Wind Energy in Colombia (World Bank Studies)
Colombia has an ambitious reform agenda in the power sector.
The country seeks to encourage foreign investment, with an emphasis on hydrocarbons and power capacity expansion; simplify modalities for small-scale energy projects; and renew interest in non-conventional renewable energy technologies with a regulatory framework to facilitate a gradual change in the energy mix. In , Law , which promotes the efficient and rational use of energy and alternative energies, was promulgated.
This law was regulated by Decree , issued in The law and the decree contemplate important aspects such as the stimulus to education and research in renewable energy sources RES. Nevertheless, the program created under this law lacks fundamental aspects to impulse the development of RES significantly, such as a regulatory support system to encourage investment, the definition of policies to promote renewable energy, or quantitative targets for the share of renewable energy.
Limitations such as the ones above present an important legal vacuum for renewable energy in Colombia. The electricity market in Colombia has regulated and non-regulated segments. The regulated market, which is directly contracted and supplied by distribution companies, applies to industrial, commercial, and residential users with power demands under 0.
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In this market, the tariff structure is established by the regulatory agency CREG. In the non-regulated market, consumers with power demands of 0. By law all urban areas in Colombia are classified in one of six socio-economic strata, which are used to determine the level of tariffs for electricity, water and other services. According to that system, consumers living in areas considered as poor - and consumers using low amounts of electricity - receive electricity and natural gas at subsidized tariffs.
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These cross-subsidies are almost entirely approximately 98 percent financed by consumers living in areas considered as being relatively affluent and who use more electricity. The cross-subsidies cover about 25 percent of the electricity and gas bill of low-income consumers. On average, 7.
Subsidies are also given to provide diesel for power production in non-grid-connected zones. The subsidy stratification system in Colombia has proven fairly ineffective at channeling subsidies towards the poor. Although the scheme is broad in its coverage and excludes no more than 2 percent of the poor for services with broad coverage such as electricity, water and sanitation, there are also high leakage rates.
Some percent of subsidy beneficiaries are from the top half of the income distribution and, moreover, only percent of subsidy resources are captured by the poor. Nevertheless, the performance of this subsidy scheme varies depending on the service considered, being water the sector with the poorest performance and telephony the one with the best behavior. A report by the World Bank estimated the following power sector investment needs for Colombia up to . About 60 percent of that relates to maintenance obligations and payment of Power Purchase Agreement PPA guarantees, and the remaining 40 percent to new investment in generation and transmission.
These investment needs are completely related to the SIN and do not take into account the needs associated with the ZNI. There are three different funds and programs that support rural electrification in Colombia, each established at a different time with different purposes, and all administered by the Ministry of Mines and Energy. It contemplated both the expansion of existing networks and the establishment of stand-alone solutions. Projects are presented to the FAER by the local government authorities.
In order to be eligible, they must form part of the local development plan and the investment plan of the corresponding distribution utility and must also pass through the national project screening and evaluation system. With 66 registered electricity producers, private companies own 60 percent of the installed generation capacity and account for 43 percent measured in number of consumers to 49 percent measured in kWh sales of energy supplied to the interconnected grid.
Renewables energies in Colombia and the opportunity for the offshore wind technology
Transmission is carried out by seven different public companies, while distribution and commercialization are in the hands of over 60 companies, both public and private. The Ministry of the Environment, Housing and Territorial Development holds the environmental responsibilities in Colombia and leads the country's commitment towards sustainable development. Within the Ministry, the Climate Change Mitigation Group addresses all the issues related with climate change.
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Because of Colombia's abundant hydroelectric potential, greenhouse gas emissions are very low per capita 1. As of August , there are three registered Clean Development Mechanism CDM projects in the electricity sector in Colombia, with overall estimated emission reductions of , t CO 2 e per year.
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In order to select the appropriate unit root test, it is crucial to test the cross-section dependence in the panel. The first-generation unit root tests Levin and Lin, Im Pesran Shin, Hadri tests are based on cross sectional independence hypothesis. However, the second-generation panel unit root tests are applicable when the panel has cross-sectional dependence.
