scholarly journals Short-term stochastic movements of electricity prices and long-term investments in power generating technologies

2021 ◽  
Author(s):  
Carlo Mari
Keyword(s):  
Electricity Market ◽  
Nuclear Power ◽  
Net Present Value ◽  
Probability Distributions ◽  
Present Value ◽  
Electricity Prices ◽  
Short Term ◽  
Market Prices ◽  
Fuel Prices

AbstractModeling probability distributions for the long-term dynamics of electricity prices is of key importance to value long-term investments under uncertainty in the power sector, such as investments in new generating technologies. Starting from accurate modeling of the short-term behavior of electricity prices, we derive long-term stationary probability distributions. Then, investments in new baseload generating technologies, namely gas, coal and nuclear power, are discussed. In order to compute the stochastic Net Present Value of investments in new generating technologies, the revenues from selling electricity in power markets as well as the costs which come from buying fuels at uncertain market prices must be evaluated over very long time horizons, i.e., over the whole lifetime of the plants. Starting from accurate short-term stochastic models of fuel prices in addition to electricity prices, we provide long-run probability distributions which are used to compute revenues and costs incurring during the whole lifetime of the plants. Five sources of uncertainty are taken into account, namely electricity market prices, fossil fuel prices (natural gas and coal prices), nuclear fuel prices and $$\hbox {CO}_{\text{2 }}$$ CO 2 prices. Our evaluation model is calibrated on empirical data to account for both historical market prices and macroeconomic views about future trends of electricity and fuel prices. The full probability density of the stochastic Net Present Value is thus determined for each generation technology considered in this study.

Robust Constrained Optimization of Short- and Long-Term Net Present Value for Closed-Loop Reservoir Management

SPE Journal ◽  
2012 ◽  
Vol 17 (03) ◽  
pp. 849-864 ◽  
Author(s):  
C.. Chen ◽  
G.. Li ◽  
A.C.. C. Reynolds
Keyword(s):  
Life Cycle ◽  
Net Present Value ◽  
Production Optimization ◽  
Nonlinear Constraints ◽  
Present Value ◽  
Short Term ◽  
Linear And Nonlinear Constraints ◽  
Linear And Nonlinear ◽  
Reservoir Description

Summary In this paper, we develop an efficient algorithm for production optimization under linear and nonlinear constraints and an uncertain reservoir description. The linear and nonlinear constraints are incorporated into the objective function using the augmented Lagrangian method, and the bound constraints are enforced using a gradient-projection trust-region method. Robust long-term optimization maximizes the expected life-cycle net present value (NPV) over a set of geological models, which represent the uncertainty in reservoir description. Because the life-cycle optimal controls may be in conflict with the operator's objective of maximizing short-time production, the method is adapted to maximize the expectation of short-term NPV over the next 1 or 2 years subject to the constraint that the life-cycle NPV will not be substantially decreased. The technique is applied to synthetic reservoir problems to demonstrate its efficiency and robustness. Experiments show that the field cannot always achieve the optimal NPV using the optimal well controls obtained on the basis of a single but uncertain reservoir model, whereas the application of robust optimization reduces this risk significantly. Experimental results also show that robust sequential optimization on each short-term period is not able to achieve an expected life-cycle NPV as high as that obtained with robust long-term optimization.

scholarly journals SEQUENTIAL CAPITAL INVESTMENT DECISION MAKING UNDER EXTREME CASH FL OW SITUATIONS: EVIDENCE USING MONTE CARLO SIMULATION

2015 ◽  
Vol 16 (5) ◽  
pp. 877-900 ◽  
Author(s):  
Wenqing Zhang ◽  
Prasad Padmanabhan ◽  
Chia-Hsing Huang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Capital Investment ◽  
Net Present Value ◽  
Capital Budgeting ◽  
Cash Flows ◽  
Present Value ◽  
Short Term ◽  
Value Analysis

Uncertainty influences a decision maker's choices when making sequential capital investment decisions. With the possibility of extremely negative cash inflows, firms may need to curtail operations significantly. Traditional Net Present Value analysis does not allow for efficient management of these problems. In addition, firm managers may behave irrationally by accepting negative Net Present Value projects in the short term. This paper presents a Monte Carlo simulation based model to provide policy insights on how to incorporate extreme cash flows and manager irrationality scenarios into the capital budgeting process. This paper presents evidence that firms with irrational managers and experiencing extremely negative cash flows may, under certain conditions, reap long term rewards associated with the acceptance of negative Net Present Value projects in the short term. These benefits are largest if cost ratios (discount rates) are small, or investment horizons are high. We argue that acceptance of short term negative Net Present Value projects implies the purchase of a long term real option which can generate positive long term cash flows under certain conditions.

