2014 Power Systems Computation Conference最新文献_第2页

Day ahead energy market and Reliability Unit Commitment: An integrated approach 日前能源市场和可靠性单位承诺:综合方法

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038424

A. Papalexopoulos, P. Andrianesis

{"title":"Day ahead energy market and Reliability Unit Commitment: An integrated approach","authors":"A. Papalexopoulos, P. Andrianesis","doi":"10.1109/PSCC.2014.7038424","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038424","url":null,"abstract":"The restructured electricity markets typically involve a Day-Ahead Market (DAM), which clears bid-in demand that may be generally different (lower) than the demand forecast. This difference gives rise to reliability concerns to the Independent System Operators (ISOs), which are addressed with the deployment of a mechanism that is usually called Reliability (or Residual) Unit Commitment (RUC). Currently, the ISOs execute the RUC process after the DAM application, to procure additional resources, beyond the DAM energy schedules, to meet the demand forecast. In this paper, we compare the currently employed sequential approach, with a proposed integrated approach which combines the functionality of the DAM and the RUC into one market application. We present the market model including all market commodities, namely energy, ancillary services and RUC capacity, for both methodologies, and apply them on a realistic test case, using actual market/system data. We derive quantitative and qualitative results for a practical system, which illustrate the value of the integration of the market and the reliability functions in the forward spot market. The key conclusion from our simulation runs, is that the integrated approach offers substantial efficiencies by procuring all DAM products simultaneously.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122903431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A progressive method to solve large-scale AC optimal power flow with discrete variables and control of the feasibility 一种求解大规模交流离散变量最优潮流的渐进式方法及其控制的可行性

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038395

Manuel Ruiz, J. Maeght, A. Marié, P. Panciatici, A. Renaud

引用次数: 16

A decomposition scheme for Short Term Hydrothermal Scheduling problems suitable for parallel processing 适合并行处理的短期热液调度问题的分解方案

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038355

Tiago Norbiato, A. Diniz, C. Borges

引用次数: 2

Model predictive control for energy storage systems in a network with high penetration of renewable energy and limited export capacity 高可再生能源渗透率和有限输出容量电网中储能系统的模型预测控制

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038359

P. Zeng, Zhi Wu, Xiao-Ping Zhang, Caihao Liang, Yantao Zhang

{"title":"Model predictive control for energy storage systems in a network with high penetration of renewable energy and limited export capacity","authors":"P. Zeng, Zhi Wu, Xiao-Ping Zhang, Caihao Liang, Yantao Zhang","doi":"10.1109/PSCC.2014.7038359","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038359","url":null,"abstract":"This paper considers a novel control strategy for energy storage systems in networks with high penetration of renewable power and limited network capacity based on the combination of model predictive control (MPC) and hierarchical optimization. The objective is to maximize the output, hence the income, from the renewable generation using appropriate charging and discharging control strategy for energy storage systems based on the prediction of renewable power output, demand and network capability in future time horizon. The battery energy storage system can be used to smooth out the variations in renewable energy such as, wind power, and maximize renewable power output whilst meeting the system constraints. Furthermore network interconnection capacity with other systems must be honored. Network interconnection capability depends on many factors including demand and flexible/inflexible generation within the network and also the external systems. In this paper, we show how this problem can be formulated as an optimization problem, leading directly to the design of a model predictive controller. In this scheme, the optimal control for energy storage systems is implemented in a receding time horizon. The method is applied as a case study to the modified IEEE-30 bus test system and northwest power grid of China.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"402 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123379923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

An affine arithmetic approach for microgrid dispatch with variable generation and load 微电网变发电变负荷调度的仿射算法

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038382

M. Pirnia, C. Cañizares, Kankar Bhattacharya, A. Vaccaro

引用次数: 5

Flexibility in generation planning: Identifying key operating constraints 发电计划的灵活性:确定关键的运行约束

