Multi-criteria assessment of potential regions for wind power generation in the State of Rio de Janeiro

Gonçalves Júnior, Elias Rocha; Rangel, Igor Cassiano; Tavares, Allysson Rodrigues Teixeira; Figueira Júnior, Elias Gomes; Erthal Junior, Milton; Souza, Claudio Luiz Melo de

doi:10.1590/0104-530X4747-20

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ORIGINAL ARTICLE • Gest. Prod. 27 (3) • 2020 • https://doi.org/10.1590/0104-530X4747-20 copy

Multi-criteria assessment of potential regions for wind power generation in the State of Rio de Janeiro

Avaliação multicriterial de regiões potenciais para a geração eólica de energia no Estado do Rio de Janeiro

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract:

Due to the current climatic conditions and concerns about the energy generation by renewable sources, wind energy becomes an alternative to meet the existing energy demand. This paper aims to analyze the most promising regions of the State of Rio de Janeiro for the implementation of wind farms for electricity generation. As an analysis tool, we intend to use the Analytic Hierarchy Process (AHP), due to its practicality, to assist in the state’s wind power atlas regions evaluation, identifying generating farms installation feasibility based on logistical, technical and economic aspects. Three suitable regions for wind farms installation were evaluated according to the following criteria: potencial for generation, land cost, interconnection cost to the grid, implementing zones e terrain-landform logistics. It was found that, for the Serrana Region, it is indicated the installation of a wind farm that operates at 50 meters in height, because it only has enough potential for equipment with this height. In the Lakes Region, it is appropriate to use wind turbines of 75 meters in height, highlighting it as the most promising for this equipment height, besides having the best logistics capacity of the three regions. Because it has a greater potential area than the other, the North Region provides a greater total production, also taking into account its greater efficiency in the aerogenerators to 100 meters of height, considering this region as the most appropriate. It is worth highlighting that, in this region, there is potential for installation in all the heights presented, scrutinizing the results obtained.

Keywords:
Renewable energy; Wind energy; Multiple-criteria decision analysis; Analytic hierarchy process; State of Rio de Janeiro

Assigned value	Importance factor
1	Equal importance: the criteria contribute equally to the objective.
3	Moderate Importance: One criterion is slightly more important than the other.
5	Fundamental importance: One criterion is obviously more important than the other.
7	Noted importance: a criterion is clearly demonstrated and its prominence was verified in practice.
9	Excessive importance: the indications that distinguish the criteria are the most absolute.
2 - 4 - 6 - 8	Intermediary values: in case of a doubt by the expert regarding the degree of importance.

Area	Region	Cities
1	North	Campos dos Goytacazes, São Francisco de Itabapoana and São João da Barra.
2	Lakes	Cabo Frio, Araruama, São Pedro da Aldeia, Saquarema, Armação dos Búzios, Rio das Ostras and Arraial do Cabo.
3	Serrana	Petrópolis, Piraí, Paracambi, Vassouras, Mendes and Miguel Pereira.

Criteria	Justification	Preference direction
Potential for generation (Janke, 2010Janke, J. R. (2010). Multicriteria GIS modeling of wind and solar farms in Colorado. Renewable Energy, 35(10), 2228-2234. http://dx.doi.org/10.1016/j.renene.2010.03.014. http://dx.doi.org/10.1016/j.renene.2010.... )	The factor that directly influences the venture, since it is the source and the intensity for the project success.	The higher the wind / solar potential, the more energy can be generated (maximization).
Land cost (Alves & Alves, 2015Alves, J. R. X., & Alves, J. M. (2015). Definição de localidade para instalação industrial com o apoio do método de análise hierárquica (AHP). Production Journal, 25(1), 13-26. http://dx.doi.org/10.1590/S0103-65132014005000023. http://dx.doi.org/10.1590/S0103-65132014... )	The land cost is a criterion that influences the value of the project installation (rent or purchase).	The lower the land value, the lower the project cost (minimization).
Interconnection cost to the grid (Baban & Parry, 2001Baban, S. M. J., & Parry, T. (2001). Developing and applying a GIS-assisted approach to locating wind farms in the UK. Renewable Energy, 24(1), 59-71. http://dx.doi.org/10.1016/S0960-1481(00)00169-5. http://dx.doi.org/10.1016/S0960-1481(00)... )	The project installation costs and the generated energy transmission vary according to installation region distance from the transmission lines.	The lower the distance from the transmission lines, the lower installing costs of new energy transmission lines (minimization)
Implementing zones (Janke, 2010)	The potential area is influenced by the venture installation distance in relation to the roads and wind speed.	The greater the power of the available space and the ease of implementation, the lower the cost and the better is the performance (maximization).
Terrain-landform logistics (Baban & Parry, 2001)	The logistical aspects of terrain, slope, for example, can cause technical installation difficulties, as well as reduce the wind/solar potential of the area.	The more flat the farm and its surroundings relief, the easier the logistical access (maximization).

