Generation Investment Research Articles

A two stage cap-and-trade model with allowance re-trading and capacity investment: The case of the Chilean NDC targets

In this work, we study an alternative approach for capping and pricing carbon emissions in electric markets: the cap-and-trade paradigm with re-trade of allowances. We model the electric market (generators and allowances’ auctioneer) as a two stage stochastic capacity expansion equilibrium problem, where we allow future investment and re-trading of emission permits among generators. The model studies generation and future investments in the electric sector in two regimes of demand: deterministic and stochastic. The configuration enforces the reduction of carbon emissions by setting a carbon budget, which allows to assess the impact of green policies and pledges concerning an electric system. We use the proposed model to analyze the Chilean electric sector under a cap-and-trade paradigm as an alternative to the existing carbon tax. We show that the Chilean pledge regarding emissions reductions does not encourage a shift to greener technologies. Moreover, we characterize two strategies to comply with the renewable targets by mid-century. On the one hand, a stringent carbon budget that induces high price of carbon permits and phases out coal-based generators. On the other hand, a less stringent target which significantly encourages investment in renewable technologies, but with low remaining shares of coal-based electric generation towards 2050.

Procurement, finance and the energy transition: Between global processes and territorial realities

Utility-scale renewable electricity generation is essential to decarbonisation as well as to ensuring affordable and secure electricity supplies around the world. Yet thus far there has been limited critical thinking dedicated to the complexities behind the finance and ownership of this new infrastructure and how national and local stakeholders should participate in and benefit from its development, particularly in contexts of high inequality in low- and middle-income countries. As the global renewable energy industry becomes increasingly consolidated and financialised, evidence from a number of countries suggests that despite the pro-environmental outcomes of utility-scale renewable electricity generation, the processes and institutions that procure and finance it have often failed to include or benefit individuals and communities living in the national and local vicinity. This paper therefore sets two key competing objectives of renewable electricity generation in context: as a predictable, long-term revenue stream for investors, and as a mechanism for socio-economic development and community empowerment. Building on scholarship from human geography, development studies and sustainability transitions, my analysis takes forward understandings of the role of finance in utility-scale renewable electricity generation as a key aspect of the political economy of the energy transition. In exploring the evolution of renewable electricity as a new and rapidly emerging asset class I consider how its development is increasingly determined by the frameworks and logics of finance and investment. Drawing on examples from South Africa and Mexico, I address the following questions: What are the evolving configurations and processes of finance and investment in utility-scale renewable electricity generation? How have they been facilitated? And what tensions have arisen from their implementation at the national and local level?

Renewable electricity generation proposed pathways for the US and China

In this study, we investigate the direction of the causal relationship between renewable electricity generation (REG) and economic growth for the US and China. The results show a unidirectional causality running from REG to economic growth for the US and China. Furthermore, a bi-directional long short-term (Bi-LSTM) algorithm is formulated to propose REG pathways based on four scenarios. First, we allow the Bi-LSTM network to make business-as-usual (BAU) predictions. The results show that the US and China’s REG as a percentage of total electricity output will hit ∼17.769 and ∼34.688 by 2030, respectively. Second, we set a 30% incremental target and estimate that the US and China REG will hit ∼17.198 and ∼31.105 by 2030, respectively. Third, the results from setting an incremental target of 50% depicts that the US and China REG will hit ∼19.844 and ∼35.891 by 2030, respectively. Finally, the 100% incremental target from the 2015 generation shows that the US and China REG are expected to hit ∼26.458 and ∼47.854 by 2030, respectively. As a policy implication, if investments in renewable electricity generation are not intensified, the US and China stand a risk of not meeting the pathway targets proposed.

Daily Forecasting for Antam's Certified Gold Bullion Prices in 2018-2020 using Polynomial Regression and Double Exponential Smoothing

Gold investment is currently a trend in society, especially the millennial generation. Gold investment for the younger generation is an advantage for the future. Gold bullion is often used as a promising investment, on other hand, the digital gold is available which it is stored online on the gold trading platform. However, any investment certainly has risks, and the price of gold bullion fluctuates from day to day. People who invest in gold hopes to benefit from the initial purchase price even if they must wait up to five years. The problem is how they can notice the best time to sell and buy gold. Therefore, this research proposes a forecasting approach based on time series data and the selling of gold bullion prices per gram in Indonesia. The experiment reported that Holt’s double exponential smoothing provided better forecasting performance than polynomial regression. Holt’s double exponential smoothing reached the minimum of Mean Absolute Percentage Error (MAPE) 0.056% in the training set, 0.047% in one-step testing, and 0.898% in multi-step testing.

