*Article* **An AHP-SWOT-Fuzzy TOPSIS Approach for Achieving a Cross-Border RES Cooperation**

#### **Aikaterini Papapostolou, Charikleia Karakosta \*, Georgios Apostolidis and Haris Doukas**

Energy Policy Unit (EPU-NTUA), Decision Support Systems Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece; kpapap@epu.ntua.gr (A.P.); george\_apo\_8@hotmail.com (G.A.); h\_doukas@epu.ntua.gr (H.D.) **\*** Correspondence: chkara@epu.ntua.gr; Tel.: +30-210-772-2083

Received: 28 January 2020; Accepted: 2 April 2020; Published: 4 April 2020

**Abstract:** The emerging need to tackle climate change and mitigate greenhouse gas emissions has led to the consolidation of interest in renewable energy sources (RES) setting specific targets in the European area. To achieve the ambitious targets set, Member States are given the opportunity to cooperate with one or more of their developing neighboring countries. The aim of this paper is to develop a methodological framework based on the combination of the Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis with the Analytic Hierarchy Process (AHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) methods for adopting the most appropriate strategic plan, in order to establish a successful energy cooperation that will create beneficial conditions for all the involved parties. The results could be important in facilitating decision makers to assess the role and design of this cooperation mechanism. Key insights will also emerge with regards to opportunities for energy strategy cooperation between Europe and its neighboring countries.

**Keywords:** renewable energy sources; energy policy; SWOT analysis; multi-criteria analysis; AHP; fuzzy TOPSIS; Morocco; Egypt

#### **1. Introduction**

#### *1.1. Background and Motivation*

Nowadays, there is plenty of scientific evidence to prove that climate is changing due to the increasing quantities of greenhouse gas (GHG) emissions, for which human activity is mainly responsible [1]. It is also a fact that as the years go by, global energy demand is rising dramatically, which is the main cause of the bulk of these emissions, as more and more fossil fuels are burnt in order to meet those demands. In order to tackle climate change, the European Commission (EC) has already adopted a series of measures to facilitate the clean energy transition in its energy sector in the future. Recently, the EC Clean Energy for all Europeans package entered into force including policies and legislation regarding renewable energy sources (RES), energy efficiency and GHG emissions reduction, while the recast Renewable Energy Directive (RED) [2,3] envisages an ambitious, binding target of 32% for RES in the European Union (EU) energy mix by 2030.

It is worth mentioning also that the international regulatory framework, as well as the international initiatives, call for increased cooperation, as a crucial factor to fully exploit the vast RES potential worldwide. This will constitute a win-win situation as it will allow us to meet climate change objectives in a cost-effective way and enable countries to develop their economies in a more sustainable way. In addition, it will allow the development of a competitive industry in the field of low-carbon technologies [4].

To meet the ambitious energy targets set, Member States are given the opportunity to cooperate with one or more of the neighboring countries towards this direction. More specifically, one or more Member States may cooperate with one or more developing neighboring countries on joint projects within the territory of the latter, with regard to electricity generation from RES. Any amount of electricity generated by such installations may be taken into account for the purposes of measuring compliance with the Member States' national overall targets, if certain demanding conditions are met.

As Karakosta et al. (2013) [5] noted and compared to the other cooperation mechanisms envisaged by the EU legislation, barriers to the implementation of the cooperation mechanism on joint projects between EU and developing countries include poor grid infrastructure (in order for the energy to be transferred into the community), geopolitical unrest, risks of limited public acceptance, existing legal limitations and complex financing schemes.

However, and despite the potential difficulties that lie in the implementation of the mechanism, especially considering that any such project should be able to attract private funding, there are major benefits as well [6]. In addition, joint projects with developing countries, although quite complex considering the involved parties, different country contexts, regulations, infrastructures etc., could be a crucial instrument striving towards international RES cooperation to foster the social, economic and environmental benefits of RES electricity (RES-E) projects.

