Article
Engineering, Electrical & Electronic
Dongliang Xiao, Haoyong Chen, Chun Wei, Xiaoqing Bai
Summary: This study proposes a statistical measure and a stochastic optimization model for generating risk-seeking wind power offering strategies in electricity markets. The statistical measure, called value at best (VaB), quantifies potential high profits in the best-case scenarios of a profit distribution. The stochastic optimization model based on VaB helps wind power producers manage potential high profits from a probabilistic perspective.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Management
Mahboobeh Peymankar, Morteza Davari, Mohammad Ranjbar
Summary: This paper discusses the maximization of expected net present value of a project under uncertain cash flows using discrete scenarios. It proposes two ILP formulations and two-stage stochastic programming approaches, utilizing Benders decomposition, to address the problem efficiently. The computational results demonstrate that the developed Benders-based methods outperform the ILP formulations.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Economics
Zachary Lucy, Jordan Kern
Summary: Large scale wind power projects are increasingly selling power directly into wholesale electricity markets, leading to a need for financial hedging contracts to mitigate price risk. The use of fixed volume price swaps is common but has drawbacks that reduce effectiveness, as explored in this paper. Research findings suggest that wind power producers should hedge lower volumes of power production and reduce basis risk to improve contract performance.
Article
Thermodynamics
Omidreza Lak, Mohammad Rastegar, Mohammad Mohammadi, Soroush Shafiee, Hamidreza Zareipour
Summary: This study proposes two-stage stochastic models for wind power producers and energy storage systems to participate in multiple markets simultaneously, analyzing the risks and profits. Results show that joint operation can increase profits, but considering transmission tariffs may have a negative impact. Sensitivity analysis on penalty factors is also conducted to show their influence on market participation.
Article
Green & Sustainable Science & Technology
Bernard Dusseault, Philippe Pasquier
Summary: Hybrid ground-coupled heat pump systems can efficiently heat and cool buildings, but their financial profitability is hard to establish during the design phase. By using the net present value-at-risk indicator, uncertainties can be addressed throughout the design process, leading to shorter payback periods and reduced financial risks. Describing uncertain parameters statistically during sizing can result in more conservative, efficient, and financially viable designs.
Article
Mathematics
Josefa Lopez-Marin, Amparo Galvez, Francisco M. del Amor, Jose M. Brotons
Summary: This article evaluates the viability of greenhouse pepper cultivation by using discounted cash flows, analyzing risks through decoupled net present value and decreasing discount functions. The study isolates main risks such as price drops and structural risks, providing a more realistic investment estimation. Sensitivity analysis shows that decoupled net present value is less affected by changes in interest rates compared to traditional net present value.
Article
Business, Finance
Hui-Wen Tang, Chong-Chuo Chang
Summary: This study examines the impact of CEO overconfidence on additional risk-taking, firm value, and financial constraints using data from the three major US stock exchanges. The results show that CEO overconfidence has a positive effect on firm overinvestment and can be incentivized through offering higher incentive compensation. Additionally, it is found that non-overconfident CEOs with a higher percentage of incentive compensation exhibit more rational risk-taking behavior and alignment with shareholders' interests.
NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE
(2024)
Article
Energy & Fuels
Zbyslaw Dobrowolski, Grzegorz Drozdowski
Summary: This article explores the universality of net present value (NPV) as a financial metric and proposes a modified NPV formula to evaluate energy firms in emerging markets. The study finds that the variable discount rate influences the time value of money and suggests the need for redefining the NPV formula. This research contributes to financial planning and risk management and provides insights for analysis in other energy sectors.
Review
Chemistry, Physical
Anudipta Chaudhuri, Rajkanya Datta, Muthuselvan Praveen Kumar, Joao Paulo Davim, Sumit Pramanik
Summary: This paper explores the current status of wind energy as a renewable energy source and the classification, mechanical materials, and electrical components of wind energy conversion systems. The flow of power and control strategies in wind energy conversion are discussed, with a focus on the maximum power-point tracking controller as an effective control method. The paper also discusses current trends and future prospects in wind energy conversion, highlighting the threat of recycling polymer matrix composite materials to wind power plants and their supply chain industries.
