Power Plant Investment Research Articles

Operation Cost Analysis of Typical Power Plant Waste Incineration

In recent years, as the main way to deal with Municipal Solid Waste (MSW), municipal solid waste incineration power generation possesses the dual positive attributes of environmental protection and energy production. In addition to effectively solving the current environmental problems of “cities besieged by garbage”, it is possible to become an important supplement of urban energy and an inevitable requirement for economic and social development. Some suggestions are put forward based on the calculation results of actual investment and operating costs of waste incineration power plants. The research results are of great reference value for timely understanding of the status quo of waste incineration power plants, formulating policies and guiding the investment and operation management of power plants.

Modified Levelized Cost of Electricity or Energy, MLOCE and Modified Levelized Avoidable Cost of Electricity or Energy, MLACE and Decision Making

LCOE is the Levelized Cost of Electricity or Energy, which is an economic measure of the minimum price at which energy can be produced over the lifetime of the power plant. This value determines the minimum value at which energy could be sold during the lifetime of the installation, and this value is considered as the net present value of unit cost electricity. It is estimated dividing the net present value of the total expenditure by the total production. The LACE is the Levelized Avoided Cost of Electricity or Energy which is a measure of income for the unit value of electricity. Of course, the value of LCOE should be less than the LACE for considering the project, these metrics are necessary but not sufficient to start the project. For overcoming these difficulties, in this paper MLCOE (Modified Levelized Cost of Electricity or Energy) and MLACE (Modified Avoided Cost of Electricity or Energy) are introduced to the calculations for considering dominant factors of construction of a plant and these are the actual estimations of CAPEX (Capital Expenses) and OPEX (Operation Expenses) through the payback period. The methodology presented in this paper will be an important supporting tool for power plant investments of go - or - not go decision.

Information Shocks and Profitability Risks for Power Plant Investments – Impacts of Policy Instruments

Climate change mitigation requires governmental intervention, but different choices are at hand. While economists in general advocate for first-best instruments, reality looks quite different, with especially many subsidy schemes for renewable energies being used. Supporters of these schemes often argue that investment risk reduction is essential to achieve ambitious environmental targets. In this paper we compare four different instruments (cap, tax, minimum quota and feed-in tariffs/renewable auctions) in terms of efficacy and efficiency and also quantify investment risks, assuming an uncertain investment environment, represented by different information shocks on demand, investment and fuel cost. We use a long-term electricity market equilibrium model (generalized peak load pricing model) of the future German electricity market implemented as a linear optimization problem. Starting from an equilibrium, single input parameters are varied to simulate the arrival of new information. Running the model again with partly fixed capacities then allows us to analyze the adjustment of the power plant portfolio towards the new equilibrium over time. As expected quantity-based instruments are effective in assuring achievement of quantitative goals, notably a certain emission level. Yet risks for investors are rather high in that furthermore that first-best instruments are the most efficient. Risks are lower with price solutions, especially feed-in tariffs or renewable auctions provide the possibility to limit risks extremely by diversification only inside the electricity market.

Renewable Energy: The Trillion Dollar Opportunity for Chinese Overseas Investment

AbstractThis paper compares the global flows of Chinese overseas investment in power plants with renewable energy investment potential embodied in “Nationally Determined Contributions.” With over US$1tn (671 GW) in Nationally Determined Contributions renewable energy investment potential in developing countries, we estimate the total level of power plant investments from China's policy banks and commercial entities since the early 2000s at US$216bn (158 GW). Although past investment has mainly been directed at fossil fuels and hydroelectric power, we argue that China is uniquely poised to lead renewable energy global investments for three reasons: (i) China's solar and wind industries are globally competitive; (ii) Chinese policy banks can give domestic firms advantages in financing global expansion; and (iii) renewable energy investment opportunities still exist in developing countries with less sovereign risk than for traditional energy investments. The Chinese government should provide special incentives for the policy banks to capitalize on these investment opportunities by deploying Chinese solar and wind technologies to Belt and Road countries and beyond.