## *1.2. Contributions*

The core objective of this paper is to assess, through case studies and integrated analysis to what extent cooperation with developing neighboring countries can help Europe achieve its RES targets and beyond this, trigger the deployment of RES-E projects in the host countries and create synergies and mutually beneficial circumstances for all involved parties [7]. In order to support the development of cooperation mechanisms and implement a successful collaboration, the current and future situation of the host country need to be examined, so as to be able to develop the most appropriate energy policies [8]. This could be achieved through the analysis of Strengths, Weaknesses, Opportunities and Threats (SWOT) of the country under examination.

SWOT analysis is used in order to assess a host country's present situation as conducive to implement RES projects under the cross-border cooperation framework. The aim is to identify factors that are favorable (Strengths, Opportunities) and unfavorable (Weaknesses, Threats) to the development of this cross-border cooperation. The SWOT analysis intents to identify win-win actions for both EU Member States and neighboring countries by providing answers to the following questions [9]:


However, SWOT analysis cannot be considered as a sufficient stand-alone tool to solve this energy planning problem. The complex nature of this process requires the use of multi-criteria decision making (MCDM) methods, which seem to be extremely powerful tools and able to deal with the different aspects that these problems include [8,10,11]. MCDM methods have been applied to many energy-related problems, such as energy planning and selection, energy resource allocation, energy policy, management of building energy, transportation systems, and electric utility planning [6,12–15]. Such problems have been discussed either from the perspective of a single criterion decision problem, such as maximizing profit or minimizing cost, or in relation to complex multi-criteria decision problems [16]. According to Wang et al. 2009 [17], the most frequently used criteria are investment cost, CO2 emissions, efficiency, operation and maintenance cost, land use, fuel cost, and job creation.

For this study, Analytic Hierarchy Process (AHP) is utilized in order to determine the weights of the criteria that will be then used to assess the alternative proposed strategies to be followed towards a successful implementation of cooperation mechanisms. After the criteria weights calculation, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) method is used, in order to rank the proposed strategies that emerge towards the promotion of cross border cooperation, since it is widely used to solve decision making problems.

In the current study, the perspectives of a cross-border energy cooperation between the EU and Morocco, which was selected as a potential host country, are examined. The reason why this country was selected has to do with the fact that the development of such a cooperation seems extremely feasible. First of all, Morocco is Spain's southern border and only a relatively narrow body of water separates the two countries. This is a favorable factor for this direction, considering that this kind of cooperation requires electrical interconnection between the countries. It is also worth mentioning that Morocco is the only North African country that has an interconnection with a European country. More specifically, a submarine cable connecting the country with Spain already exists, which is both important for importing energy and also for potential energy exports in the following years. Moreover, the country has strong potential in developing RES, while an upward trend in the energy demand in the past several years can be observed [18].

Finally, the results of the pilot application in Morocco were compared with the results of an additional case study. This paper also provides a comparative analysis between Morocco and Egypt, so as to obtain a clearer picture of the pros and cons of the applied methodology.

#### *1.3. Decision Support Methods Review*

#### 1.3.1. SWOTAnalysis

SWOT analysis is a well-known analytical tool, which has been widely applied for strategic decision-making processes [19], in regional energy planning and management [20,21], as well as in renewable energy schemes [22,23]. In particular, SWOT analysis has been used so far in order to investigate and assess the current status of RES in different regions [23,24] yielding a good basis for formulating policy recommendations regarding enhanced utilization of RES. The use of SWOT analysis for exploring energy sector conditions and developing an environmental strategic plan could enable a correct comprehension of the current energy situation and serve as a basis for objectives and strategy proposals [25]. Lei et al. 2019 [26] exploit through the SWOT analysis a new opportunity for African countries to develop their solar power resource through mutually beneficial cooperation between Africa and China within the framework of the Belt and Road Initiative (BRI). Agyekum et al. 2020 [27] used the SWOT analysis to assess Ghana's nuclear power program. The research found out that in Ghana there are a lot of strengths and opportunities in investing in nuclear. However, issues such as a porous security system, corruption, porous borders and policy discontinuity are threats to the smooth implementation and operation of a nuclear power plant.

