{"title":"Small-signal stability analysis of delayed power system stabilizers","authors":"V. Bokharaie, R. Sipahi, F. Milano","doi":"10.1109/PSCC.2014.7038316","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038316","url":null,"abstract":"This paper presents a stability analysis of power system stabilizers (PSS) for synchronous generators with inclusion of time delays. The paper shows that a time delay in the PSS feedback loop can improve the small-signal stability of a power system if the regulator gain is properly tuned. The paper provides a proof-of-principle analysis based on the classical model of the synchronous machine as well as a case study based on a detailed transient model of the IEEE 14-bus test system. The paper also provides a discussion on the practical implications that the properties of delayed PSS can have on the control of synchronous machines and of the whole power system.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"41 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":"123296014","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}
{"title":"Hierarchical models of advanced distance protection IEDs","authors":"A. Apostolov","doi":"10.1109/PSCC.2014.7038391","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038391","url":null,"abstract":"Advanced multifunctional distance protection Intelligent Electronic Devices (IEDs) are complex systems with a multi-level functional hierarchy. Their integration in modern IEC 61850 based substation protection, automation and control systems requires good understanding of their functionality and the IEC 61850 principles of object modeling. The goal of this paper is to present a hierarchical object model of such devices.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"20 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":"126573809","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}
{"title":"Classification of disturbance records in power stations based on fuzzy reasoning","authors":"M. Moreto, Dionatan A. G. Cieslak, J. Rolim","doi":"10.1109/PSCC.2014.7038367","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038367","url":null,"abstract":"Nowadays, it is a common practice in power generation utilities to monitor the generation units using Digital Fault Recorders (DFRs). In general, the disturbance records are stored at the utility central office or control center, leading to a substantial amount of data that in practice is not analysed in its totality. This paper describes a methodology to deal with this problem by proposing a fuzzy classification system. From the DFR phasor records, currents and voltages sampled signal are extracted. The data is processed in order to calculate some meaningful features that are applied to a fuzzy inference system. The fuzzyfied input variables are processed by fuzzy rules which emulate the engineers reasoning at the control center. The output of the fuzzy system indicate which kind of disturbance occurred and what is its degree of pertinence. The proposed methodology enables an automated pre-classification of the DFR data helping the engineers by focusing their attention to the most relevant occurrences. Related studies show that approximately 95% of the disturbance records can be automatically archived because they result from normal operational procedures. The results obtained by using real disturbance records show that the proposed scheme is able to correctly classify the occurrences and also to generalize the result from situations not directly represented in the rule set.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"14 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":"121228224","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}
{"title":"Impacts of network expansion on generation capacity expansion","authors":"David Pozo, E. Sauma, J. Contreras","doi":"10.1109/PSCC.2014.7038320","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038320","url":null,"abstract":"A pessimistic three-level equilibrium model for a market-based expansion of both transmission and generation is proposed. The lower (third) level models the market outcome; the intermediate (second) level models the equilibrium in generation capacity expansion by taking into account the outcomes of the market equilibrium at the third level. The upper (first) level models the expansion of the transmission network. The second and third levels are modeled as an Equilibrium Problem with Equilibrium Constraints (EPEC) parameterized in terms of the optimal decisions of the transmission planner. This three-level hierarchy is motivated by the fact that transmission planners should consider expansions in generation that may take place, as well as the clearing of the market related to generation expansion, in order to make their decisions. At the first level, the transmission planner can take different positions with different impacts in the system because a manifold of equilibria is possible with different costs for the system. Unlike previously reported hierarchical approaches, which are implicitly formulated as optimistic, we solve the pessimistic solution of the problem (the transmission planner takes a pessimistic attitude towards the outcome of the generation expansion equilibrium). Results for a test power system are presented in order to show the efficiency and interpretations of the proposed model.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"17 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":"123820734","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}
{"title":"Optimal expansion model of renewable distributed generation in distribution systems","authors":"Sergio Montoya-Bueno, J. Muñoz, J. Contreras","doi":"10.1109/PSCC.2014.7038348","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038348","url":null,"abstract":"This paper proposes an optimal model for expansion, integration and allocation of renewable distributed generation in insular distribution systems. Furthermore, storage systems are included. The model aims to minimize renewable distributed generation (photovoltaic and wind) investment, operating costs and energy losses. The constraints include voltage limits, feeders' capacities, renewable DG units per node and storage systems. In addition, load demand, solar irradiation, and wind speed are considered as stochastic inputs. The problem is formulated as a stochastic mixed-integer linear programming model. The objective function and the constraints are linearized to obtain the optimal solution. A real case study shows the applicability of the model in an insular distribution system.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"280 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":"116557330","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}
