Review

Exploiting wind-solar resource complementarity to reduce energy storage need

  • Received: 22 June 2020 Accepted: 14 August 2020 Published: 21 August 2020
  • Resource complementarity carries significant benefit to the power grid due to its smoothing effect on variable renewable resource output. In this paper, we analyse literature data to understand the role of wind-solar complementarity in future energy systems by evaluating its impact on variable renewable energy penetration, corresponding curtailment, energy storage requirement and system reliability. Results show that wind-solar complementarity significantly increases grid penetration compared to stand-alone wind/solar systems without the need of energy storage. However, as capacity increases, the capability of complementarity to increase grid penetration approaches its limit due to the reduced matching of output to the load profile and pursuant increase in excess generation. Thus, achieving very high penetration requires appropriately designed energy storage and curtailment. Yet, even at higher grid penetration, complementarity carries significant multidimensional benefits to the power system. The most important observation was the achievement of very high grid penetration at reduced energy storage and balancing requirements compared to stand-alone systems. Researchers reported that using the same energy storage capacity, wind-solar complementarity led to significantly higher penetration of up to 20% of annual demand compared to stand-alone systems. In addition, by coupling to curtailment as an enabler, and related dispatch flexibility that comes with storage application, lower balancing capacity need was reported at higher penetration. Wind-solar complementarity was also found to reduce ramping need while contributing to improved system adequacy. Complementarity from other dispatchable renewable resources further reduces storage need and curtailment and improve system reliability, whereas power grid integration and relative cost changes allow for further optimisation while transitioning to 100% renewable energy.

    Citation: Solomon A. A., Michel Child, Upeksha Caldera, Christian Breyer. Exploiting wind-solar resource complementarity to reduce energy storage need[J]. AIMS Energy, 2020, 8(5): 749-770. doi: 10.3934/energy.2020.5.749

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  • Resource complementarity carries significant benefit to the power grid due to its smoothing effect on variable renewable resource output. In this paper, we analyse literature data to understand the role of wind-solar complementarity in future energy systems by evaluating its impact on variable renewable energy penetration, corresponding curtailment, energy storage requirement and system reliability. Results show that wind-solar complementarity significantly increases grid penetration compared to stand-alone wind/solar systems without the need of energy storage. However, as capacity increases, the capability of complementarity to increase grid penetration approaches its limit due to the reduced matching of output to the load profile and pursuant increase in excess generation. Thus, achieving very high penetration requires appropriately designed energy storage and curtailment. Yet, even at higher grid penetration, complementarity carries significant multidimensional benefits to the power system. The most important observation was the achievement of very high grid penetration at reduced energy storage and balancing requirements compared to stand-alone systems. Researchers reported that using the same energy storage capacity, wind-solar complementarity led to significantly higher penetration of up to 20% of annual demand compared to stand-alone systems. In addition, by coupling to curtailment as an enabler, and related dispatch flexibility that comes with storage application, lower balancing capacity need was reported at higher penetration. Wind-solar complementarity was also found to reduce ramping need while contributing to improved system adequacy. Complementarity from other dispatchable renewable resources further reduces storage need and curtailment and improve system reliability, whereas power grid integration and relative cost changes allow for further optimisation while transitioning to 100% renewable energy.


    Abbreviations: ERP: Enterprise resource planning; AHP: Analytic hierarchy process

