Evaluation of influential factors in the choice of micro-generation solar devices: a case study in Cyprus

Transcription

1 Evaluation of influential factors in the choice of micro-generation solar devices: a case study in Cyprus Mehrshad Radmehr, PhD, Newcastle University 33 rd USAEE/IAEE Conference, Pittsburgh, Pennsylvania Oct 25-28, 2015

2 Choice experiments technique (CEs) The CE sets choices in the form of qualitative or discrete choices which are assigned with different levels. Respondents choose over a bundle of alternatives and Make trade-offs between the levels of attributes. Willingness to pay (WTP) can also be estimated from the trade-offs that they make.

3 Choice experiments technique (CEs) A change in the attributes levels or marginal effects of attributes yields information on the individual s level of preferences. The information compiled can be quantified to address the factors that influence an individual s choice. One of the most used survey methods, particularly for nonmarket valuation in environmental economics projects (Scarpa and Rose, 2008).

4 Obligations & Objectives The adoption of a national action plan is obligatory for each member state( EU Commission directive 2009/28/EC) for Renewable energy (RE) utilization. Until 2010, the total consumption of RE was only 2.9% in Cyprus, but recently the EU proposed a binding target of RES of 13% for total use of energy, with a 5% reduction of greenhouse gas emissions by To develop plans for implementing projects on RE sources technologies in the sectors of: 1. Electricity 2. Heating/Cooling, 3. Transport.

5 Cyprus location

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7 RE potential Cyprus has 300 days of sunny weather per year A high potential for solar energy utilization above other renewable energy sources, in particular micro-generation solar panels. Despite; - Average daily solar radiation varies from 2.3 to 7.2 kwh per square metre during winter and summer ( highest in Europe) utilization is low - Completely reliant on imported fossil fuels therefore the costs of electricity and gas is high

8 RE exploitation in Cyprus could provide Firstly, the security of the supply of energy via : 1. diversification of energy sources, 2. increasing the country s energy self-sufficiency, 3. maximization of the efficiency of RES utilization as a substitute to the imported sources..secondly, the competitiveness and adoption of investment in the energy sector to maximize the benefit from the exploitation of the resources.

9 Continues Thirdly, environmental protection and the pursuit of sustainable development schemes. Fourthly, to overcome the demand for new power plant due to an annual increase in power consumption and demand. (approx. 10%) Finally, Job creation : possibility of assembling and manufacturing of PV in Cyprus with increase in demand

10 Unsuccessful government attempts Lack of education and awareness Failing trusts among households No workable policy Various installation incentives and feed-in tariffs

11 The survey initiated in 2011 Individuals choices were tested using the CEs procedure to uncover the extent of households acceptance of compensation and propensity to purchase a micro-generation solar system. The sample population was selected based on the random sampling. Households aged 18 and above. The mode of face to face interview was used. Pre-studies were carried out to test the factors in the CE and their levels: Focus groups Interviews Pilot studies and revisions.

12 The attributes comprised: CEs Survey government subsidy, feed-in tariff (FIT), investment cost, energy savings, space required for installation.

13 Factors and their levels Attributes Attribute levels Subsidy 10%, 25%, 40% Feed-in tariff (FIT) 0.10, 0.20, m 2 ; 1kWp Space required 16m 2 ; 2kWp 25m 2 ; 3kWp 40m 2 ; 4kWp Initial investment cost 4000, 6000, 8000, 10000, 12000,14000 Energy saving (Annual) 800,1200,1500, 2000, 3000, 3600

14 Respondents were asked to choose their most preferred alternative from two hypothetical scenarios of attributes and do nothing. I would choose neither of the alternatives An example of a generated generic choice card designed

15 Data A CE survey of 205 respondents was carried out to evaluate the attributes that influence respondents choices in the adoption of micro-generation solar panels. Each respondent was presented with six choice cards in sequence. The total collected data from 205 respondents yielded 1,230 choice sets and 3,690 numbers of cases, estimated in NLOGIT5.0.

16 CE Survey procedure To prevent the hypothetical effect, micro-generation solar technology and its attributes was introduced by images, visual aids, and hints. Finally, the survey was finished with a set of demographic questions.

17 Analyses The Conditional logit (CL) model examines the differences between the scenarios characteristics or the levels of attributes. It tests the variance between choice alternatives. It estimates the impact of the specific variables on the probability of choosing a particular alternative.

18 Conditional logit(cl)model The CL model is a reliable and basic random utility model for analyzing CE data (Scarpa et al., 2005, p.253). The CL model assumes the disturbance term is independent from irrelevant alternatives (IIA) across the individual s choices. Therefore, the choice probability can be expressed as follows:

19 Conditional logit(cl)model We assumed that in the CL model each individual s random utility related to choosing alternative j was a linear function of its features, namely subsidy, FIT, space, cost, and energy saving. Therefore, the underlying utility function form was as follows:

20 CL model & WTP The parameter estimates of the CL model can be converted into WTP for different non-price attributes. WTP for each attribute can be calculated by dividing the coefficient of attributes with the coefficient of the COST attribute.