A Multi-Criteria Decision Making (MCDM) for Renewable Energy Plants Location Selection in Vietnam under a Fuzzy Environment

In the context of increasing energy demands in Vietnam, and as a result of the limited supply of domestic energy (oil/gas/coal reserves are exhausted), the potential for renewable energy sources in Vietnam is significant. Thus, building wind power plants in Vietnam is necessary. Access to this type of renewable energy not only contributes to society’s energy supply but also helps to save energy and reduce environmental pollution. Although some works have reviewed applications of the Multi-Criteria Decision Making (MCDM) model in wind power plant site selection, little research has focused on this problem in a fuzzy environment. This is the reason why a hybrid Fuzzy Analytic Hierarchy Process (FAHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are developed for wind power plant site selection in Vietnam. In the first stages of this research, an FAHP model is proposed for determining the weight of each potential location for building a wind power plant, based on qualitative and quantitative factors. A TOPSIS is applied for ranking all potential alternatives in the final stage. The authors collected data from seven locations, which have good conditions for investment in a wind power plant. The results indicate that Binh Thuan (Binh Thuan Province is located on coast of South Central Vietnam) is the best place for building a wind power plant in Vietnam. The contributions of this work proposed an MCDM approach under fuzzy environments for wind power plant location selection in Vietnam. This paper also resides in the evolution of a new approach that is flexible and practical for a decision-maker. This work also provides a useful guideline for wind power plant location selection in others countries.

Meta Analisis Pengembangan Assesment Kelayakan Sistim Pembangkit Tenaga Air

Abstract-This study aims to determine the feasibility assessment of hydroelectricity to feasibility studies that have been conducted in various developing and developed countries. In a feasibility study usually consider various important aspects such as technical and non technical aspects that will affect the productivity of a feasibility study.Methododologi research based on the meta-analysis method, in which the analysis is based on a review of a number of research results on similar issues in the case of a feasibility assessment of the power plant system. Approaches are based on journal articles and research reports that are taken based on their compatibility with the theme of research. The technical aspects used are hydraulic and civil aspects, mechanical and electrical aspects, while non technical aspects are economic, social and cultural aspects. So with the development of this feasibility rating model can be a reference for developers, government and investors to decide the feasibility of a power plant investment
 
 Keywords: Assessment Feasibility, Hydropower, Power Plant, Feasibility Study, Meta analysis

Photovoltaic solar power plant investment optimization model for economic external balance: Model of Turkey

Through using a linear optimization model that interprets solar energy and current deficit parameters, investment plans were performed for countries which have current deficit problem of energy source. The specifics of the study are due to the linear optimization model, which reveals the current deficit and solar energy together for the investment strategy. While the model is constituted, without affecting the existed current account, some parameters based on such as profit transfers for foreign investments, payments of interest for domestic investments, import rates for photovoltaic solar panels, solar energy electricity production values, electricity demand projection for the future and import resource rates for electricity production. In the framework of these constraints of the model, the effects of solar systems on domestic investment and foreign direct investments on current account balance are analyzed for the period of 2017–2030 in Turkey. In the application of the model in Turkey to reduce the current deficit, this is concluded that the solar energy is a significant opportunity. In addition, the linear optimization model is considered as a reference for countries facing energy-related current deficit problems.

A framework for selecting the location of very large photovoltaic solar power plants on a global/supergrid

One of the important optimization applications (minimization and maximization) is the power grid systems. National electricity grids should be interconnected to develop larger regional grids (supergrids), and further integrated to build up a worldwide grid (global grid) for minimizing consumption of natural resources and maximizing economical useful life, recycling rate, and effective usage of natural resources. These supergrids and global grid concepts can only be developed through detailed and organized supportive research studies. This research study aims to find, define, identify, describe and select location selection factors of very large photovoltaic solar power plant investments on a global grid and supergrid concepts. Grey systems theory, fuzzy (Type-1 and 2) theories, Mamdani’s type fuzzy rule-based system, Interpretive Structural Modelling (ISM), Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) tool, and Political, Economic, Social and Technological (PEST) framework and its extensions (SLEPT, PESTEL, PESTLE, STEEPLE, STEEPLED, DESTEP, STEER) are concurrently used in this study. Eleven (11) criteria are presented for preliminary screening (i.e. C1: global horizontal irradiation (GHI), C2: governments supergrid integration policy, C3: supergrid business climate and conditions, C4: High Voltage Direct Current (HVDC) and High Voltage Alternating Current (HVAC) electrification grid infrastructure, C5: land use, allocation and availability, C6: geological conditions, C7: political, war, terror & security, C8: topographical conditions, C9: climatic conditions, C10: water availability conditions, C11: natural disaster/hazard conditions), and 191 factors are presented for pre-feasibility investment stages. Findings can directly be used or taken as a basis for further analysis by researchers and practitioners.