    It is well documented that ERP systems are beneficial to business operations (Ragowsky & Somers, 2002; Beatty & Williams, 2006); however, the implementation of ERP systems can be costly and time-consuming. Likewise, the software installation and system operating costs can be translated into a real financial burden for a company. The human resources and staffing are also expensive, and the training of staff for the complex system is tedious. Moreover, if any component of an ERP system is not implemented correctly or the technology is incompatible or inefficient for the business structure, the huge capital expenditure and human cost will become a receipt of disaster which may lead to the demise of some companies (Davenport, 1998; Martin, 1998; Parr & Shanks, 2000; Olson, et al. 2013). In practice, the implementation of ERP systems is overly complex, with a highly technical architecture and high operating cost; the enormous amount of time is spent on integrating the system to fit into the organization, and these factors are suggested to be the main reasons for a successful rate when implementing an ERP system (Davenport, 1998; Martin, 1998). Previous studies of ERP systems have focused on understanding the factors leading to either the success or failure of ERP implementation, and the aim is usually to assist those enterprises which currently have an ERP system in place or are planning to change to this system to achieve greater success and less failure (Bradley, 2008; Kim et al., 2005; Morteza & Zare, 2013; Olson & Staley, 2012; Sumner, 2006). Even after spending millions of dollars on investing in ERP systems, some companies are still facing ongoing challenges (Parr & Shanks, 2000; Olson et al., 2013). Olson and Zhao (2007) pointed out that 70% of the companies had failed to achieve the objectives after implementing ERP. Moreover, the implementation of ERP involves different phases, and each phase embeds the crucial factors affecting the ERP implementation success and failure. These crucial factors include top management support, consultant experience, vendor capacity, staff feedback and evaluation, organizational process and reengineering, etc; and, beyond all of these factors, the managers' ability to control these issues is the key to the success of ERP implementation. Kwahk & Lee (2008) argued that, in fact, ERP systems were still experiencing higher failure rates, with approximately 60% to 90% of the companies failing to implement the ERP systems. While some companies understand the importance of those key success factors, they failed in the ground operation and execution (Basoglu et al., 2007; Kwahk & Lee, 2008).

    In a local context, Taiwanese businesses that have been successful in ERP implementation show some influential findings. For instance, the electronics industry has focused on, for example, information sharing, project organization and management (Cai, 1999); the organizational structure, project management, information technology and business management (Zhang, 2000); or organizational and personnel factors, and ERP software configuration (Dai, 2007). The traditional manufacturing sector has focused on an organization's internal environment, the ERP user and consultant support (Zhang et al., 2013). The telecommunication sector emphasizes the organizational structure, technology and external environment (Bai, 2007). The construction sector focuses on four key issues, including the internal environment, software vendor characteristics, system configuration and implementation outcomes (Huang, 2006). The review of these studies indicates that each industry will have its unique success factors in the ERP selection and implementation process. According to the white paper on small- and medium-sized enterprise research (2010), Taiwanese industries are classified into nine major sectors: garments, underwear, bags and suitcases, sweaters, towels, hosiery, swimwear, bedding and shoes. Each industry is further divided into small sub-sectors. For example, the garment industry has a wide range of sub-sectors, including upstream and downstream industries such as fiber manufacturing, spinning, weaving, dyeing, finishing, clothing and apparel. In a global supply chain, the garment exporting companies often experience an overwhelmingly high demand. The clothing specifications and requirements of fabrics, accessories, materials and styles are often complex and change from time to time; and, the clients demand just-in-time delivery and high-quality products. As such, the smooth and efficient operation of handling the complexity and competition existing in the garment industry will, to some extent, rely on an integrated and effective information system. However, the white paper on small- and medium-sized enterprise research (2019) reported that ERP implementation in the over 50 workers' businesses was roughly 80% in the manufacturing industry and 50% only in the service industry.

    This case study was based on R enterprise, which had the first ERP system installed in 2002; the full-scale implementation was launched after 2007. During 2013, the company adopted a growth strategy and expanded rapidly overseas, with the number of multinational operations and manufactories increasing every year. Whenever launching new ventures in different countries or experiencing expansion of the existing manufacturing plants in their home country, the company must operate under the so-called dual system, whereby the old system coexists during the period of transformation to the new ERP system. The challenges are immense during the transformation period because the work is doubled and the different management styles in multiple locations eventually cost its business. The ERP system modules currently in use have failed to meet the managerial requirements. The new system is not easy to customize, is difficult to operate and, at the same time, involves many other issues, such as incompatibility and difficulty in making the necessary adjustments and modifications. All of these issues need to be resolved when transforming from the old system to the new one; if these issues are not resolved, there is a risk of running a dual system in one organization, which would lead to much more ongoing complexity and complications. The general management office in the home country revises the ERP systems on a yearly (or monthly) basis, and the purpose is to effectively facilitate and integrate a fast-growing and independent financial system. However, the administration has not been able to provide a complete set of ERP system. This study aims to explore the key success factors for ERP system implementation in the garment industry through analysis of the case of R enterprise. The findings are expected to provide useful insight for the companies that are preparing a second implementation of ERP.