Region	Height (m)	Area (Km²)	Potential/Area (GWh/Km²)	Total Annual Potential (GWh)
North	50	1844	3.61	995.00
	75	3335	4.12	6,273.00
	100	3908	4.24	12,300.00
Lakes	50	886	3.85	1,613.00
	75	1566	4.41	3,848.00
	100	2130	4.51	5,425.00
Serrana	50	576	3.94	1,145.00
	75	1050	4.26	2,289.00
	100	1484	4.25	3,248.00

Region	Cities	R$ / Hectare	R$ Average / Hectare
North	Campos dos Goytacazes	3,870.00	3,495.00
	São Francisco de Itabapoana	2,935.00
	São João da Barra	3,680.00
Lakes	Cabo Frio	2,420.00	2,420.00
	Araruama	2,420.00
	São Pedro da Aldeia	2,420.00
	Saquarema	2,420.00
	Armação de Búzios	2,420.00
	Rio das Ostras	2,420.00
	Arraial do Cabo	2,420.00
Serrana	Petrópolis	2,420.00	1,932.50
	Piraí	1,905.00
	Paracambi	2,420.00
	Vassouras	1,905.00
	Mendes	1,320.00
	Miguel Pereira	1,625.00

Area	Region	Power plants	Substations	Total
1	North	1	10	11
2	Lakes	0	12	12
3	Serrana	3	11	14

Region	Height (m)	Available zone (Km²)
North	50	1844
	75	3335
	100	3908
Lakes	50	886
	75	1566
	100	2130
Serrana	50	576
	75	1050
	100	1484

Logistics		Weight	North		Lakes		Serrana
Logistics		Weight	Qty.	Total	Qty.	Total	Qty.	Total
Port		5	1	5	1	5	0	0
Landform	Flat	5	1	5	1	5	0	0
Landform	Rugged	0	0	0	0	0	1	0
Federal Highway	Duplicated	3	0	0	1	3	3	9
Federal Highway	Paved	2	2	4	2	4	1	2
State highway	Duplicated	2	0	0	1	2	0	0
State highway	Paved	1	5	5	8	8	12	12
Total			19		27		23

50 meters	C1 (Km²)	C2 (GWh/Km²)	C3 (R$)	C4 (Number)	C5 (Number)
North region	1,844	3.12	3,495.00	11	19
Lakes region	886	3.429	2,420.00	12	27
Serrana region	576	3.5	1,932.50	14	23
Direction	Max	Max	Min	Max	Max
75 meters	C1 (Km²)	C2 (GWh/Km²)	C3 (R$)	C4 (Number)	C5 (Number)
North region	3,335	3.825	3,495.00	11	19
Lakes region	1,566	4.019	2,420.00	12	27
Serrana region	1,050	3.859	1,932.50	14	23
Direction	Max	Max	Min	Max	Max
100 meters	C1 (Km²)	C2 (GWh/Km²)	C3 (R$)	C4 (Number)	C5 (Number)
North region	3,908	4.053	3,495.00	11	19
Lakes region	2,130	4.072	2,420.00	12	27
Serrana region	1,484	3.868	1,932.50	14	23
Direction	Max	Max	Min	Max	Max

Ranking	50 meters	75 meters	100 meters
1	Serrana region	Lakes region	North region
2	Lakes region	North region	Lakes region
3	North region	Serrana region	Serrana region

Universidade Federal de São Carlos Departamento de Engenharia de Produção , Caixa Postal 676 , 13.565-905 São Carlos SP Brazil, Tel.: +55 16 3351 8471 - São Carlos - SP - Brazil
E-mail: gp@dep.ufscar.br

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[1] Source: Adapted from Saaty (1991)Saaty, T. L. (1991). Método de análise hierárquica. São Paulo: McGraw-Hill..