Geothermal resources in Egypt integrated with GIS-based analysis

The energy of Egypt is generally derived from petroleum products. However, advancements in the development of the generation capacity using sustainable and renewable resources, for example, solar, wind and geothermal resources and investment in nuclear power plants are planned. The geology and structure setting of Egypt affirms that reasonable geothermal resources are available, particularly along the Gulf of Suez, the Red Sea, the Western Desert and parts of the Nile Valley. The main objective of this research is to develop a geothermal favourability map of Egypt, which may be considered as a screening tool for the assessment of optimal areas for geothermal development. Digital data layers and maps were employed in a GIS model to select the most promising areas for geothermal potentiality. The ArcGIS model includes six thematic layers: distance to faults, Bouguer anomaly, distance to seismic activity, Curie depth, heat flow, and temperatures at different depths. The validation of the generated geothermal favourability map was performed by a comparison with thermal water wells and hot springs. Generally, the most encouraging zones for geothermal probability in Egypt are located near the shorelines of the Gulf of Suez and the Red Sea.

Cost-Energy Optimum Pathway for the UK Food Manufacturing Industry to Meet the UK National Emission Targets

This paper investigates and outlines a cost-energy optimised pathway for the UK food manufacturing industry to attain the national Greenhouse Gas (GHG) emission reduction target of 80%, relative to 1990 levels, by 2050. The paper employs the linear programming platform TIMES, and it models the current and future technology mix of the UK food manufacturing industry. The model considers parameters such as capital costs, operating costs, efficiency and the lifetime of technologies to determine the cheapest pathway to achieve the GHG emission constraints. The model also enables future parametric analyses and can predict the influence of different economic, trade and dietary preferences and the impact of technological investments and policies on emissions. The study showed that for the food manufacturing industry to meet the emission reduction targets by 2050 the use of natural gas as the dominant source of energy in the industry at present, will have to be replaced by decarbonised grid electricity and biogas. This will require investments in Anaerobic Digestion (AD), Combined Heat and Power (CHP) plants driven by biogas and heat pumps powered by decarbonised electricity.

REGIONALNA KONWERGENCJA PRODUKTYWNOŚCI PRACY SEKTORÓW WIEJSKICH W KONTEKŚCIE ŚRODKÓW POZYSKANYCH NA ROLNICTWO Z UNII EUROPEJSKIEJ

The production of renewable energy has been increasing in Poland in accordance with the EU mandate. Solar energy use, in particular, has been affected by regulations and the associated subsidy mechanism. The specific aim of the tudy was the verification of the influence exerted by renewable energy regulations on the amount of revenues and duration of the period when an investor can expect positive returns on operating a PV power plant. The analysis involved five scenarios and used financial and operational data shared by the existing PV power plant in Jadowniki, Poland. Two scenarios refer to plants operating under the support mechanism applied before July 1, 2016, while three scenarios consider plants operating under the auction system that became the support mechanism for renewable energy producers on July 1, 2016. Scenarios I and II generate a positive NPV and IRR under the assumed conditions including the use of green certificates. For PV power plants operating since July 1, 2016, Scenarios III and IV show that the return is dependent on the auction price and the size of NPV and IRR discourages investment. Scenario V assumes absence of support in the form of green certificates or through auction systems and generates loss. The continuing changes in the regulation of power generation from renewable energy sources, including solar energy, creates uncertainties that are likely to discourage investment in large commercial PV power plants in Poland.

Optimal design of carbon tax to stimulate CCS investment in China's coal‐fired power plants: A real options analysis

AbstractCarbon tax is an important policy instrument to control greenhouse gases. How to design a suitable carbon tax rate is of significance for policy makers. This study aims to address this issue from a microeconomic perspective by exploring the decision behavior of a potential investor. A trinomial tree model based on real options theory is presented to evaluate carbon capture and storage (CCS) investment in coal‐fired power plants considering uncertain factors. The model is then applied to a case study and the main findings are as follows: (1) carbon tax policy will have a positive effect on the CCS investment. If the carbon price is not high enough to trigger CCS investment, a hybrid mechanism integrating carbon trading and carbon tax to stimulate CCS investment is required; (2) in applying the trinomial tree real options model, the optimal carbon tax rate should be 145.3 RMB/ton for supercritical pulverized coal (SCPC) (or 79.54 RMB/ton for integrated gasification combined cycle (IGCC)) plants under current market condition and at current technological levels; (3) the optimal carbon tax rate is sensitive to uncertainties. Specifically, the optimal tax rate depends largely on not only the cost of the CCS investment but also the portfolio of carbon price volatility and the initial carbon price level. These conclusions provide the theoretical foundations for decision making regarding CCS investment and related policy making. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd.