    This study involved applying a two-stage Delphi method and analytic hierarchy process (AHP; Saaty 2000) to conduct an exploratory analysis of ERP systems and examine how the professional and organizational issues have contributed to the success of ERP implementation.

    The starting point was a review of the literature; from the previous studies, the factors for successful ERP implementation were initially identified and, subsequently, these factors were proposed to construct the first-round Delphi questionnaire. Five experts/scholars were selected to participate in the 3-round Delphi interview. After interviewing the five experts/scholars, the factors that were recommended to be the key common issues that influence the success of ERP systems were then discussed, summarized and grouped to design the second-stage AHP questionnaire.

    First of all, the questionnaire design can be divided into the following five steps: 1. selecting experts; 2. collecting questions and sorting; 3. the first-round questionnaires 4. the second-round questionnaire; 5. forming general comments and consensus. If there is no consensus that can be researched by the experts/scholars, repeat Steps 3 and 4 to have consistent results.

    Step 1: Selecting experts. According to Linstone (1978), experts or scholars need to have a high level of familiarity in the field of ERP to be qualified to give any representative opinions in the interview. Therefore, this study utilized three industry experts who have more than five years' experience in ERP system implementation and two professors with relevant research and professional backgrounds in this area to form the interview panel, totaling five experts/scholars. The experts' background and experience are summarized in Table 1.

    Table 1.  Summary of experts' background in Delphi interview.
    Industry Working Experience Using ERP Experience
    Expert ID ERP System Experience (Y/N) 5–10 Years > 10 Years 5–10 Years > 10 Years
    Expert A Y Y Y
    Expert B Y Y Y
    Expert C Y Y Y
    Expert D Y Y Y
    Expert E Y Y Y

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    Step 2: ERP key successful factors collection and collation. The five experts and scholars reviewed the literature, both domestic and international studies, and identified initial key ERP success factors that include four aspects, 12 guidelines and 48 evaluation criteria, as shown in Table 2. These became the base questions used in the first-round questionnaire.