scholarly journals Clustering electricity market participants via FRM models

2020 ◽  
pp. 1-12
Author(s):  
Ayla Gülcü ◽  
Sedrettin Çalişkan
Keyword(s):  
Electricity Market ◽  
Distance Metrics ◽  
Agglomerative Clustering ◽  
Timely Manner ◽  
Short Term ◽  
Clustering Techniques ◽  
Market Participants ◽  
Cosine Distance ◽  
Collateral Mechanism

Collateral mechanism in the Electricity Market ensures the payments are executed on a timely manner; thus maintains the continuous cash flow. In order to value collaterals, Takasbank, the authorized central settlement bank, creates segments of the market participants by considering their short-term and long-term debt/credit information arising from all market activities. In this study, the data regarding participants’ daily and monthly debt payment and penalty behaviors is analyzed with the aim of discovering high-risk participants that fail to clear their debts on-time frequently. Different clustering techniques along with different distance metrics are considered to obtain the best clustering. Moreover, data preprocessing techniques along with Recency, Frequency, Monetary Value (RFM) scoring have been used to determine the best representation of the data. The results show that Agglomerative Clustering with cosine distance achieves the best separated clustering when the non-normalized dataset is used; this is also acknowledged by a domain expert.

LOCA analysis of BWR-4/Mark-I nuclear power plant with TRACE

Kerntechnik ◽  
2021 ◽  
Vol 86 (2) ◽  
pp. 128-142
Author(s):  
J.-J. Huang ◽  
S.-W. Chen ◽  
J.-R. Wang ◽  
C. Shih ◽  
H.-T. Lin
Keyword(s):  
Nuclear Power ◽  
Coupled Model ◽  
Short Term ◽  
Containment System ◽  
Loss Of Coolant Accident ◽  
Main Steam Line ◽  
Main Steam ◽  
Temperature Responses ◽  
Term Analysis

Abstract This study established an RCS-Containment coupled model that integrates the reactor coolant system (RCS) and the containment system by using the TRACE code. The coupled model was used in both short-term and long-term loss of coolant accident (LOCA) analyses. Besides, the RELAP5/CONTAN model that only contains the containment system was also developed for comparison. For short-term analysis, three kinds of LOCA scenarios were investigated: the recirculation line break (RCLB), the main steam line break (MSLB), and the feedwater line break (FWLB). For long-term analysis, the dry-well and suppression pool temperature responses of the RCLB were studied. The analysis results of RELAP5/CONTAN and TRACE models are benchmarked with those of FSAR and RELAP5/GOTHIC models, and it appears that the results of the above four models are consistent in general trends.

Comparison of Spar and Semisubmersible Floater Concepts of Offshore Wind Turbines Using Long-Term Analysis

2015 ◽  
Vol 137 (6) ◽  
Author(s):  
Hasan Bagbanci ◽  
D. Karmakar ◽  
C. Guedes Soares
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Transfer Functions ◽  
Probability Distributions ◽  
Offshore Wind ◽  
Short Term ◽  
Offshore Wind Turbines ◽  
Floating Wind Turbine ◽  
Offshore Floating Wind Turbine

The long-term probability distributions of a spar-type and a semisubmersible-type offshore floating wind turbine response are calculated for surge, heave, and pitch motions along with the side-to-side, fore–aft, and yaw tower base bending moments. The transfer functions for surge, heave, and pitch motions for both spar-type and semisubmersible-type floaters are obtained using the fast code and the results are also compared with the results obtained in an experimental study. The long-term predictions of the most probable maximum values of motion amplitudes are used for design purposes, so as to guarantee the safety of the floating wind turbines against overturning in high waves and wind speed. The long-term distribution is carried out using North Atlantic wave data and the short-term floating wind turbine responses are represented using Rayleigh distributions. The transfer functions are used in the procedure to calculate the variances of the short-term responses. The results obtained for both spar-type and semisubmersible-type offshore floating wind turbine are compared, and the study will be helpful in the assessments of the long-term availability and economic performance of the spar-type and semisubmersible-type offshore floating wind turbine.