{"title":"Hybrid evolutionary-adaptive approach to predict electricity prices and wind power in the short-term","authors":"G. Osório, J. Matias, J. Catalão","doi":"10.1109/PSCC.2014.7038453","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038453","url":null,"abstract":"Nowadays, with the new paradigm shift in the energy sector and the advent of the smart grid, or even with the mandatory imposition for a gradual reduction of greenhouse gas emissions, the renewable producers, namely the wind power producers are faced with the competitiveness and deregulated structure that characterizes the liberalized electricity market. In a liberalized electricity market, the most important signal for all market players corresponds to the electricity prices. In this sense, accurate approaches for short-term electricity prices prediction are needed, and also for short-term wind power prediction due to the increasing share of wind generation. Hence, this paper presents a new hybrid evolutionary-adaptive approach for wind power and electricity market prices prediction, in the short-term, based on mutual information, wavelet transform, evolutionary particle swarm optimization and adaptive neuro-fuzzy inference system, tested on real case studies, proving its superiority in a comprehensive comparison with other approaches previously published in the scientific literature.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"1 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":"122792154","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}
F. Ruelens, B. Claessens, Stijn Vandael, Sandro Iacovella, P. Vingerhoets, R. Belmans
{"title":"Demand response of a heterogeneous cluster of electric water heaters using batch reinforcement learning","authors":"F. Ruelens, B. Claessens, Stijn Vandael, Sandro Iacovella, P. Vingerhoets, R. Belmans","doi":"10.1109/PSCC.2014.7038106","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038106","url":null,"abstract":"A demand response aggregator, that manages a large cluster of heterogeneous flexibility carriers, faces a complex optimal control problem. Moreover, in most applications of demand response an exact description of the system dynamics and constraints is unavailable, and information comes mostly from observations of system trajectories. This paper presents a model-free approach for controlling a cluster of domestic electric water heaters. The objective is to schedule the cluster at minimum electricity cost by using the thermal storage of the water tanks. The control scheme applies a model-free batch reinforcement learning (batch RL) algorithm in combination with a market-based heuristic. The considered batch RL technique is tested in a stochastic setting, without prior information or model of the system dynamics of the cluster. The simulation results show that the batch RL technique is able to reduce the daily electricity cost within a reasonable learning period of 40-45 days, compared to a hysteresis controller.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"57 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":"127647775","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}
{"title":"Probabilistic security constrained optimal power flow for a mixed HVAC and HVDC grid with stochastic infeed","authors":"R. Wiget, Maria Vrakopoulou, G. Andersson","doi":"10.1109/PSCC.2014.7038408","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038408","url":null,"abstract":"This paper formulates a probabilistic security-constraint optimal power flow considering a combination of an AC system and a multi-terminal HVDC grid that can depict the future power systems. The probabilistic formulation is discussed considering uncertainty in the generation infeed (e.g. wind power). To achieve a tractable problem we use a linearized version of the power flow equations of the combined grid where the voltage angles (of the HVAC grid) and the voltage magnitudes (of the HVDC grid) are eliminated. The flexibility introduced by the HVDC terminals is exploited for control of the power flows in a corrective way, i.e adjust their setpoints after the occurrence of a contingency. The method is applied at the three area IEEE RTS96 test system and the costs, power flows and security levels are investigated. A comparison between a deterministic and the proposed probabilistic method is done.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"108 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":"131918237","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}
{"title":"A linear decision rule approach for robust unit commitment considering wind power generation","authors":"Peng Xiong, P. Jirutitijaroen","doi":"10.1109/PSCC.2014.7038414","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038414","url":null,"abstract":"This paper proposes a robust optimization formulation to solve unit commitment (UC) problems under wind energy uncertainties. Unlike the conventional stochastic programming or chance-constrained methods, this robust approach does not require information on the exact distribution of wind power. Instead, it protects the system against load loss under all possible wind generation scenarios within a straightforward uncertainty set. The level of conservatism of yielded UC decisions can be readily adjusted by the parameters of the uncertainty set. This robust UC is formulated as a two-stage problem, and the linear decision rule technique is applied to approximate the recourse decisions, so that the solution is computationally tractable. Case studies based on the IEEE Reliability Test System are conducted to demonstrate the performance of the proposed method. The results show that this method can well manage the uncertainty of wind power in UC decision-making.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"80 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":"134504976","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}
{"title":"Impact of improved models on the reliability calculation of offshore wind farms","authors":"Issam Athamna, M. Zdrallek, E. Wiebe, F. Koch","doi":"10.1109/PSCC.2014.7038437","DOIUrl":"https://doi.org/10.1109/PSCC.2014.7038437","url":null,"abstract":"Reliability calculation programs for electrical power systems are available since the early 80s and have been since then continuously developed e.g. [1] [2]. However, these programs are designed for conventional power supply systems which consist of predominantly consumers. Through the development of electrical power systems in Europe and particularly the establishment of many new offshore wind farms, these lead to an enormous change in the power supply grids (infeed grids). Therefore it is a substantial need for adaptation of these programs to determine the reliability of the overall power system in a realistic way. In this paper, additionally to the offshore specific reliability indices, three new models are presented. These models are especially created for offshore wind farms and their characteristics. These models are respectively: the weather influence model, the power infeed control model and the reliability modeling of the wind turbine generator (WTG). Based on one exemplary wind farm design, the developed models are compared with the conventional models. This work presents the impact of the different improved models on the reliability results. The importance and the necessity of these established models in order to reach more realistic and environmental depended reliability analysis results are hereby illustrated.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"319 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":"133400906","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}