    Table 2.  Stage 1 Delphi method: Summary of key factors from expert questionnaires.
    Aspects Guidelines Evaluation Criteria
    Enterprise/ Organization resources (Ye and Chen, 2005) Enterprise environmental resources (Bradley, 2008), Organizational and process improvement (Olson and Zhao, 2007), Project planning and management (Vasilash, 1997). Top management support and commitment (Maskell, 1991), Budget support and sufficient economic resources (Shanley, 1997), Excellent information environment (West, 1998), Sufficient project resources and authorization (Wall and McKineey, 1998), Enablement of business process reengineering (Bingi et al., 1999), Clear project plan based on defined ERP capacity requirement, limited scope and focused flowchart (Laughlin, 1999), Transparency level of the overall information flow and documentation process (Huang and Lin, 2012), Standard operating procedures and institutional processes (Davenport, 1998), Ability to accelerate and shorten the operation cycle of the company (Wu and Huang, 2008), Feasible and effective project schedule (Parr and Shanks, 2000), Attention to problem-solving (Holland and Light, 1999), Establishment of the optimal cross-departmental task force (Wall and McKineey, 1998).
    System user (Zhang et al., 2013) Users' ability (Ye and Chen, 2005), Execution process (Liu, 2003), Staff awareness (Ling, 2010). Staff professional competence and the ability to coordinate the project (Zhang et al., 2013), Staff has ability to understand and use information (Ye and Chen, 2005), Users have basic information literacy (Shanley, 1997), Users' attitude and engagement in system implementation (Xie, 2001), Strong leadership from the project team (Parr and Shanks, 2000), Good interdepartmental communication and coordination on focused issue solution (Vasilash, 1997), Ability to placate and eliminate employee resistance to new system (Shanley, 1997), Stable project team members (Nah, 2006), Staff acceptance and agreement (Lin, 2010), Staff attitude and resistance to change (Lin, 2010), Employee morale and commitment (Lin, 2010), Trust within the organization (Lin, 2010).
    ERP technique and vendor (Zhang et al., 2013) System design and integration capabilities (Oliver, 1999), System vendor's specialty (Bingi et al., 1999), Vendor's technical support (Lin, 1999). User-friendly interface (Wu and Huang, 2008), System is customizable and flexible enough to be modified (Wu and Huang, 2008), System incorporates an aggressive schedule and timeliness (Ye and Chen, 2005), System can effectively integrate different companies and regions and operate in different currency systems (Huang and Lin, 2012), Provide timely information for management decision-making (Wu and Huang, 2008), Manufacturer R & D capacity in new program development (Lin, 2010), Supplier can provide integrated software and can update the software when the company is continuing developing (Huang and Lin, 2012), Provide technical assistance for rapid, effective transfer of best practice interventions (Huang and Lin, 2012), Supplier can assist with the system implementation, testing, operation, maintenance and upgrade (Huang and Lin, 2012), Maintain good interaction with the company (Shanley, 1997), Assist the company to successfully install software and hardware (Guo, 1999), Supplier can work with the company to develop internal process and management software (Huang and Lin, 2012).
    Consultant service (Ye and Chen, 2005) Consultant service details (Liu, 2003), Consultant team specialty (Xu, 2000), Technique support (Huang and Lin, 2012). Consultancy fees charged level (Martin, 1998), Timely response to the company requirements (Liu, 2003), Assist the company staff in training and education and technology transfer (Bingi et al., 1999), Clear and effective implementation of quality assurance (Liu, 2003), Consultant can analyze the company's past, present and future operational capacity (Davenport, 1998), Consultant have a good understanding of the nature of business and competition (Ye and Chen, 2005), Consultant has high familiarity with ERP system modules and operating procedures (Martin, 1998), Consultant have a similar experience of successfully implementing the system (Oliver, 1999), Consultant can build in cost-benefit metrics and analytical tools (Wall and McKineey 1998), Level of control in the system implementation schedules (West, 1998), Consultant can work with the project team members and understand each other (Martin, 1998), Consultant can analyze the company's current HR and economic resource allocation (Martin, 1998).
    Source:based on the literature review conducted by authors.

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    Step 3: First-round questionnaire. Develop the questionnaire and distribute it to experts and scholars. All of the key ERP factors listed in Table 2 were used to design the Delphi questionnaire; it was sent to the experts and scholars who had been selected for the interview; then, phone calls were made to confirm the time for the first face-to-face meeting. During the first meeting, the interviewer typically spent about 2–3 hours to explain the tasks, and for each of the factors on the questionnaire, the experts and scholars had three options: they could choose either agree, delete or modify. If they chose the option of modify, there was an extra column where the experts and scholars needed to fill in details to support the modification. Apart from selecting based on the existing factors, the experts and scholars could also recommend other factors in the overall comments column in the questionnaire. After the questionnaire was completed, it was mailed back to begin data entry and collection work. Using descriptive statistics, these survey results will be presented in the form of frequency distribution tables.

    Step 4: Second-round questionnaire. We distributed the second questionnaire with added and deleted factors and/or new opinions. At the same time, we printed out the results from the first questionnaire, i.e., the frequency distribution table, and sent both the second questionnaire and the frequency distribution table generated from the first questionnaire to the experts and scholars. After reviewing the results from the first questionnaire, the experts and scholars filled out the second questionnaire to either maintain or modify their views. In the second questionnaire, the experts and scholars no longer needed to have a face-to-face interview, so the whole process was done by telephone. Once the questionnaire was completed, the experts and scholars needed to mail the documents back, and this was followed by data entry and collection work again.

