Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Research on evaluation system of emergency disposal plan for power plant incidents

This paper starts with the analysis of the unusual inherence mechanism, from two aspects: accumulating and human error. We put forward twelve factors affected the decision of the emergency treatment plan in practice and summarized the evaluation index system combining with literature data. Then we screened out eighteen representative indicators by used the FDM expert questionnaire in the first phase. Hereafter, we calculated the weight of evaluation index and sorted them by the FAHP expert questionnaire, and came up with the frame of the evaluation rule by combined with the experience. In the end, the evaluation principles are concluded.

A stochastic programming approach for the development of offering strategies for a wind power producer

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

Is the electric vehicle a solution for the wind power integration in the portuguese power system?

The integration of Plug-in electric vehicles in the transportation sector has a great potential to reduce oil dependency, the GHG emissions and to contribute for the integration of renewable sources into the electricity generation mix. Portugal has a high share of wind energy, and curtailment may occur, especially during the off-peak hours with high levels of hydro generation. In this context, the electric vehicles, seen as a distributed storage system, can help to reduce the potential wind curtailments and, therefore, increase the integration of wind power into the power system. In order to assess the energy and environmental benefits of this integration, a methodology based on a unit commitment and economic dispatch is adapted and implemented. From this methodology, the thermal generation costs, the CO2 emissions and the potential wind generation curtailment are computed. Simulation results show that a 10% penetration of electric vehicles in the Portuguese fleet would increase electrical load by 3% and reduce wind curtailment by only 26%. This results from the fact that the additional generation required to supply the electric vehicles is mostly thermal. The computed CO2 emissions of the EV are 92 g CO2/kWh which become closer to those of some new ICE engines.

Optimal offering strategies for wind power producers considering uncertainty and risk

This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

Modeling radionuclides dispersion and deposition downwind of a coal-fired power plant

In this study the inhalation doses and respective risk are calculated for the population living within a 20 km radius of a coal-fired power plant. The dispersion and deposition of natural radionuclides were simulated by a Gaussian dispersion model estimating the ground level activity concentration. The annual effective dose and total risk were 0.03205 mSv/y and 1.25 x 10-8, respectively. The effective dose is lower than the limit established by the ICRP and the risk is lower than the limit proposed by the U.S. EPA, which means that the considered exposure does not pose any risk for the public health.

Measurements of environmental background radiation in the surrounding area of a coal-fired power plant

Certain materials used and produced in a wide range of non-nuclear industries contain enhanced activity concentrations of natural radionuclides. In particular, electricity production from coal is one of the major sources of increased exposure to man from enhanced naturally occurring materials. Over the past decades there has been some discussion about the elevated natural background radiation in the area near coal-fired power plants due to high uranium and thorium content present in coal. This work describes the methodology developed to assess the radiological impact due to natural radiation background increasing levels, potentially originated by a coal-fired power plant’s operation. Gamma radiation measurements have been done with two different instruments: a scintillometer (SPP2 NF, Saphymo) and a gamma ray spectrometer with energy discrimination (Falcon 5000, Canberra). A total of 40 relevant sampling points were established at locations within 20 km from the power plant: 15 urban and 25 suburban measured stations. The highest values were measured at the sampling points near to the power plant and those located in the area within the 6 and 20 km from the stacks. This may be explained by the presence of a huge coal pile (1.3 million tons) located near the stacks contributing to the dispersion of unburned coal and, on the other hand, the height of the stacks (225 m) which may influence ash’s dispersion up to a distance of 20 km. In situ gamma radiation measurements with energy discrimination identified natural emitting nuclides as well as their decay products (212Pb, 214Pb, 226Ra 232Th, 228Ac, 234Th 234Pa, 235U, etc.). This work has been primarily done to in order to assess the impact of a coal-fired power plant operation on the background radiation level in the surrounding area. According to the results, an increase or at least an influence has been identified both qualitatively and quantitatively.