Pesaran cross-section dependence CD test is based on a simple average of all pair-wise correlation coefficients in the OLS residuals obtained from standard augmented Dickey—Fuller regressions for each variable in the panel [ 39 ]. Table 2 presents the result of Cross- section dependence CD. So, here we have applied a second-generation panel unit root test e. The results show that taking first-differences turns the variables stationary from non-stationary at their levels.
Stationary data suggests the possibility of the existence of long-run relationship among the variables. In this paper, we used the Pedroni and panel co-integration test to check the existence of long-run co-integration among the dependent and independent variables. It is a comprehensive co-integration test that takes into account the heterogeneous intercepts and trend coefficients across cross-sections [ 41 , 42 ]. Table 4 and Table 5 present the results of Pedroni panel co-integration test. Here, four out of seven test statistics confirm the presence of co-integration among the variables for both the models e.
Pedroni introduced fully modified OLS FMOLS to tackle the problems of simultaneity bias, non-exogeneity and serial correlation and obtain asymptotically efficient consistent estimates in panel series [ 43 , 44 ]. The findings of long run output elasticity in FMOLS suggests that renewable and non-renewable energy consumption both cause positive and significant impact on output along with labour and capital. From the findings it is seen that, non-renewable energy consumption contributes to the increase in CO 2 emission more than the GDP growth. Table 7 presents the DOLS long-run elasticity results for panel.
From the findings, it is seen that, non-renewable energy consumption contributes more in the increase of CO 2 emissions compared to GDP. The outcomes are positive for both types of energy consumption.
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Important fact is, renewable energy consumption has the future prospect in ensuring sustainable economic growth, which is not possible with non-renewable energy consumption. Additionally, renewable energy consumption is found effective in reducing CO 2 emissions. From the findings of both FMOLS and DOLS it can be said that, in the long-run, renewable energy consumption can ensure green growth in emerging and developing countries. This section will test the long-run elasticity for individual countries of different regions through country specific FMOLS method, which will give more specific outcomes for the countries of different regions.
In the country-specific long-run output elasticity results for 30 emerging and developing countries, 18 show significant long-run relationship between renewable energy and economic output. Of these 18 countries, 15 show significant and positive relation and 3 have a significant but negative relation between renewable energy and economic output.
Among these 3 countries, 2 are from the African region Uganda, Chad and another from the Asian region Malaysia.
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The present characteristics of energy consumption of these countries show a dependence on fossil fuel energy and limited investment in renewable energy sector. This is resulting in slow deployment of renewable energy. From our results, it is seen that, the impact of renewable energy consumption on economic growth is more than non-renewable energy consumption for Asian, South-Asian and most of the African countries Ghana, Tunisia, South Africa, Zimbabwe and Cameroon.
But for the Latin American and the Caribbean countries, it can be said that economic growth depends on non-renewable energy consumption. For the country specific long-run elasticity results for CO 2 emissions, out of 30 developing countries, 12 show significant results. Of them, 9 show the empirical evidence that, renewable energy consumption will reduce CO 2 emission. But for 3 countries, the increase in renewable energy consumption leads to a slight increase in CO 2 emission, although the rate is lower than that of non-renewable energy consumption.
Depending on the nature and relative importance of renewable energy sources in an economy, the results may change from country to country. These countries have a common practice of using energy mixes both renewable energy and fossil fuel energy in parallel like solar photovoltaic PV for electricity and gas stove for cooking in daily household life. Sometimes, problems arise from the variation in renewable energy technology development, lack of knowledge in operation, fault in designing or installation of plants.
While, in case of the Caribbean countries non-renewable energy consumption plays the dominant role in increasing CO 2 emissions. In order to examine the direction of short-run causality among the variables, we have used the panel causality test based on Dumitreschu and Hurlin According to Dumitreschu and Hurlin , the test value converges to a normal distribution under the homogeneous non-causality hypothesis.