Sustainable and renewable implementation multi-criteria energy model (SRIME)—case study: Sri Lanka

0 F. M. Mart n Termodina mica, Escuela Te cnica Superior de Ingenieros de Montes, Universidad Polite cnica de Madrid , Madrid , Spain 1 L. C. Dom nguez-Dafauce (&) Escuela Polite cnica, Universidad Europea de Madrid , Madrid , Spain 2 Luis Carlos Dom nguez-Dafauce Sustainable and renewable are certainly very appreciated terms nowadays. These words may summarize a whole new attitude towards our world and the people who live in it. This paper's goal is to define an original multicriteria energy model, named SRIME, specially designed for developing countries. First, an extensive research will be carried out on: energy demand; potential renewable energy, its current know-how and potential future development; potential avoided emissions (CO2, NOX, SO2); and the possible international support versus the in-country possibilities. The precedence constraints will be applied to establish in which degree renewable energy may be substituting for the fossil fuel: the purely economic approach will give way to a sustainable, renewable, development focused energy planning. It must be noted that an innovative function has been specifically included in the SRIME, which evaluates, applying the precedence constraints, the influence renewable energy may have on developing countries rural health and education. Six functions have been established: replaceable amount of fossil energy; CO2, NOX and SO2 avoidable emissions; rural health and education development maximization; and the cost function. These functions will be optimized through the Chebyshev distance (L?) compromise programming minimization, so that the Pareto optimal solution may be obtained. - Abbreviations AC Alternating current BT Biomass thermal BEG Biomass electricity generation GDP Gross domestic product GOSL Government of Sri Lanka HH Household HMDP High materially developed countries IAEA International Atomic Energy Agency LEC Levelized energy cost Lk k-dimensional distance LMDC Low materially developed countries LPC Linear programming computation LRY Real GDP per capita MCDM Multi-criteria decision making MDG Millennium development goals MMTCDE Million metric tons of carbon dioxide equivalents MSW Municipal solid waste NCRE Non-conventional renewable energy PH Pico hydro PUCSL Public Utilities Commission of Sri Lanka PV Photovoltaic system RE Renewable energy SH Small hydro SHS Solar home systems SL Sri Lanka SLSEA Sri Lanka Sustainable Energy Authority SRIME Sustainable and renewable implementation multi-criteria energy UN United Nations Wind power Wind power plant The MCDM has been used over the years [1, 2], and is indeed a currently widely used tool for energy applications [36]. The aim of this paper is to focus on a set of sustainable and renewable factors that will be assessed through a precedence constraints evaluation. The optimal solution will be then chosen among the possible solutions for every one of the six equations, applying the Linear Programming Computation (LPC). The best compromised solution is then found among the Pareto optimal solutions [7], which will allow rejection of the solutions corresponding to any of the six optimizing equations that are found to be situated furthest from the rest of the optimal values obtained for the remaining equations. This way the dominating solutions will be softened, letting energy planners base their decisions on a solution that can not be improved without making at least one of the variables worse off. This methods greatest challenge is how investigators and then planners will decide to calculate the weights to be applied to every one of the six equations. This decision will require a broad consensus among a wide range of experts so that decisions are not postponed, generating conflict, wasting time and, therefore, damaging future programming. The subjective part of the compromise programming is also a demanding issue, which has to be carefully and professionally performed. The value given to the different subjects must be thoroughly assessed, avoiding a personal opinionated view from the experts. SRIME model Figure 1 shows the steps that are proposed in this model, which has been specifically designed for low materially developed countries. The first stage is to carry out a thorough evaluation of the current energy demand, and subsequent future needs. Secondly, the possible renewable solutions will be assessed, taking into account the incountry possibilities, along with the international support, aiming to enunciate the first function, using the precedence constraints.1 The third step will be to study the potentially avoidable emissions so that the corresponding three 1 The authors are aware of the fact that there are many other optimization methods, like the cascade optimization or the ideal point discriminant analysis [1], and have indeed checked the obtained results using some of the mentioned methods, obtaining similar results. functions may be stated (F2, F3, F4). Then the fifth function will come from a deep study of the possible interactions between health and education and renewable energy, according to the parameters described by the UN and other international organizations. The last phase is to enunciate the cost function (F6). The Lk distances will then be minimized, according to the chosen weights, so that a compromised solution may be selected among the several obtained by the preferred optimization tool.2 Maximization of RE potential capacity: F1 The so-called green economy focuses on the various advantages our world shall enjoy if we were to go green [8 11]. Not only climate change is involved here but also the potential enhancement of the overall development factors, especially the health co-benefits. You may find the corresponding equation and Table 1 below, which includes a summary of the potential precedence constraints the authors have chosen to be applied [1214].3 F1 x11; x12; . . .; xij; . . .; xnm A11x11 A12x12 Environmental impact minimization: F2, F3, F4 Environmental impact has ben a major concern in the world for the past ten years. Local researchers are indeed looking into potential present and future sustainable possibilities [15, 16]. These are the three corresponding functions: F2 x11; x12; . . .; xij; . . .; xnm B11x11 B12x12 F3 x11; x12; . . .; xij; . . .; xnm C11x11 C12x12 F4 x11; x12; . . .; xij; . . .; xnm D11x11 D12x12 Dnmxnm Bij/Cij/Dij: life cycle CO2/NOx/SO2 avoided emissions (ton/energy unit) For all Bij C 0; Cij C 0; Dij C 0 ) max F2; F3; F4 optimal avoided emissions maximization 2 Please note subscript i denotes every RE type, and j denotes the different sectors; i.e., xij denotes the amount of fossil fuel (ktoe) replaced by RE i in sector j. 3 Coefficients A are non-dimensional and obtained through prece dence constraints, where no energy or cost quantification is involved. These precedence constraints are based on the factors showed below in Table 1. Fig. 1 SRIME energy model. Own constru (...truncated)