Assessment of heavy metals in the surroundings of coal-fired power plant

This paper aims to survey metal concentrations in soils in the vicinity of a coal-firedpower plant located in southwest of Portugal. Two annual sampling campaigns were carried out to measure a hypothetical soil contamination around the coal plant. The sampling area was divided into two subareas, both centered in the emission source, delimited by two concentric circles with radius of 6 km and 20 km. About 40 samplings points were defined in the influence area. Metals measurements were performed with a portable analytical X-ray dispersive energy fluorescence spectrometer identifying about 20 different elements in each sampling point. The most relevant elements measured included As, Cu, Fe, Hg, Pb, Ti and Zn in both sampling areas. Considering the results obtained in the first sampling campaign, arsenic is predominantly higher within the 6-20 km sampling area. The second sampling campaign showed that both sampling areas presented relatively similar metal concentrations except for Fe, Mn, Sr and Zn which concentration is higher within the 6-20 km sampling area. Also, As, Fe, Mn and Ti concentrations decreased significantly from the first to the second sampling campaign and their concentration were predominately higher in the NE-E and E-SE directions.

Particulate matter flux deposition in the vicinity of a coal-fired power plant

This paper describes the methodology adopted to assess local air quality impact in the vicinity of a coal power plant located in the south of Portugal. Two sampling areas were selected to assess the deposition flux of dust fallout and its potential spatial heterogeneity. The sampling area was divided into two subareas: the inner, with higher sampling density and urban and suburban characteristics, inside a 6-km circle centered on the stacks, and an outer subarea, mainly rural, with lower sampling density within a radius of 20 km. Particulate matter deposition was studied in the vicinity of the coal fired power plant during three seasonal sampling campaigns. For the first one, the average annual flux of dust fallout was 22.51 g/(m2 yr), ranging from 4.20 to 65.94 g/(m2 yr); for the second one was 9.47 g/(m2 yr), ranging from 0.78 to 32.72 g/(m2 yr) and for the last one was 38.42 g/(m2 yr), ranging from 1.41 to 117.48 g/(m2 yr). The fallout during the second campaign turned out to be much lower than for others. This was in part due to meteorological local patterns but mostly due to the fact that the power plant was not working at full power during the second sampling campaign.155

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Maximizing the Social Welfare of Virtual Power Players Operation in Case of Excessive Wind Power

The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.

Energy resources management in three distinct time horizons considering a large variation in wind power

The intensive use of distributed generation based on renewable resources increases the complexity of power systems management, particularly the short-term scheduling. Demand response, storage units and electric and plug-in hybrid vehicles also pose new challenges to the short-term scheduling. However, these distributed energy resources can contribute significantly to turn the shortterm scheduling more efficient and effective improving the power system reliability. This paper proposes a short-term scheduling methodology based on two distinct time horizons: hour-ahead scheduling, and real-time scheduling considering the point of view of one aggregator agent. In each scheduling process, it is necessary to update the generation and consumption operation, and the storage and electric vehicles status. Besides the new operation condition, more accurate forecast values of wind generation and consumption are available, for the resulting of short-term and very short-term methods. In this paper, the aggregator has the main goal of maximizing his profits while, fulfilling the established contracts with the aggregated and external players.

Real Time Pricing Approaches to Deal With Unexpected Wind Power Variations

The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.

Real-Time Tariffs for Electric Vehicles in Wind Power based Power Systems

The use of Electric Vehicles (EVs) will change significantly the planning and management of power systems in a near future. This paper proposes a real-time tariff strategy for the charge process of the EVs. The main objective is to evaluate the influence of real-time tariffs in the EVs owners’ behaviour and also the impact in load diagram. The paper proposes the energy price variation according to the relation between wind generation and power consumption. The proposed strategy was tested in two different days in the Danish power system. January 31st and August 13th 2013 were selected because of the high quantities of wind generation. The main goal is to evaluate the changes in the EVs charging diagram with the energy price preventing wind curtailment.