Strategic Participation of Residential Thermal Demand Response in Energy and Capacity Markets

The value proposition of residential thermal demand response (DR) could be enhanced through participation in multiple electricity markets. However, this potential value could be affected by misalignment of the strategic objectives of DR participants and also by the adoption levels of flexible heating technologies. This article presents an extended multi-perspective model (EMPM) which integrates the optimization problems of the DR participants within a single framework to evaluate the participation of residential thermal DR in energy and capacity markets. The capacity market participation is explicitly modeled based on parameters obtained using a bespoke capacity value assessment methodology. Subsequently, an iterative algorithm is proposed for determining consumer adoption levels of flexible heating technologies. The results indicate that while capacity market participation of residential thermal DR would be beneficial for all DR entities, consumers' comfort preferences would have a noticeable impact on the results. Additionally, very high consumer adoption levels of flexible technologies would reduce power system costs and increase investment in low-carbon generation, but would not be optimal from the consumers' investment perspective. Additionally, sensitivity analyses highlight that multiple market participation, energy inefficiency of the building fabric and greater preference for comfort could incentivize greater consumer adoption of flexible heating technologies.

Fertility transition and socioeconomic development in districts of India, 2001-2016.

The fertility-development relationship is bi-directional, context-specific, multi-phased and inconsistent over time. Indian districts provide an ideal setting to study this association due to their size, diversity and disparity in socioeconomic development. The objective of this study was to understand the association of fertility and socioeconomic development among the 640 districts of India. Data were drawn from multiple sources: Censuses of India 2001 and 2011; DLHS-2; NFHS-4; and other published sources. A district-level data file for Total Fertility Rate (TFR) and a set of developmental indices were prepared for the 640 districts for 2001 and 2016. Computation of a composite index (District Development Index, DDI), Ordinary Least Squares, Two Stage Least Squares and panel regressions were employed. By 2016, almost half of all Indian districts had attained below-replacement fertility, and 15% had a TFR of above 3.0. The DDI of India increased from 0.399 in 2001 to 0.511 by 2016 and showed large variations across districts. The correlation coefficient between TFR and DDI was -0.658 in 2001 and -0.640 in 2016. Districts with a DDI of between 0.3 and 0.6 in 2001 had experienced a fertility decline of more than 20%. The fertility-development relationship was found to be strongly negative, convex and consistent over time, but the level of association varied regionally. For any given level of DDI, fertility in 2016 was lower than in 2001; and the association was stronger in districts with a DDI below 0.45. The negative convex association between the two was prominent in the northern, central and eastern regions and the curves were flatter in the west, south and north-east. The increasing number of districts with low fertility and low development draws much attention. Some outlying districts in the north-eastern states had high TFR and high DDI (>0.6). Based on the findings, a multi-layered strategy in districts with low socioeconomic development is recommended. Additional investment in education, child health, employment generation and provisioning of contraceptives would improve the human development to achieve India's demographic goals.

The Contribution of Taxes, Subsidies and Regulations to British Electricity Decarbonisation

Great Britain’s carbon emissions from electricity generation fell by two-thirds between 2012 and 2019, providing an important example for other nations. This rapid transition was driven by a complex interplay of policies and events: investment in renewable generation, closure of coal power stations, raising carbon prices and energy efficiency measures. Previous studies of the impact of these simultaneous individual measures miss their interactions with each other and with exogenous changes in fuel prices and the weather. Here we use Shapley values, a concept from cooperative game theory, to disentangle these and precisely attribute outcomes (CO2 saved, changes to electricity prices and fossil fuel consumption) to individual drivers. We find the effectiveness of each driver remained stable despite the transformation seen over the 7 years we study. The four main drivers each saved 19–29 MtCO2 per year in 2019, reinforcing the view that there is no ‘silver bullet’, and a multi-faceted approach to deep decarbonisation is essential.