A combined thermal power plant investment decision-making model based on intelligent fuzzy grey model and ito stochastic process and its application

Uncertainties are often involved in the investment decision making of the coal-fired power plant. They are often characterized by diversity and fuzziness. In order to minimize their adverse effects on the evaluation of investment, we proposed a novel combined thermal power plant investment decision-making model. This model takes the Net Present Value(NPV) as the objective function, and takes the predictions of revenue and cost as the center. With regard to revenue prediction, Self-adapting Intelligent Grey prediction Model (SIGM) combined with Interval Grey number Prediction Model based on the Triangular whitenization weight function(IGPM_T) model is employed to forecast the changing tendency of the on-grid price, which is the decisive factor for revenue of power plant. With respect to cost prediction, Ito stochastic process theory is utilized to simulate the variation tendency of the operating cost of power generation. In order to acquire the key drift and floating coefficients in the formula of Ito process, the combinatorial simulation experiment is conducted, and by visual comparison, rational coefficient combination is determined. Finally, the reliability and validity of the proposed combined model are verified through an example of a coal-fired power plant, and results show that the proposed model can provide satisfactory evaluation for thermal power plant investment.

Committed emissions from existing and planned power plants and asset stranding required to meet the Paris Agreement

Over the coming decade, the power sector is expected to invest ~7.2 trillion USD in power plants and grids globally, much of it into CO2-emitting coal and gas plants. These assets typically have long lifetimes and commit large amounts of (future) CO2 emissions. Here, we analyze the historic development of emission commitments from power plants and compare the emissions committed by current and planned plants with remaining carbon budgets. Based on this comparison we derive the likely amount of stranded assets that would be required to meet the 1.5 °C–2 °C global warming goal. We find that even though the growth of emission commitments has slowed down in recent years, currently operating generators still commit us to emissions (~300 GtCO2) above the levels compatible with the average 1.5 °C–2 °C scenario (~240 GtCO2). Furthermore, the current pipeline of power plants would add almost the same amount of additional commitments (~270 GtCO2). Even if the entire pipeline was cancelled, therefore, ~20% of global capacity would need to be stranded to meet the climate goals set out in the Paris Agreement. Our results can help companies and investors re-assess their investments in fossil-fuel power plants, and policymakers strengthen their policies to avoid further carbon lock-in.

Investment feasibility tracking: the importance of measuring and tracking the success level of the project during commercialization phase

Measuring project success level is a challenging activity. This area of works has attracted many researchers to look deeper into the method of measurement, success factor identification, risk management, and many others relevant topics. However, the project management scope is limited until the project handover stage. After a project handover, the control of a project management changes from Project Management Team to the project owner/commercialization team. From an investor’s point of view, the success of a project delivery needs to be followed by the success of commercialization phase. This paper aims to present an approach on how we track and measure the progress and success level of a project investment in the commercialization phase. This is an interesting topic which probably often being forgotten in many practical case. Our proposed concept modify Freeman and Beale concept by estimating the variance between the Planned Net Present Value / Annual Worth (as it is in the Feasibility Study Document) and the Actual Net Present Value / Annual Worth (until the point time of evaluation). The gap will lead us to the next analysis and give us some important information, especially exposing whether our project investment performs better than the planning or underperformed. Some corrective actions can be suggested based on the provided information. Practical cases to exercise the concept is also provided and discussed; one case in a property sector in the middle of commercialization phase, and another case in a Power Plant investment approaching the end of commercialization phase.

Administracyjnoprawne uwarunkowania rozwoju energetyki wiatrowej w Polsce

On July 15, 2016, a legal act entered into force, which electrified the business community, especially the unconventional energy industry, local government authorities, and all those who saw the development of the alternative energy sector as the only solution for the global energy crisis. This is about the Act of 20 May 2016 on Investments in Wind Power Plants, which set out the conditions, rules and procedures for the location and operation of wind farms with a power greater than the power of a micro installation, as well as the conditions for the location of housing developments (residential buildings and mixed-use buildings) in the vicinity of wind farms. This Act has been named, both by scholars of law and the media, “another special legislation”, although it is not a typical special legislation. Although it is a lex specialis in relation to the Act of 7 July 1994 – Construction Law, as well as the Act of 27 March 2003 on Spatial Planning and Land Development, its provisions, unlike any “special legislation”, do not introduce preferential conditions for investors with regard to identifying location and authorization for the project covered by it. On the contrary, they introduce a number of significant constraints in the process. The legislature’s goal of increasing the transparency of the wind farm building permit process has come at too high a cost; at the expense of violating basic constitutional standards, notably the principle of proportionality and the principle of protection of property.

