, in which we determine the structure of the coproduction system with a mixed integer linear programming method. Evaluated results indicated that the coproduction system is economical under appropriate capacity of the electrolyzer.

Energy trading for fun and profit buy your neighbor's rooftop solar power or sell your own-it'll all be on a blockchain

Would you pay slightly more for your electricity if you knew it was sourced from photovoltaic panels on your neighbor's roof? Or, if you are that neighbor, would you use your solar power to charge a battery and dump that energy back onto the grid at peak hours, when the price was highest? The answers to these questions-which depend on how people would behave in an open energy market-are unknown, because that market does not exist. Net metering and feed-in tariff programs, the two dominant schemes for reimbursing residential energy production, pay out at a fixed rate, effectively decoupling producers from the price signals that might otherwise direct their behavior. But that may be changing. And we may have the blockchain to thank. Multiple projects are now under way to use technology that was originally intended to account for transactions in digital currency to track electricity production and put it up for sale.

Development of Japan’s Photovoltaic Deployment Scenarios in 2030

There is a strong need to address climate change issues by mobilizing a variety of technologies, including renewable energy technologies. In this paper, we focus on photovoltaic (PV) technology because solar cells or PV panels are already popular in many countries, mainly incentivized by a feed-in tariff (FIT) program and low production cost. However, it is difficult to accurately predict future PV installation capacity for a region because of a variety of uncertainties, such as national energy policies and consumers’ lifestyles. Taking such uncertainties into account, this paper takes a scenario design approach to analyze future PV deployment, thereby helping to examine policy implications and offering appropriate actions. A case study of Japan’s PV deployment scenarios up to 2030 is presented here. Four distinct future situations are assumed, with particular focus on technological advancement and national share of nuclear energy. The results show that solar power generation in 2030 could account for 3.4%–7.4% of the national electricity demand.

Antidumping and Feed-In Tariffs as Good Buddies? Modeling the EU-China Solar Panel Dispute

The paper analyzes the interactions between trade and renewable energy policies based on the EU-China solar panel dispute which is the most significant antidumping (AD) complaint in Europe. We build a price competition duopoly model with differentiated products and intra-industry trade in photovoltaic (PV) equipment. We show that an optimal antidumping duty always increases with the feed-in tariff (FIT) program set in the home country. An appropriate antidumping duty - nullifying the dumping margin - decreases with the FIT program. We show that optimal FIT increases with the AD duty. Therefore, trade and renewable energy optimal policies may complement one another. Lastly, we introduce R&D activities in the PV sector, and international spillovers. We show that R&D makes the optimal FIT lower and increases the dumping margin. These effects are reinforced by technological spillovers.

P-6 木質バイオマス発電事業における事業採算性評価ツールの開発(ポスターセッション)

P-6 木質バイオマス発電事業における事業採算性評価ツールの開発(ポスターセッション)

Highlight of Grid-connected PV systems in administrative buildings in Egypt

Solar energy applications are becoming increasingly common in Egypt. The abundant sunshine in Egypt, as well as the increasing competitiveness of solar energy systems including- but not limited to photovoltaic (PV), – predicts that these technologies could be weighed to be raised in Egypt. PV systems are installed on roof tiles or other parts of building structures to supplement grid utility, reduce electric bills, and provide emergency back–up energy. Moreover, they simultaneously reduce significant amounts of CO 2 emissions. It is foreseen, a number of residential and public buildings in Egypt are using solar power to cut electric utility bills significantly. The approximately payback period to recover the investment costs for PV systems is up to about 5 years. In addition, it is more economical to use PV system than grid utility systems. The two components that determine the total initial price of a grid- connected PV system are the modules and the balance of systems (BOS). The BOS includes different components such as mounting frames, inverters and site- specific installation hardware. The Government of Egypt (GOE) has endorsed the deployment of PV systems through three approaches. It started with a prime minister decree to install PV projects on one-thousand of the governmental buildings. This was followed by as an initiative called "Shamsk ya Masr", and finally the Feed-in Tariff (FiT) projects. Following the prime minster decree the Egyptian Electricity Holding Company (EEHC) and its affiliated companies took the lead to install PV systems at the top roof of their administrative buildings and interconnect these systems to the electricity network where the suitable locations have been selected for mounting them. About 90 PV systems have been already mounted with about a capacity of 9 MW. On the other hand, "Shamsk ya Masr" has considered energy efficiency (EE) so as to complement the PV systems, which will be installed on administrative buildings. Cost- effective EE measures should be implemented prior to or at the same time as implemented PV program. The amount of electricity that a PV system produces depends on the system type, orientation and the available solar resource. In 2014, the GOE issued the Feed-in Tariff program to further promote RE technologies in general and PV in particular. Egyptian Electric Utility and Consumer Protection Regulatory Authority (Egypt ERA) has set the regulations, promotion and awareness for PVs. This approach has been applied for administrative buildings as well. The paper highlights the impact of the previously mentioned mechanisms in deploying PV technologies through small scale projects. It also represents a cost- benefit analysis for the installed systems taking into account the measured value for PV parameters (kWh/kWp, PSH) and daily load profiles of the selected administrative buildings.