Markets for Efficient Decarbonization: Revisiting Market Regulation and Design

In the 1980s, some seminal works such as markets for power: an analysis of Electric Utility Deregulation by Joskow and Schmalensee and Spot Pricing of Electricity by Schweppe et al. set the foundations for electric system restructuring toward a fully liberalized, marginal price-based market environment in which generators and end users trade. Even then, it was clear that the task was not going to be easy, but an increasingly and always significant portion of the industry and academic thought that it was at least possible. More than three decades after the first markets were implemented, the entire power sector community continues to discuss the suitability of relying on short-term market prices as an efficient signal to drive investments, especially in the current context in which not only traditional generators but also end users can decide to invest in energy supply resources, and an increasing amount of new generation investments have zero or close to zero variable costs, which some people see as a threat to the short-term market paradigm.

Electricity Price Distributions in Future Renewables-Dominant Power Grids and Policy Implications

Future electricity systems with tight constraints on carbon emissions will rely much more on wind and solar generation, with zero marginal cost, than today. We use capacity expansion modelling of Texas in 2050 to illustrate wholesale price distributions in future energy-only, carbon-constrained grids without price caps under a range of technology/system assumptions. Tightening carbon emissions constraints dramatically increases the frequency of very low prices. The frequency of high prices also increases, and all resources earn the bulk of their energy market revenues in relatively few hours. The presence of demand response, long-duration energy storage, dispatchable low-carbon generation, or a robust market for hydrogen for non-electricity use (and for energy storage) weakens but does not undo these results. Financial instruments to hedge price volatility will consequently be more costly and it is likely that we will need to redesign capacity remuneration mechanisms to provide adequate incentives for optimal investment in VRE generation and, particularly, storage. In order to encourage economy-wide electrification, the marginal retail price of electricity should be low whenever the wholesale price is low. With automated control of demand via demand response contracts, the risks of price volatility faced by retail customers can be mitigated without sacrificing efficiency. To encourage economy-wide electrification, the marginal retail price of electricity should be low when the wholesale spot price is low. We discuss ways of reducing consumers’ risk in this world while providing adequate investment incentives.

Resource-efficient and renewable energy transition in the five least developed countries of Asia: a post-COVID-19 assessment

The economic fallout from COVID-19 resulted in an economic slowdown and a contraction in economic output, changed economic structures, and reduced financial inflows in the five least developed countries (LDCs) of Asia – Bangladesh, Cambodia, Lao People’s Democratic Republic (PDR), Myanmar, and Nepal. This policy brief discusses these impacts in light of the LDC-graduation procedures of the United Nations together with the challenges that these countries face meeting their nationally determined contributions (NDCs) and the environment-related Sustainable Development Goals (SDGs 7, 12, and 13). The economic slowdown in Bangladesh, Lao PDR, and Myanmar and a contraction in economic output in Cambodia and Nepal has increased poverty in the five LDCs and is putting pressure on biomass resources in the rural areas of these countries. The change in the structures of their economies, which threatens to reverse processes of economic modernization in these LDCs, is undermining two decades of progress regarding the efficient use of natural resources and the associated reduction in greenhouse-gas (GHG) emissions per unit of gross domestic product (GDP). A decline in financial inflows such as remittances, foreign direct investment, and official development assistance (ODA) is also a risk to both short- and long-term prospects of further investment in renewable energy generation and low GHG-emissions technologies. This policy brief suggests policies that target technical interventions and incentivize small-scale renewable energy technologies that are less susceptible to microeconomic and macroeconomic impacts from external shocks such as COVID-19.

The Contribution of Taxes, Subsidies And Regulations to British Electricity Decarbonisation

Great Britain’s carbon emissions from electricity generation fell by two-thirds between 2012 and 2019, providing an important example for other nations. This rapid transition was driven by a complex interplay of policies and events: investment in renewable generation, closure of coal power stations, raising carbon prices and energy efficiency measures. Previous studies of the impact of these simultaneous individual measures miss their interactions with each other and with exogenous changes in fuel prices and the weather. Here we use Shapley values, a concept from cooperative game theory, to disentangle these and precisely attribute outcomes (CO2 saved, changes to electricity prices and fossil fuel consumption) to individual drivers. We find the effectiveness of each driver remained stable despite the transformation seen over the 7 years we study. The four main drivers each saved 19–29 MtCO2 per year in 2019, reinforcing the view that there is no ‘silver bullet’, and a multi-faceted approach to deep decarbonisation is essential.

