检索结果-内蒙古大学图书馆

The future of power generation in Brazil: An analysis of alternatives to Amazonian hydropower development

ENERGY FOR SUSTAINABLE DEVELOPMENT 2017年 41卷 24-35页

作者： de Faria, Felipe A. M. Jaramillo, Paulina Carnegie Mellon Univ Dept Engn & Publ Policy 5000 Forbes Ave Pittsburgh PA 15213 USA

The Brazilian government has plans to build 26 large hydropower plants in the Amazon basin between 2013 and 2028. These plants will have a total installed capacity of 44 GW, 9000 km(2) of reservoir area, and a total cost of US$ 30-70 billion. In this paper we aim to evaluate alternative generation pathways to avoid the adverse social and environmental impacts associated with reservoirs in the Amazon. Specifically we model the Brazilian electricity network under five capacity expansion scenarios. We assumed the government expansion plans as the baseline and created alternative scenarios where wind and natural gas power plants replace large Amazonian hydropower plants. We compared the scenarios using several performance indicators: greenhouse gas emissions, land use, capital and operational costs, wind curtailments, and energy storage in the hydropower reservoirs. The simulations suggest that a more aggressive policy towards wind generation than the baseline has the potential to replace Amazon hydropower providing advantages to the system operation (e.g., higher storage in hydropower reservoirs). However, when installedwind capacity reaches 24% to 28% of the total installed capacity, more thermal generation is required to balance the hydro-wind variability, increasing the operational costs and greenhouse gas emissions compared to the baseline. (C) 2017 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

关键词： stochastic dual dynamic programming Brazilian power system Impact assessment

来源：评论

学校读者我要写书评

暂无评论

Uncertainty dynamics in energy planning models: An autoregressive and Markov chain modeling approach

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2024年 191卷

作者： Guevara, Esnil Babonneau, Frederic Homem-de-Mello, Tito Univ Finis Terrae Fac Econ & Business Ctr Econ & Sustainable Business Providencia Chile KEDGE Business Sch Talence France ORDECSYS Chene Bougeries Switzerland Univ Adolfo Ibanez Sch Business Penalolen Chile

This paper deals with the modeling of stochastic processes in long-term multi -stage energy planning problems when limited information is available about the distributions of such processes. Starting from simple estimates of variation intervals for uncertain parameters, such as energy demands and costs, we model the temporal correlation of these parameters through carefully constructed autoregressive (AR) models that respect intervals defined in each period. We introduce a coefficient for "zigzag"effects in the evolution of uncertain processes, which controls the correlation across periods and also the likelihood of extreme scenarios. preserve the convexity of the stochastic problem, we discretize the AR models associated with the cost parameters involved in the objective function by Markov chains. The resulting formulation is then solved using a stochastic dual dynamic programming (SDDP) algorithm available in the literature that handles finite -state Markov chains. Our numerical experiments, carried out on the Swiss energy system, show a very desirable adaptation strategy of investment decisions to uncertainty scenarios, a behavior that is not observed when the temporal correlation is ignored. Moreover, the solutions lead to better out -of -sample cost performances, especially on extreme scenario realizations, than the non -correlated ones which usually result in overcapacities to protect against high, but unlikely, parameter variations over time.

关键词： Energy planning Uncertainty modeling Temporal correlation Autoregressive processes Markov chains stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Bi-objective multistage stochastic linear programming

引用

MATHEMATICAL programming 2022年第1-2期196卷 907-933页

作者： Dowson, O. Morton, D. P. Downward, A. Northwestern Univ Dept Ind Engn & Management Sci Evanston IL 60208 USA Univ Auckland Dept Engn Sci Auckland New Zealand

We propose an algorithm for solving a class of bi-objective multistage stochastic linear programs. We show that the cost-to-go functions are saddle functions, and we exploit this structure, developing a new variant of the stochastic dual dynamic programming algorithm. Our algorithm is implemented in the open-source stochastic programming solver ***. We apply our algorithm to a hydro-thermal scheduling problem using data from the Brazilian Interconnected Power System. We also propose and implement a computationally tractable heuristic for bi-objective stochastic convex programs.

关键词： Bi-objective Non-convex stochastic dual dynamic programming stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Evaluating policies in risk-averse multi-stage stochastic programming

引用

MATHEMATICAL programming 2015年第1-2期152卷 275-300页

作者： Kozmik, Vaclav Morton, David P. Charles Univ Prague Fac Math & Phys Prague Czech Republic Univ Texas Austin Grad Program Operat Res & Ind Engn Austin TX 78712 USA

We consider a risk-averse multi-stage stochastic program using conditional value at risk as the risk measure. The underlying random process is assumed to be stage-wise independent, and a stochastic dual dynamic programming (SDDP) algorithm is applied. We discuss the poor performance of the standard upper bound estimator in the risk-averse setting and propose a new approach based on importance sampling, which yields improved upper bound estimators. Modest additional computational effort is required to use our new estimators. Our procedures allow for significant improvement in terms of controlling solution quality in SDDP-style algorithms in the risk-averse setting. We give computational results for multi-stage asset allocation using a log-normal distribution for the asset returns.