A Design Method for Incentive-based Demand Response Programs Based on a Framework of Social Welfare Maximization

Demand response program (DR) is expected as one of the most effective alternatives to the traditional power supply-demand operations because it does not require additional investment in power plants and equipment. However, there is still room for discussion on setting of electricity price and rebate level with ensuring resources. This paper presents a pricing method for the DRs based on an idea of social welfare maximization. In the proposed method, decrement of the consumers’ comfort, which is caused by the DR cooperation, is calculated as the appropriate incentive payment. That is, the authors evaluate the negative consumer surplus, and convert it into the incentive payment in the DRs. Meanwhile, the limit of DR requirement is estimated in accordance with the resulting decrement of suppliers’ benefit. Through discussions on numerical results, usefulness of the authors’ proposal is verified.

What Caused the Drop in European Electricity Prices? A Factor Decomposition Analysis

European wholesale electricity prices have dropped by nearly two thirds since their all-time high around 2008. Different factors have been blamed, or praised, for having caused the price slump: the expansion of renewable energy; the near-collapse of the European emissions trading scheme; over-optimistic power plant investments; a decline in final electricity consumption; and cheap coal and natural gas. This ex-post study of European electricity markets from 2008 to 2015 uses a fundamental power market model to quantify their individual contributions on day-ahead prices. The two countries we study in detail, Germany and Sweden, differ significantly: fuel and CO2 prices were important price drivers in Germany, but in Sweden it was electricity demand. This difference is explained by the nature of the hydro-dominate Nordic electricity system. In both countries, however, the single largest factor depressing prices was the expansion of renewable energy. At the same time, Germany's nuclear phase-out had an upward effect on prices. If one defines the Energiewende as the combination of these two policies, its net effect on power prices was negligible.

Study and model development of renewable energy investment feasibility under willingness and ability to pay approach

Solar PV power plant investment in Indonesia is one amongst the alternative for electricity supply to maintain electrical reliability supply and to maximize local energy potential for remote areas. An objective approach in terms of ability and willingness to pay of the community at study location becomes the basis for revenue potential calculation of on this study. Assessment of investment feasibility including economic incentive calculation becomes more important if incentive is required in order to improve return of investment and at the time to provide good quality of energy supply at the lowest possible cost. Community characteristics data on study location is processed using statistical methods and micropower optimization simulation to generate PV system specification and all component needed to invest. To increase the return of investment the economic incentive scenarios are generated to provide alternatives to optimize the economic feasibility while maintaining the technical feasibility based on the ability and willingness to pay of the community, and not inflicting financial loss to the incentive giver. The results of investment feasibility calculation, with various scenarios built for investment alternatives, PV investment is economically feasible based on common investment analysis criteria such as expected NPV (net present value), IRR (internal rate of return), and PBP (payback period).

The importance of project finance for renewable energy projects

Given the magnitude of investment needs into low-carbon power generation, the availability and cost of capital is crucial for successful energy transitions. Recently, a strong increase of non-recourse project finance (as compared to corporate finance on a project sponsor's balance sheets) could be observed for power generation projects. Classical economic motivations for project finance are the prevention of contamination risk, and agency conflicts – however, these reasons do not apply for comparably small projects in low-risk environments, such as many renewable energy projects being realized today. This paper therefore assesses the importance of project finance for renewable energy projects in investment-grade countries, and the underlying drivers to use this kind of finance. Eight potential reasons for using project finance are distilled from economic and finance theory, and then empirically evaluated using a novel dataset for new power plant investments in Germany 2010–2015. Results show that in this extreme case with particularly low investment risks, project finance has much larger importance for renewables than for fossil fuel-based power plants. It is not used to reduce contamination risk or agency conflicts, but, instead driven by the “debt overhang” of non-utility sponsors such as independent project developers. We discuss implications for policy makers, the financial sector, as well as energy scholars concerned with power generation investment decisions.