What Kinds of Distributed Generation Technologies Defer Network Expansions? Evidence from France

This paper estimates the relationship between investments in five distributed generation technologies and hourly net injections to the distribution grid for over 2,000 substations in France between 2005 and 2018. We find that investments in distributed wind and solar capacity have little or no impact on the annual peak of hourly net injections to the distribution grid, while investments in hydroelectric and thermal distributed generation significantly reduce it. An optimistic analysis of battery storage suggests that high levels of investments are required for distributed wind and solar investments to deliver similar reductions in the annual peak of hourly net injections.

When the Wind of Change Blows, Build Batteries? Optimum Renewable Generation and Energy Storage Investments.

Renewables have become the cheapest energy source in most of the world, but their generation remains variable and difficult to predict. Recent technological advances have rendered large-scale electricity storage economically viable, thus mitigating the renewable intermittency issue and enabling combinations of renewable generation plus storage, e.g., wind farms and batteries, to be potentially viable candidates to replace fossil fuel power plants. However, it is not yet well-understood how to jointly determine optimal capacity for their generation and storage. Our work aims to shed light on this question by developing a two-product newsvendor model of a utility's strategic capacity investment in renewable generation and storage to match demand with supply, while using fossil-fuel backup, if needed. We establish optimal capacity guidelines contingent on market and technology parameters. We find that renewable generation and storage are strategic complements, except in cases with very high penetration of either technology, when they surprisingly turn into strategic substitutes. We also develop sufficient and necessary conditions, as well as a simple heuristic, to determine which of the many storage technologies can turn a profit in the broadest set of market conditions, and thus is likely to be adopted first (for multi-hour storage). In particular, we show that low-efficiency, cheap technologies, such as thermal, can turn a profit easier than high-efficiency, expensive ones, such as lithium-ion batteries. Using real-life data from Europe and the US, we calibrate our model to provide insight on the role that large-scale storage plays in both the short- and long-term, while technology improves, emission taxes are levied, and renewables become cheaper. Finally, we show that, when generation and storage investment decisions are made by different players, investment levels decrease relative to the monopoly outcome.

The Role of Biomass Gasification in the Future Flexible Power System – BECCS or CCU?

In this work we study if biomass gasification for production of advanced biofuels also can play a role in managing variability in the electricity system. The idea is a CCU/power-to-gas concept to enhance methane production from biomass gasification. The suggested process is flexible in that CO2 not used for methane production can be stored through a BECCS concept that implies negative GHG emissions. For this purpose, rigorous models of three different gasification process configurations were simplified through surrogate modeling and integrated into a dynamic optimization model of regional electricity systems. The results show the diverse advantages of flexible operation between CCU and BECCS and that it is economically beneficial for the system to invest in gasification at the investigated levels of CO2 charge. The gasification option also provides value for low-priced electricity and thus stimulate increased investments in renewable electricity generation, which indicates the importance of considering geographical diversities in the assessment and highlights the importance of studying this type of concept with a time-resolved model. It is clear that the BECCS option is the most used, however, the limited quantities of CO2 used for the CCU option has a large impact on the investments made in the electricity system.

Unlocking a Renewable Energy Future: How Government Action Can Drive Private Investment

A renewable energy future is within our grasp: the technology is now widely available and cost-effective in most places around the world. But the current rates of deployment remain well below what is required to avert the worst impacts of climate change. The private sector is poised to invest billions of dollars to massively speed up, scale and support the energy transition. However, many investors, particularly in the private sector, are deterred by some of the risks related to renewable energy investments. As the energy transition is likely to be financed largely by the private sector, governments must work with the private sector to remove barriers and incentivize investment in renewable energy. This working paper, produced in partnership with Ørsted, focuses on the challenges and solutions to scaling investment in renewable energy generation and provides actionable policy solutions to unlock the private sector investment needed to support the energy transition.