Kamran et al. 2020 [28] performed a SWOT analysis as a reference point that diagnoses the feasibility of current status and future roadmap to nurture the renewable energy sector in Pakistan. Igli ´nski et al. 2016 [29] examined the history, current state and prospects for the development of the wind power sector in Poland including a SWOT analysis of wind power investment. Studies also exist in the literature that combine the SWOT analysis with MCDM methods. Ervural et al. 2018 [30] used a combined Analytic Network Process (ANP) and fuzzy TOPSIS method with SWOT analysis in order to evaluate Turkey's energy planning strategies. The results showed that the most important priority was to turn the country into an energy terminal by effectively using the geo-strategic position within the framework of the regional cooperation. Wang et al. 2020 [31] integrated the fuzzy AHP and SWOT model for choosing and assessing the strategic renewable energy technologies in Pakistan by considering four indicators and 17 sub-indicators. The finding of that study demonstrated that socio-political and economic criteria were the influential indicators for the selection of renewable

energy sources. Khan 2018 [32] evaluated the prioritized the strategies for stimulating the growth of the Iranian Compressed Natural Gas (CNG) market through the application of SWOT analysis along with a modified Fuzzy Goal Programming. Finally, Solangi et al. 2019 [33] evaluated strategies for sustainable energy planning in Pakistan through an integrated SWOT-AHP and Fuzzy-TOPSIS approach. The results of the study reveal that providing low-cost and sustainable electricity to residential, commercial, and industrial sectors is a highly prioritized energy strategy.

#### 1.3.2. AHP

The AHP framework is a popular tool for formulating and analyzing decisions, which is extremely useful for ranking alternatives, as well as calculating the weights of different criteria through pairwise comparisons [34]. AHP establishes a balance between quantitative and qualitative factors, as it makes it possible to incorporate judgments on intangible qualitative criteria alongside tangible quantitative criteria [35]. The AHP method is based on three basic rules/factors: first, structure of the model; second, comparative judgment of the alternatives and the criteria; third, synthesis of the priorities. Based on the above, it is clear that AHP has two main advantages: mathematical simplicity and flexibility. These two are probably the reasons why AHP is a favorite research tool in many fields, including energy management and renewable energy sources.

Available literature is abundant with examples of AHP method application in various fields, including environment and energy management [36]. Ghimire et al. 2018 [37] identified and ranked through AHP, the barriers to developing renewable energy in Nepal. Twenty-two barriers were identified and categorized into six types of barriers: social, policy and political, technical, economic, administrative, and geographic. Political instability and transportation problems are ranked first and second in overall barriers. In the same year, Ozdemir and Sahin et al. 2018 [38] examined three different locations in Turkey to find the best place for setting up a solar photovoltaic power plant through AHP, which was used to evaluate locations taking into consideration both quantitative and qualitative factors which play an effective role on the electricity production. Recently, Colak et al. 2020 [39] explored the optimal site selection for solar photovoltaic power plants using Geographic Information System (GIS) and AHP having as a case study the Malatya Province in Turkey. Keleey et al. 2018 [40] highlighted the importance of foreign direct investment (FDI) for the development of renewable energy in developing countries by using the AHP method to clarify the relative significance of the determinants in the location decisions of foreign wind and solar energy investors. Finally, Wu et al. (2019) [41] introduced a new approach using the AHP model under an interval type-2 fuzzy weighted averaging set to evaluate the performance of renewable energy projects based on the sustainability view. The results of that proposed method found that the GHG emission reduction had the best rank among other criteria.

#### 1.3.3. FuzzyTOPSIS

Fuzzy multi-criteria methods constitute one approach to evaluate alternative decisions, which involve subjective judgments and are made by a group of experts. A pairwise comparison process is used to assist decision makers to make comparative judgments, while absolute judgments are made using a linguistic evaluation method [42].

TOPSIS is one of the known classical and most popular MCDM methods that was developed by Hwang and Yoon in 1981 [43]. TOPSIS is a widely accepted multi-attribute decision-making technique owing to its simultaneous consideration of the ideal and the anti-ideal solutions, and easily programmable computation procedure. Its basic principle has to do with the fact that the chosen alternative should have the shortest distance from the positive ideal solution (PIS) and the farthest from the negative ideal solution (NIS), compared to the others. Having to use crisp values is one of the weak points in the crisp evaluation process. TOPSIS method is not able to deal with decision-makers' ambiguities and uncertainties which cannot be handled by crisp values. The use of fuzzy set theory offers the decision makers the opportunity to incorporate unquantifiable information, incomplete information; non-obtainable information and partially ignorant facts into a decision model [44].