关键词： Multi-stage stochastic programming stochastic dual dynamic programming Importance sampling Risk-averse optimization

来源：评论

学校读者我要写书评

暂无评论

Estimating the cost savings and avoided CO₂ emissions in Brazil by implementing energy efficient policies

引用

ENERGY POLICY 2014年第Apr.期67卷 4-15页

作者： Calili, Rodrigo F. Souza, Reinaldo C. Galli, Alain Armstrong, Margaret Marcato, Andre Luis M. Pontificia Univ Catolica Rio de Janeiro PUC Rio Dept Elect Engn BR-22451900 Rio De Janeiro RJ Brazil Mines Paristech F-75006 Paris France Univ Fed Juiz de Fora BR-36036900 Juiz de Fora MG Brazil

Investing more in renewable energy sources and using this in a rational and efficient way is vital for the sustainable growth of world. Energy efficiency (EE) will play an increasingly important role in future generations. The aim of this work is to estimate how much the PNEf (National Plan for Energy Efficiency) launched by the Brazilian government in 2011 will save over the next 5 years by avoiding the construction of additional power plants, as well as the amount of the CO2 emission. The marginal operating cost is computed for medium term planning of the dispatching of power plants in the hydro-thermal system using stochastic dynamic dual programming, after incorporating stochastic energy efficiencies into the demand for electricity. We demonstrate that even for a modest improvement in energy efficiency (< 1% per year), the savings over the next 5 years range from R$ 237 million in the conservative scenario to R$ 268 million(1) in the optimistic scenario. By comparison the new Belo Monte hydro-electric plant will cost R$ 26 billion to be repaid over a 30 year period (i.e. R$ 867 million in 5 years). So in Brazil EE policies are preferable to building a new power plant. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Geometric Brownian motion Hydrothermal power system stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第2期257卷 669-686页

作者： Steeger, Gregory Rebennack, Steffen Colorado Sch Mines Div Econ & Business Golden CO 80401 USA

Many decomposition algorithms like Benders decomposition and stochastic dual dynamic programming are limited to convex optimization problems. In this paper, we utilize a dynamic convexification method that makes use of Lagrangian relaxation to overcome this limitation and enables the modeling of non convex multi-stage problems using decomposition algorithms. Though the algorithm is confined by the duality gap of the problem being studied, the computed upper bounds (for maximization problems) are at least as good as those found via a linear programming relaxation approach. We apply the method to the strategic bidding problem for a hydroelectric producer, in which we ask: What is the revenue maximizing production schedule for a single price-maker hydroelectric producer in a deregulated, bid based market? Because the price-maker's future revenue function has a sawtooth shape, we model it using mixed-integer linear programming. To remedy the non-concavity issues associated with modeling the future revenue function as a mixed-integer linear program, we model the price-maker's bidding decision utilizing both Benders decomposition and Lagrangian relaxation. We demonstrate the utility of our algorithm through an illustrative example and through three case studies in which we model electricity markets in El Salvador, Honduras, and Nicaragua. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Lagrangian relaxation Mixed-integer linear programming Benders decomposition Hydroelectric scheduling Strategic bidding problem stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Co-Optimization of Energy and Ancillary Services for Hydrothermal Operation Planning Under a General Security Criterion

引用

IEEE TRANSACTIONS ON POWER SYSTEMS 2017年第6期32卷 4914-4923页

作者： Street, Alexandre Brigatto, Arthur Valladao, Davi M. Pontificia Univ Catolica Rio de Janeiro PUC Rio Elect Engn Dept Rio De Janeiro RJ Brazil Pontificia Univ Catolica Rio de Janeiro PUC Rio Ind Engn Dept Rio De Janeiro RJ Brazil

One of the most used methods for long-term hydrothermal operation planning is the stochastic dual dynamic programming (SDDP). Using this method, the immediate and future water opportunity cost can be balanced and an economic-dispatch policy can be defined for multiple reservoirs under inflow uncertainty. In this framework, equipment outages and reserve deliverability are generally disregarded, despite their strong impact on the operative plan. However, recent advances in robust optimization have shown how to endogenously account for security criteria in scheduling models with reduced computational burden. Within this framework, reserve deliverability is ensured across the network via the co-optimization of energy and reserves (ancillary services). In this paper, we propose a new multistage model for planning hydrothermal coordination that co-optimizes the nominal energy dispatch and individual up and down reserve allocations. The main goal of this paper is to address a general n - K security criterion, such that, for each inflow scenario, the system is capable of withstanding the loss of up to K components, i.e., generation or transmission assets. The proposed methodology uses the column-and-constraint generation algorithm to efficiently incorporate a compound umbrella set of contingencies in the SDDP algorithm. Results for the Brazilian power system data corroborate the effectiveness of the proposed model.