Article
Engineering, Electrical & Electronic
Xuan Zhang, Yumin Zhang, Xingquan Ji, Pingfeng Ye, Jingrui Li
Summary: This paper proposes an IES-UC optimization model that incorporates power-to-Gas (P2G) and wind power conditional value at risk (CVaR) to address the challenges of wind power grid connection and mitigate operational risks. Uncertainty of wind power is analyzed using CVaR theory, while P2G methods and power storage devices are used to reduce curtailment and mitigate operational risks. The dynamic transmission equations of the gas and thermal networks are derived to exploit the flexibility and enhance wind power accommodation capacity. A linearized version of the CVaR model is also presented for computational efficiency. Simulations on test systems validate the effectiveness and feasibility of the proposed model.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Su Wang, Bo Sun, Liang Ni, Steven H. Low, Danny H. K. Tsang
Summary: The stochastic economic dispatch (SED) is a promising solution for short-term cost-efficiency with high renewable penetration. However, little research has been done on the long-term efficiency of SED in promoting efficient investments in flexibility resources and renewable generators. This study theoretically reveals the financial incentives for efficient investments in SED from both short-term and long-term perspectives and shows that SED can motivate investments in flexibility resources and renewables to improve system efficiency and reliability in the long run. Simulations are conducted for validation.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Engineering, Industrial
Robert W. Grubbstrom
Summary: This paper examines the distribution properties of the net present value (NPV) when affected by stochastic disturbances in the form of a random walk process. Two different scenarios, Case A and Case B, are studied, revealing distinct consequences on the distribution of NPV. It is also shown that different leverage values impact the stability and determinism of NPV under these scenarios.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Article
Green & Sustainable Science & Technology
Rabab Rabbani, Muhammad Zeeshan
Summary: This study evaluates the techno-economic feasibility of wind power plants in Pakistan under different policy scenarios, considering both local and foreign financing options. The results show that Sujawal is the most favorable location with the shortest payback period, while the decrease in tariffs for wind power over time has a negative impact on the project's economic benefits.
Article
Engineering, Electrical & Electronic
Ana Sofia Aranha, Alexandre Street, Cristiano Fernandes, Sergio Granville
Summary: This work proposes a dynamic model to represent sequential decision making in power systems with high renewable energy penetration. It considers uncertainties in both long-term and short-term levels as path-dependent stochastic processes. The model accounts for correlations between inflow forecasts, renewable generation, spot and contract prices through interconnected long- and short-term decision trees. A case study of the Brazilian power sector demonstrates the value of the model in defining optimal trading strategies for wind power generators.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Operations Research & Management Science
Mahboobe Peymankar, Mohammad Ranjbar
Summary: The study investigates a project scheduling problem with periodically variable cash flows aiming to maximize net present value (NPV). It considers deterministic and stochastic cash flow scenarios, developing integer linear programming and multi-stage stochastic programming models respectively. The study analyzed the performance of solution approaches through randomly generated test instances and compared the sensitivity of important parameters between deterministic and stochastic models.
ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH
(2021)
Review
Energy & Fuels
Anna Manuella Melo Nunes, Luiz Moreira Coelho, Raphael Abrahao, Edvaldo Pereira Santos, Flavio Jose Simioni, Paulo Rotella, Luiz Celio Souza Rocha
Summary: The development and implementation of public policies for renewable energies are crucial for addressing contemporary challenges. This study analyzed these policies from the perspective of the circular economy, finding that they have positive economic returns and contribute to reducing greenhouse gas emissions. However, barriers to implementation in the private sector and resistance to raising awareness in society require strong public sector engagement and evaluation of policies. Overall, the circular economy promotes more efficient structures and alternative solutions for energy security and sustainability.
Review
Energy & Fuels
Karel Janda, Eva Michalikova, Luiz Celio Souza Rocha, Paulo Rotella Junior, Barbora Schererova, David Zilberman
Summary: This study provides a comprehensive review of the recent literature on the impact and contribution of corn ethanol to retail gasoline prices in the US. It identifies the main characteristics and clusters of the literature, explores the numerical impact of the VEETC/RFS mandate on gasoline prices, and identifies the main trends and potential research directions. The prevailing result in the literature indicates that the addition of ethanol reduces the price of gasoline, with estimates ranging from no effect to nearly 10% off the price of gasoline.