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038323

B. Palmintier

{"title":"Flexibility in generation planning: Identifying key operating constraints","authors":"B. Palmintier","doi":"10.1109/PSCC.2014.7038323","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038323","url":null,"abstract":"This paper utilizes the recent methodology of clustered integer unit commitment (UC) - which tractably captures operational flexibility within generation expansion planning - to explore which operating constraints are the most important for generation investment decisions. Flexibility has been previously shown to alter the optimal generation mix, particularly in scenarios with high flexibility required by significant renewables (>=20%) and/or decreased flexibility of some low-carbon technologies (e.g. traditional nuclear). This work explores the potential to relax some operating constraints to speed-up computation while controlling errors. It is found that operating reserves and maintenance are the most important constraints, while hour-to-hour ramping is least important. However, relaxing integers provides the best accuracy vs. performance trade-offs, but only when the linear program (LP) relaxation includes the full problem with UC constraints. This reduces computation time ~50× with the lowest errors across all metrics: cost (-1%), CO2 (-1%), capacity (-9%), and energy mix (-9%). Considerably high speed ups are possible using the LP relaxed formulation with selected subsets of UC constraints. For cost and CO2, the combination of grouped reserves, ramping, maintenance, and LP provides errors around 2% with ~1500× speedup. However, for capacity and energy mixes, only LP provides reasonable errors (<;25%).","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116193639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 44

Operational strategies for predictive dispatch of control reserves in view of stochastic generation 考虑随机发电的控制储备预测调度策略

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038417

S. Delikaraoglou, K. Heussen, P. Pinson

{"title":"Operational strategies for predictive dispatch of control reserves in view of stochastic generation","authors":"S. Delikaraoglou, K. Heussen, P. Pinson","doi":"10.1109/PSCC.2014.7038417","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038417","url":null,"abstract":"In view of the predictability and stochasticity of wind power generation, transmission system operators (TSOs) can benefit from predictive dispatch of slow and manual control reserves in order to maintain reactive reserve levels for unpredictable events. While scenario-based approaches for stochastic optimization are well suited for this problem, it appears that TSOs are hesitant in adopting this method into their practice of predictive dispatch. Differences in the formulation of constraints and cost functions, the timing and reserve product constraints influence the dispatch result significantly and yield varying results with different practical implications. To support adoption, there is a need to study relevant parameters and trade-offs to be considered in introducing such methods to operation practice, enabling also the investigation of alternate reserve product constraints, e.g., to enable reserve contribution from storage-constrained units. This paper introduces a framework for comparison of operational strategies for system balancing, proposes criteria for performance assessment and exemplifies a systematic evaluation of several operation strategies.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"83 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113943360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Aggregated electric vehicles load profiles with fast charging stations 聚合了快速充电站的电动汽车负载分布

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038402

G. Celli, G. G. Soma, F. Pilo, F. Lacu, S. Mocci, N. Natale

引用次数: 37

Generating capacity reliability assessment of the Itaipu hydroelectric plant via sequential Monte Carlo simulation 基于时序蒙特卡罗模拟的伊泰普水电站发电能力可靠性评估

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038436

R. A. Gonzalez-Fernandez, Ricci E. Oviedo-Sanabria, Armando M. Leite da Silva

{"title":"Generating capacity reliability assessment of the Itaipu hydroelectric plant via sequential Monte Carlo simulation","authors":"R. A. Gonzalez-Fernandez, Ricci E. Oviedo-Sanabria, Armando M. Leite da Silva","doi":"10.1109/PSCC.2014.7038436","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038436","url":null,"abstract":"The Itaipu Dam is a well-known hydroelectric plant located at the Paraná River, in the border between Brazil and Paraguay. With an installed capacity of 14GW, Itaipu is currently the world's largest electric energy generation plant and the second largest in terms of installed capacity, reaching in 2012 a total generation of 98.3TWh. This work proposes a probabilistic methodology based on sequential Monte Carlo simulation (MCS) to assess the generating capacity reliability of Itaipu. The main objective is to estimate reliability indices which can quantify the risks of not having sufficient available generation capacity to meet contractual and/or system demands. All deterministic and stochastic data regarding the Itaipu generating units are directly obtained from their operating history data base. Furthermore, many chronological aspects, such as scheduled maintenance and capacity fluctuation, can be easily included in the simulation model. Finally, by taking advantage of the sequential MCS framework, the proposed method can represent both Markovian and non-Markovian state transitions, obtain monthly indices, and also estimate the annualized reliability indices probability distributions. Case studies are presented and discussed in details.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114847607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Analysis and comparison of secondary frequency control reserve activation rules: Pro-rata vs. merit order 二次变频储备激活规则的分析与比较:按比例与择优顺序

2014 Power Systems Computation Conference Pub Date : 2014-08-01 DOI: 10.1109/PSCC.2014.7038293

Iason Avramiotis-Falireas, P. Zolotarev, A. Ahmadi-Khatir, M. Zima

引用次数: 14