关键词： Adjustable robust optimization column-and-constraint generation co-optimization of energy and ancillary services hydrothermal operation planning N-K security criterion stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

stochastic Optimization of Microgrid Operation With Renewable Generation and Energy Storages

引用

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2022年第3期13卷 1481-1491页

作者： Aaslid, Per Korpas, Magnus Belsnes, Michael M. Fosso, Olav B. Norwegian Univ Sci & Technol N-7465 Trondheim Trondelag Norway SINTEF Energy Res N-7465 Trondheim Trondelag Norway

The operation of energy storage systems (ESSs) in power systems where variable renewable energy sources (VRESs) and ESSs must contribute to securing the supply, can be considered as an arbitrage against scarcity. The value of using stored energy instantly must be balanced against its potential future value and future risk of scarcity. This paper proposes a multi-stage stochastic programming model for the operation of microgrids with VRESs, ESSs and thermal generators that is divided into a short- and a long-term model. The short-term model utilizes information from forecasts updated every six hours, while the long-term model considers the value of stored energy beyond the forecast horizon. The model is solved using stochastic dual dynamic programming and Markov chains, and the results show that the significance of accounting for short- and long-term uncertainty increases for systems with a high degree of variable renewable generation and ESSs and limited dispatchable generation capacity.

关键词： Markov processes Uncertainty Optimization Predictive models Generators Costs Renewable energy sources Energy Management energy storage systems variable renewable energy sources Markov chains quantile regression stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Risk neutral and risk averse approaches to multistage renewable investment planning under uncertainty

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第3期250卷 979-989页

作者： Bruno, Sergio Ahmed, Shabbir Shapiro, Alexander Street, Alexandre Petr Brasileiro SA BR-22453900 Rio De Janeiro RJ Brazil Pontifical Catholic Univ Rio de Janeiro PUC Rio Dept Elect Engn BR-22453900 Rio De Janeiro RJ Brazil Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA Pontifical Catholic Univ Rio de Janeiro PUC Rio Dept Elect Engn BR-22453900 Rio De Janeiro RJ Brazil

Strategies for investing in renewable energy projects present high risks associated with generation and price volatility and dynamics. Existing approaches for determining optimal strategies are based on real options theory, that often simplify the uncertainty process, or on stochastic programming approaches, that simplify the dynamic aspects. In this paper, we bridge the gap between these approaches by developing a multistage stochastic programming approach that includes real options such as postponing, hedging with fixed (forward) contracts and combination with other sources. The proposed model is solved by a procedure based on the stochastic dual dynamic programming (SDDP) method. The framework is extended to the risk averse setting. A specific case study in investment in hydro and wind projects in the Brazilian market is used to illustrate that the investment strategies generated by the proposed approach are efficient. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.

关键词： stochastic programming Renewable energy investment planning stochastic dual dynamic programming Integer programming Risk averse

来源：评论

学校读者我要写书评

暂无评论

Strategic investments: Electrolysis vs. storage for Europe's energy security in the hydrogen era

引用

ENERGY POLICY 2024年 195卷

作者： Blanchard, Ange Paris Saclay Univ Ind Engn Res Dept CentraleSupelec 3 Rue Joliot Curie F-91190 Gif Sur Yvette France

European hydrogen demand is projected to surge in the upcoming decade, leading to a potential risk of excessive dependence on imports, which may exceed 50% by 2035. This paper compares two strategies to tackle this hydrogen import disruption vulnerability. The first option is to invest in Underground Hydrogen Storage (UHS) for strategic stockpiling. The second option is to increase electrolysis capacity to inflate local production potential. We identify the most effective investment strategies for Central Western Europe (CWE) in 2035 by implementing a Multistage stochastic dynamic programming (MSDP) model. Results show electrolysis outperforms UHS in preventing import disruption risks, although the two technologies are complementary. Notably, electrolysis represents 95% of the strategic investment budget. The overall cost of the optimal strategic investment amounts to 5-10% of the total investment in hydrogen infrastructure.

关键词： Hydrogen storage Electrolysis Strategic investment Energy security stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：