Article
Thermodynamics
Victor A. D. Faria, Anderson Rodrigo de Queiroz, Joseph F. DeCarolis
Summary: This research proposes an analytical decision-making framework to define renewable offshore portfolios using artificial neural networks and risk-averse stochastic programming. Synthetic energy scenarios are generated using a generative adversarial neural network, considering distributed resources over large geographic regions. A stochastic model is then used to determine the optimal location and number of turbines for each technology. The framework is tested using data from the U.S. East coast, demonstrating the ability to create statistically consistent energy scenarios and the significance of resource diversification in improving system security.
Article
Energy & Fuels
Lucas Barros Scianni Morais, Giancarlo Aquila, Victor Augusto Duraes de Faria, Luana Medeiros Marangon Lima, Jose Wanderley Marangon Lima, Anderson Rodrigo de Queiroz
Summary: This paper investigates the application of shallow and deep neural networks in modeling short-term load forecasting problem. Different model architectures including multi-layer perceptron, long-short term memory, and gated recurrent unit are tested, and global climate model information is used as input for more accurate predictions. A case study for the Brazilian interconnected power system is presented and compared with forecasts from the Brazilian Independent System Operator model. The results show that bidirectional long-short term memory and gated recurrent unit outperform other models, achieving Nash-Sutcliffe values up to 0.98 and mean absolute percentile error values of 1.18%, superior to the results obtained by the Independent System Operator models (0.94 and 2.01% respectively). The better performance of neural network models is confirmed under the Diebold-Mariano pairwise comparison test.
Review
Energy & Fuels
Giancarlo Aquila, Lucas Barros Scianni Morais, Victor Augusto Duraes de Faria, Jose Wanderley Marangon Lima, Luana Medeiros Marangon Lima, Anderson Rodrigo de Queiroz
Summary: The development of smart grid technologies enables the integration of new and intermittent renewable energy sources into power systems. This requires accurate short-term load demand forecasting, which is crucial for supply strategies, system reliability decisions, and price formation. Machine learning models, such as Neural Networks and Support Vector Machines, have gained popularity due to advancements in mathematical techniques and computational capacity. The study reviews various methods used for short-term load forecasting, with a focus on machine learning strategies, and discusses the Brazilian experience.
Article
Oceanography
Jorge Yuri Ozato, Giancarlo Aquila, Edson de Oliveira Pamplona, Luiz Celio Souza Rocha, Paulo Rotella Junior
Summary: This study compares the cost-effectiveness of offshore wind farms at five different locations on the Brazilian coast, considering taxation and tradable green certificates. The results indicate that the taxation method and the best location for harnessing wind energy are the key factors affecting cost reduction and financial risk.
OCEAN & COASTAL MANAGEMENT
(2023)
Article
Energy & Fuels
Gabriel Nasser Doyle de Doile, Paulo Rotella, Luiz Celio Souza Rocha, Karel Janda, Rogerio Peruchi, Giancarlo Aquila, Pedro Paulo Balestrassi
Summary: Photovoltaic systems are crucial for decarbonizing electricity production. To increase the amount of photovoltaic energy generation and reduce reliance on the grid, local battery energy storage systems are being considered. However, the profitability of installing a PV system with battery storage depends on the specific context and regulations in place.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Arthur Leandro Guerra Pires, Paulo Rotella Junior, Luiz Celio Souza Rocha, Rogerio Santana Peruchi, Karel Janda, Rafael de Carvalho Miranda
Summary: The present study proposes a multi-objective optimization method for wind and photovoltaic (PV) hybrid generation with battery energy storage, considering a tariff policy issue for the grid-connected residential scenario. The proposed method used Response Surface Methodology (RSM) to model two objective functions, one environmental (Carbon footprint) and the other financial (Net Present Value - NPV) in relation to four controllable variables. The study found that only regions with favorable environmental conditions and higher energy tariffs became financially viable for the proposed model, with NPV values ranging from R$-76,080.94 to R$ 69,675.23. The research suggests the need for incentives mainly related to wind energy and batteries, which are still expensive elements in the national scenario for residential generation, reducing the probability of achieving economic viability.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)