The Interplay between Green Policy, Electricity Prices, Financial Constraints and Jobs: Firm-Level Evidence

Increased investment in clean electricity generation or the introduction of a carbon tax will most likely lead to higher electricity prices. We examine the effect from changing electricity prices on manufacturing employment. Analyzing firm-level data, we find that rising electricity prices lead to a negative impact on labor demand and investment in sectors most reliant on electricity as an input factor. Since these sectors are unevenly spread across countries and regions, the labor impact will also be unevenly spread with the highest impact in Southern Germany and Northern Italy. We also identify an additional channel that leads to heterogeneous responses. When electricity prices rise, financially constrained firms reduce employment more than less constrained firms. This implies a potentially mitigating role for monetary policy.

A mathematical programming formulation for long-term infrastructure investment planning in Small Island Developing States

Mixed-integer programming is a common method used in electricity generation and transmission optimization models. However, the size of the problem can result in extraordinarily long run times. Solve time also increases exponentially with the number of variables to optimize. There is therefore a constant trade-off between a realistic representation of the network and computational tractability. Additionally, actual data and publicly available, real-world application are scare. This is particularly true for Small Island Developing States. This paper bridges these gaps by describing a customized mathematical formulation for co-optimizing generation and transmission infrastructure investments. Data from the island of Jamaica and program scripts are available for reproduction. Key customizations to a mixed-integer programming model for long-term generation and transmission infrastructure investment planning include:•Hours are treated as representative hour categories and multiplied by the number of hour types within a given period.•Simulated construction is limited to every other year.•While fossil fuel plants are treated as discrete variables, renewable energy plants are treated as continuous variables.

Coordinated Development Based Grid-Source-load Collaborative Planning Method of Uncertainty and Multi-agent Game

When planning the power grid, it is necessary to obtain the optimal decision scheme according to the market behavior of different stakeholders. In this paper, the virtual game player "nature" is introduced to realize the deep integration of game theory and robust optimization, and a source network load collaborative planning method considering uncertainty and multi-agent game is proposed. Firstly, the planning decision-making models of different stakeholders of DG investment operators, power grid investment operators and power users are constructed respectively; then, the static game behavior between distributed generation (DG) investment operators and power grid investment operators is analyzed according to the transmission relationship of the three; at the same time, robust optimization is used to deal with DG. In this paper, we introduce the virtual game player "nature" to study the dynamic game behavior between the virtual game player and the power grid investment operator. On this basis, the dynamic static joint game planning model is proposed.

Efekat investiranja u upravljanje čvrstim otpadom u Republici Srbiji

The problem of establishing an effective solid waste management system is complex and still unresolved in Serbian municipalities, cities and settlements. Most landfills in Serbia do not meet basic sanitary standards and can often contain waste that is dangerous to human, plant and animal health, and waste that can be recycled is often dumped. The aim of this paper is to investigate the relationship between waste generation and private investments in waste management. Statistical method of multiple linear regression was used to examine the impact of three predictors - economic development, investments in waste management, and urban population, on the dependent variable - municipal solid waste generation. The results of the research reveal that investments in waste management in Serbia do not have an effect on the waste reduction because the financial resources for such investments are not adequately managed. There is a large number of scientific researches that have dealt with the analysis of the mentioned relationship, however, their number on the example of Serbia is rather scarce. The results of the research could be useful to the state administrations of the Republic of Serbia.

Generator Interconnection, Network Expansion, and Energy Transition

Inefficient coordination between decentralized generation investment and centralized transmission planning is a significant barrier to achieving rapid decarbonization in liberalized electricity markets. While the optimal configuration of the transmission grid depends on the relative social costs of competing technologies, existing processes have not led to transmission expansion consistent with declines in the cost of wind and solar combined with increased estimates of the social costs of traditional thermal resources. To break the negative feedback loop preventing efficient network expansion, this paper proposes an inversion of the generator interconnection process in conjunction with modifications in the definition of financial rights connected with transmission service. From a generator perspective, the effect of the proposed reforms is to trade highly uncertain network upgrade and congestion costs for a fixed interconnection fee. From a transmission planning perspective, the goal is to improve the quality of information about new generation included in forward-looking planning processes. Simulation on a stylized two-node system demonstrates the potential of the approach to facilitate a transition to clean technologies.