Coordinated Scheduling of Wind-Thermal Gencos in Day-Ahead Markets

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modeled by variable costs, start-up costs and technical operating constraints, such as: ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, aiming to maximize the expected profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Bidding strategy of wind-thermal energy producers

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Bidding Decision of Wind-Thermal GenCo in Day-Ahead Market

This paper deals with the self-scheduling problem of a price-taker having wind and thermal power production and assisted by a cyber-physical system for supporting management decisions in a day-ahead electric energy market. The self-scheduling is regarded as a stochastic mixed-integer linear programming problem. Uncertainties on electricity price and wind power are considered through a set of scenarios. Thermal units are modelled by start-up and variable costs, furthermore constraints are considered, such as: ramp up/down and minimum up/down time limits. The stochastic mixed-integer linear programming problem allows a decision support for strategies advantaging from an effective wind and thermal mixed bidding. A case study is presented using data from the Iberian electricity market.

The flora and communities Carnaubal Palm Forest in the northern region of Ceará - Brazil

The “dicótilo-palmácea” mixed forest is found in the fluvial plains (floodplains) of watercourses on the Ceará semiarid region (Brazil), distinguishing from the surrounding vegetation (caatinga) by the prevalence of larger tree species. In the river’s margins, presenting high variability in the extension of the riverbanks, arise floodplains in pedologic complexes mainly composed by neossols and argissols, resulting from the deposition of sediments. In these areas of high fertility soils and subjected to flooding during part of the year, it develops a particular type of riparian vegetation dominated by carnauba palm tree (Copernicia prunifera (Mill.) H.E. Moore) forming a particular type of riparian forest, designated by carnaubal palm forest. We aimed to carry out floristic and phytosociological surveys of carnauba palm forests located in the northern region of Ceará. The classical sigmatist method of Braun-Blanquet was applied and classification analysis (Twinspan) was perfomed. The field work occurred in March 2014 and 2016 in eight areas: Fazenda Pedra Branca (03º 37’ 10’’ S e 40º 18’ 30’’ W, 104 m asl), Vale do Rio Bom Jesus (04º 04’ 42’’ S e 39º 57’ 08’’ W, 200 m asl), Lagoa do Peixe (03º 56’ 28’’ S e 40º 23’ 23’’ W, 97 m asl), Fazenda Peixes (04º 06’ 03’’ S e 40º 32’ 43’’ W, 114 m asl), Fazenda Natividade (04º 02’ 50’’ S e 40º 29’ 03’’ W, 109 m asl), Fazenda Morro Alto (02º 53’ 42’’ S e 39º 54’ 51’’ W, 16 m asl), Fazenda Araticum (03º 04’ 58’’ S e 40º 09’ 36’’ W, 19 m asl) and Fazenda Experimental da UVA (03º 37' 04'' S 40º 18' 18'' W, 200 m asl).The floristic list consists of 170 species, distributed between 127 genera and 50 families. Twenty-seven Brazilian endemic species were identified, from which 8 are exclusive of the Caatinga biome. The Fabaceae was the most representative family, with the highest number of species (28), followed by Poaceae (17), Malvaceaea (14), Euphorbiaceae (12), Asteraceaea (9), Convolvulaceae and Rubiaceae (9). The dominant life forms were therophytes (34%), phanerophytes (30%) and chamaephytes (18%). Two communities were identified as a result of the classification analysis using the Twinspan.