Consequently, fuzzy TOPSIS and its extensions are developed to solve ranking and justification problems [10,42]. It meets specific requirements when uncertain and imprecise knowledge, as well as possibly vague preferences must be considered [45]. This method allows the fuzzy values to be used in the decision problem as it offers a realistic approach by using linguistic assessments instead of numerical values [46,47]. Fuzzy TOPSIS method has been applied in various fields, which shows an excellent performance in the decision making of alternatives selection [48–50].

Moreover, as far as assessments in the field of energy policy are concerned, fuzzy TOPSIS has been applied in many different studies [51]. It has been also used to evaluate the viability of renewable energy projects [15]. Papapostolou et al. 2017 [10] presented a new extension of fuzzy TOPSIS method for prioritization of alternative energy policy scenarios to realize targets of renewable energy in 2030. Rani et al. 2020 [52] ranked and chose the renewable energy sources in MCDM problems based on fuzzy TOPSIS. Çolak and Kaya (2017) [53] developed a new model in order to evaluate renewable energy alternatives with the use of AHP and TOPSIS methods under interval type-2 fuzzy. According to the findings the wind energy was the best source among the available renewable energy sources. Karunathilake et al. (2019) [54] used a combination of the fuzzy TOPSIS method and life cycle thinking to select and assess different renewable energy sources. Ligus and Peternek, 2018 [55] proposed a hybrid MCDM model based on fuzzy AHP and fuzzy TOPSIS in order prioritize low-emission energy technologies development in Poland through criteria relevant to the sustainable development policy goals in Poland. The research results show that renewable energy technologies should be utilized instead of nuclear energy.

#### *1.4. Manuscript Organisation*

Apart from this introductory section, the rest of the paper is organized as follows. Section 2 gives an overview of the method followed for the assessment of a potential transnational cooperation in the field of RES, as well as the methodological steps of the SWOT-AHP-fuzzy TOPSIS.

Section 3 includes the application of the proposed model for the country of Morocco, as well as a comparison of the obtained results with the respective results obtained from the application in Egypt.

Section 4 includes the discussion of the results and in Section 5, the main conclusions of the paper are summarized and key points for further research are proposed.

#### **2. Materials and Methods**

#### *2.1. Overview of the Proposed Methodology*

The establishment of a successful energy cooperation with the host countries, requires the assessment of the host countries current situation, so as Europe to define the appropriate strategic plan towards this direction [7].

Consequently, there is a need to assess, through case studies analysis, the role and design of this cooperation mechanism with regards to:


The following figure (Figure 1) illustrates the methodology applied in order to draw the necessary conclusions considering the effectiveness of the implementation of a cross border cooperation between the EU and developing countries.

**Figure 1.** Proposed methodology for addressing the problem.

Firstly, the areas to be evaluated, in order to study the extent to which the neighboring countries can participate in such an energy cooperation, were identified. Then, taking these axes into account, 12 criteria were adopted, which refer to the above-mentioned axes and give a clear picture of the current situation in the country under consideration. After setting the criteria, an extensive study in the international literature and in online sources followed to gather information that characterize a host country in each of the criteria. This process was followed by the identification of the strengths, weaknesses, opportunities and threats existing in each of these 12 criteria and a SWOT analysis for the host country was completed. Finally, through Threats, Opportunities, Weaknesses and Strengths (TOWS) analysis, the four alternative strategies (SO, WO, ST, WT) were obtained [25,56,57]. The TOWS analysis has been widely used to define strategies based on a previously conducted SWOT analysis. Thus, according to the specific TOWS matrix, strategies can be developed, on the basis of the identified strengths, weaknesses, opportunities and threats [57]. More specifically the four alternative strategies are defined as:


Subsequently, after an extensive literature review, the most appropriate MCDM methods for the specific problem were selected. These MCDM methods were applied to assess and classify the alternative strategies from the most to the least preferable according to decision maker's preferences. Finally, after the strategies' classification, the most suitable strategy towards achieving a successful energy cross border cooperation was identified.