21 Attributes Basic CL model and WTP estimation Coefficient St.err. p-values WTP St.err. p-values SUBS *** *** FITC *** *** SPACE *** *** SAVEK *** *** COSTK *** The statistically significant of all variables imply as a proof for the choice of the explanatory variables in this survey.

22 The CL model with interaction terms Choice Coefficient Standard Error Z Prob. z >Z* SUBSIDY *** FIT *** SPACE *** COST *** SAVE *** IRCITYD ** IINCHD ***

23 The CL model with interaction terms and the WTP estimation Attributes Coefficient St.err. p-values WTP St.err. p-values SUBS *** *** FIT *** *** SPACE *** *** SAVE *** *** COST *** IUCITYD IINCHD ** ** IHIGHD *** ***

24 Findings The parameters of SUBSIDY, FIT, and SAVING ENERGY were statistically significant with a small standard error. This suggests that all explanatory variables play important roles in households decisions for the choice and procurement of micro-generation solar equipment on their premises. The WTP results showed that people were willing to pay 2.7 Euro more for each 1% of the increase in subsidy. were willing to pay 0.13 Euro more for each 10 cent Euro FIT. were willing to pay 2,700 for each extra 1000 saving annually.

25 Findings Education was found to be a crucial factor in Turkish Cypriot decisions and choices. The interaction between the variables of higher level of income with subsidy reveals that as the level of income increases, households showed a higher consent and WTP for a lower subsidy. The WTP of people with higher level of income was found to be 0.55 Euro more than people with the lower income for each one per cent of increase in subsidy. In addition, educated people were WTP 93 cent Euro more than lower or non-degree people for each 10 cent Euro FIT.

26 Conclusions The study helped the government to adopt a new policy. I. A higher support from respondents for covering the capital costs of micro-generation solar technology. II. A lower level of tariff was accepted by respondents. In 2014, government placed NET Metering system based on this study result.. The percentage of PV installation has increased by 15% in 2014 compared with the previous year.

27 Further study To account for taste heterogeneity and avoid the restrictive IIA assumption. Mixed logit model or random parameter logit analysis (RPL) allows for heterogeneity in preferences between households. RPL allows the parameter associated with each observed variable (e.g., its coefficient) vary randomly across customers.

28 Further study Installation of PV during construction has been studied: A framework for evaluating WTP for BIPV in residential housing design in developing countries A further study needs to be done in the case of apartment buildings, as the land availability is getting limited in Cyprus.

29 References Bergmann, A., Colombo, S., Hanley, N. (2008) 'Rural versus urban preferences for renewable energy developments', Ecological Economics, 65, pp Carson, T. R., Louviere, J. J., Anderson, D. A., Arabie, P., Bunch, D. S., Hensher, D. A., Johnson, R. M., Kuhfeld, W. F., Steinberg, D., Swait, J., Timmermans, H. and Wiley, J. B. (1994) 'Experimental Analysis of Choice', MKTG Letters 5, (4), Ferrini, S. and Scarpa, R. (2007) 'Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study', Journal of Environmental Economics and Management, 53(3), pp Haab, T.C. and McConnell, K.E. (2003) Valuing Environmental and Natural Resources, The Econometrics of Non- market Valuation. Cheltenham,UK: Edward Elgar. Hensher, D.A., Rose, J.M. and Greene, W.H. (2005) Applied Choice Analysis, A primer. UK: Cambridge University Press. Holmes, T. P., & Adamowicz, W. L. (2003). Attribute-based methods. In A primer on nonmarket valuation (pp ). Springer Netherlands. McFadden, D. (1974) 'Conditional logit analysis of qualitative choice behavior', in Zarmbka, P. (ed.) Frontier in econometrics, Newyork: Academic press, pp Scarpa, R., Ferrini, S. and Willis, K. (2005) 'Performance of Error Component Models for Status-Quo Effects in Choice Experiments.', in Scarpa, R. and Alberini, A. (eds.) Applications of Simulation Methods in Environmental and Resource Economics. The Economics of Non-Market Goods and Resources,. Dordrecht,The Netherlands: Springer, pp Scarpa, R. and Rose, J.M. (2008) 'Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why', Australian Journal of Agricultural & Resource Economics, 52(3), pp Breffle, W.S. and Rowe, R.D. (2002) 'Comparing Choice Question Formats for Evaluating Natural Resource Tradeoffs', Land Economics, 78(2), pp