Scenario analysis for sustainable woody biomass energy businesses: The case study of a Japanese rural community

Woody biomass is widely used as a renewable energy source to produce electricity and heat, with the goal of reducing CO2 emissions, enhancing energy security, and rejuvenating rural economies. In Japan, the energy usage of woody biomass is currently incentivized by feed-in tariff (FIT) programs. However, a variety of unpredictable factors (e.g., a drastic change in national energy policy and feedstock supply) might undermine the sustainability of woody biomass energy businesses. In order to clarify conditions for designing sustainable woody biomass energy businesses from environmental and economic viewpoints, this paper proposes a method for undertaking scenario analyses where the influences of future uncertainties are analyzed. For quantitative assessment, a woody biomass energy business is modeled as a sequence of processes using a discrete event simulation technique. A case study is carried out with a particular focus on the energy business with a 10 MW woody biomass power generation plant in a Japanese rural community in the period of 2015–2034 (20 years). The results reveal that the business has potential to gain economic profit and halve CO2 emissions when compared with the worst case scenario. Critical factors for enhancing the sustainability of the business include collecting the amount of wood residue used for electricity generation and keeping the selling price of electricity from woody biomass at over 35% of the current price.

Analysis and model-based predictions of solar PV and battery adoption in Germany: an agent-based approach

In order to tackle energy challenges faced in Germany, a Feed-in Tariff program was created in 2004 to aid the adoption of solar PhotoVoltaic (PV) systems where owners of such systems are paid a certain amount for each unit of electricity generated. Solar PV electricity generation is limited due to its intermittency but this can be managed using batteries. In this paper, we study the adoption of PV and battery (PV-battery) systems in Germany, and evaluate policies that could improve the adoption of these systems and their impact on the electric grid. To do this, we create an agent-based model that is simulated to estimate the impacts of different policies; this model is informed by an online survey with respondents from Germany. Simulating adoption over a period of 10 years, the results show that increasing electricity prices could result in improved PV-battery adoption in Germany better than reducing PV-battery system prices could. In addition, given the high level of affinity of people towards PV systems in Germany, disconnection from the grid would be a viable option within the next 10 years.

Ergodic Energy Management Leveraging Resource Variability in Distribution Grids

Contemporary electricity distribution systems are being challenged by the variability of renewable energy sources. Slow response times and long energy management periods cannot efficiently integrate intermittent renewable generation and demand. Yet stochasticity can be judiciously coupled with system flexibilities to enhance grid operation efficiency. Voltage magnitudes for instance can transiently exceed regulation limits, while smart inverters can be overloaded over short time intervals. To implement such a mode of operation, an ergodic energy management framework is developed here. Considering a distribution grid with distributed energy sources and a feed-in tariff program, active power curtailment and reactive power compensation are formulated as a stochastic optimization problem. Tighter operational constraints are enforced in an average sense, while looser margins are enforced to be satisfied at all times. Stochastic dual subgradient solvers are developed based on exact and approximate grid models of varying complexity. Numerical tests on a real-world 56-bus distribution grid and the IEEE 123-bus test feeder relying on both grid models corroborate the advantages of the novel schemes over their deterministic alternatives.

Efficient Feed-In-Tariff Policies for Renewable Energy Technologies

Feed-in-tariff (FIT) policies aim at driving down the cost of renewable energy by fostering learning and accelerating the diffusion of green technologies. Under FIT mechanisms, governments purchase green energy at tariffs that are set above market price. The success or failure of FIT policies, in turn, critically depend on how these tariffs are determined and adjusted over time. This paper provides insights into designing cost-efficient and socially optimal FIT programs. Our modeling framework captures key market dynamics as well as investors’ strategic behavior. In this framework, we establish that the current practice of maintaining constant profitability is theoretically rarely optimal. By contrast, we characterize a no-delay region in the problem’s parameters, such that profitability should strictly decrease over time if the diffusion and learning rates belong to this region. In this case, investors never strategically postpone their investment to a later period. When the diffusion and learning rates fall outside the region, profitability should increase at least temporarily over some time periods and strategic delays occur. The presence of strategic delays, however, makes the practical problem of computing optimal FIT schedules very difficult. To address this issue, the regulator may focus on policies that disincentivize investors to postpone their investment. With this additional constraint, a constant profitability policy is optimal if and only if the diffusion and learning rates fall outside the no-delay region. This provides partial justifications for current FIT implementations.