Creating continuous areas of old forest in long-term forest planning

2000 ◽  
Vol 30 (11) ◽  
pp. 1817-1823 ◽  
Author(s):  
Karin Öhman
Keyword(s):  
Net Present Value ◽  
Problem Formulation ◽  
Core Area ◽  
Northern Sweden ◽  
Present Value ◽  
The Core ◽  
Long Range Planning ◽  
The Cost

Harvest activities tend often to create landscapes where the old forest is fragmented into isolated patches that provide marginal conditions for species that inhabit forest interiors. This paper presents a long-range planning model designed to maximize the net present value and to create continuous patches of old forest. In this model, the spatial structure of old forest is controlled by core area and edge habitats. Core area is defined as the area of old forest that is free of edge effects from surrounding habitats. The core area requirement is set to a fixed value for each of a number of time periods, whereas the area of edge habitats, which should be as small as possible, is weighted against the net present value. The model is applied in a case study to an actual landscape consisting of 755 stands of forest in northern Sweden and solved using simulated annealing. The results show that distinct continuous patches of old forest are created when both a core area requirement and consideration of the amount of edge habitats are included in the problem formulation. The cost of creating continuous areas of old forest was found to be significant.

scholarly journals Hybrid Forecasting Model for Short-Term Electricity Market Prices with Renewable Integration

2018 ◽  
Vol 11 (1) ◽  
pp. 57 ◽  
Author(s):  
Gerardo Osório ◽  
Mohamed Lotfi ◽  
Miadreza Shafie-khah ◽  
Vasco Campos ◽  
João Catalão
Keyword(s):  
Electricity Market ◽  
Wavelet Transforms ◽  
Fuzzy Inference ◽  
Electricity Sector ◽  
Forecasting Model ◽  
Probabilistic Forecasting ◽  
Short Term ◽  
Market Prices ◽  
Inference System ◽  
Hybrid Particle Swarm Optimization

In recent years, there have been notable commitments and obligations by the electricity sector for more sustainable generation and delivery processes to reduce the environmental footprint. However, there is still a long way to go to achieve necessary sustainability goals while ensuring standards of robustness and the quality of power grids. One of the main challenges hindering this progress are uncertainties and stochasticity associated with the electricity sector and especially renewable generation. In this paradigm shift, forecasting tools are indispensable, and their utilization can significantly improve system operation and minimize costs associated with all related activities. Thus, forecasting tools have an essential key role in all decision-making stages. In this work, a hybrid probabilistic forecasting model (HPFM) was developed for short-term electricity market prices (EMP) combining wavelet transforms (WT), hybrid particle swarm optimization (DEEPSO), adaptive neuro-fuzzy inference system (ANFIS), and Monte Carlo simulation (MCS). The proposed hybrid probabilistic forecasting model (HPFM) was tested and validated with real data from the Spanish and Pennsylvania-New Jersey-Maryland (PJM) markets. The proposed model exhibited favorable results and performance in comparison with previously published work considering electricity market prices (EMP) data, which is notable.

Short-Term and Long-Term Health Risks of Nuclear-Power-Plant Accidents

2012 ◽  
Vol 2012 ◽  
pp. 212-213
Author(s):  
A.D. Elster
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Health Risks ◽  
Nuclear Power ◽  
Short Term

The Need for Strategic Planning for Nuclear Power Plant I&C Upgrades

2002 ◽  
Author(s):  
J. Douglas Hill ◽  
Paul Moore
Keyword(s):  
Strategic Planning ◽  
Control Systems ◽  
Digital Technology ◽  
Nuclear Power ◽  
Power Plants ◽  
Short Term ◽  
Nuclear Plants ◽  
And Control ◽  
Plant Control

Nuclear power plants rely on Instrumentation and Control (I&C) systems for control, monitoring and protection of the plant. The original, analog designs used in most nuclear plants have become or soon will be obsolete, forcing plants to turn to digital technology. Many factors affect the design of replacement equipment, including long-term and short-term economics, regulatory issues, and the way the plant operates on a day-to-day basis. The first step to all modernization projects should involve strategic planning, to ensure that the overall long and short-term goals of the plant are met. Strategic planning starts with a thorough evaluation of the existing plant control systems, the available options, and the benefits and consequences of these options.

The Development of a Generic Qualified Digital Platform

2010 ◽  
Author(s):  
Victor S. S. Shyu ◽  
Ming-Huei Chen
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Systems Design ◽  
Nuclear Industry ◽  
Regulatory Body ◽  
Short Term ◽  
Digital Platform ◽  
And Control ◽  
Nuclear Instrumentation

The nuclear industry and research institutes in Taiwan are conducting a joint effort project to establish a self-reliant nuclear Instrumentation and Control (I&C) system design and fabrication capabilities in Taiwan. The purposes of this project, as called Taiwan’s Nuclear I&C System (TaiNICS), are planned to support digital upgrade of the existing nuclear power plants and the new nuclear installations in Taiwan. The project will be a long term pursuit of several task branches, including establishment of a generic qualified digital platform, qualification and certification processes, nuclear I&C systems design, safety analyses for software common cause failure, licensing, and collaboration. The short term goal of this project is to submit the License Topical Report (LTR) of a generic digital platform for the review of Taiwan’s regulatory body in 2013.

Sign in / Sign up

Export Citation Format

Share Document