    Step 5: Third-round questionnaire to determine key success factors. To avoid spending excessive time on the survey, we adopted an upper limit of a maximum of three times for the Delphi interview. The first two interviews were conducted in a traditional way of correspondence, and the third interview entailed an online meeting. As soon as the opinions were collected, the key factors were assessed and used to design the subsequent AHP questionnaire.

    To assess whether the framework (see Table 2) was sufficient and appropriate to contain the four aspects, 12 guidelines and 48 evaluation criteria, the first-stage Delphi method was applied and the questionnaires were distributed to the experts. The survey was conducted through two traditional face-to-face interviews and one online conference. The interviewer collected the questionnaires from the five selected experts and scholars for the three occasions, and, through the review of the experts' responses, as well as suggestions to those open questions, the framework and its layout were further revised. The results show that the experts reached a consensus on the following amendments: deleting 14 criteria and revising three criteria in the Tier 3 evaluation criteria for the aspect 'ERP technique and vendor'; adding two new factors, namely, 'system implementation is in alignment with company's strategic visions'; 'the professional level in the field of work and familiarity with the process', 'education and training of the project members and users', 'provision of good after-sales service and technical support', 'a good understanding of company's visions and strategies' and 'good communication and coordination skills'. Finally, we designed the AHP questionnaire based on the results generated from the first-stage Delphi expert questionnaires. The Delphi results were screened and used to form the key ERP successful factors in the AHP questionnaire (see Table 3, Tiers 1 to 3), which was distributed mainly to the top executives in the case company.

    Table 3.  Summary of top managers' backgrounds from AHP interview.
    Top Manager ID Working Experience Education Level
    < 5 Years 5–10 Years 10–15 Years > 15 Years
    Manager A Y Master Degree
    Managers B–G Y 1 Master Degree & 5 Bachelor Degrees
    Managers H–I Y 2 Bachelor Degrees
    Manager J Y Bachelor Degree

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    The main participants in the AHP questionnaire were the top decision-makers who had executive power in determining the fate of the project for the case company, and they were interviewed to enhance the accuracy of the AHP test. The top managers' backgrounds and experience were summarized in Table 3. The questionnaires were then collected and the weights were calculated for the case company's key ERP success factors. The AHP questionnaire framework is shown in Table 4.

    Table 4.  Framework established from AHP questionnaire.
    Tier 0 Tier 1 Tier 2 Tier 3
    Objective A Aspect B Guideline C Evaluation Criteria D
    ERP Key Success Factors Enterprise/ organization resources
    B1
    Enterprise environmental resources
    C1
    Top management support and commitment D1
    Budget support and sufficient economic resources D2
    Excellent information environment D3
    Organizational and process improvement
    C2
    Enablement of business process reengineering D 4
    Standard operating procedures and institutional processes D5
    Clear project plan by defined ERP capacity requirement, limited scope and focused flowchart D6
    Project planning and management
    C3
    Goal congruence between ERP project implementation and corporate strategy D7
    Feasible and effective project schedule D8
    Attention to problem-solving D9
    System user
    B2
    Employee competence
    C4
    Professional competence and the familiarity with the project D10
    Staff professional competence and the ability to coordinate the project D11
    Staff has ability to understand and use information D12
    Execution process
    C5
    Strong leadership from the project team D13
    Good interdepartmental communication and coordination on focused issue solution D14
    Education and training to project team members and users D15
    Staff awareness
    C6
    Staff acceptance and agreement D16
    Staff attitude and resistance to change D17
    Employee morale and commitment D18
    ERP technique and vendor
    B3
    System design and integration capabilities
    C7
    User-friendly interface D 19
    Customizability and flexible for modification D20
    Systems integrated with an aggressive schedule and timeliness D21
    System vendor's specialty
    C8
    Manufacturer R & D capacity in new program development D22
    Supplier can provide integrated software and can update the software to facilitate the company's growth D23
    Provide technical assistance for rapid, effective transfer of best practice interventions D24
    Vendor's technical support
    C9
    Supplier can assist with the system implementation, testing, operation, maintenance and upgrade D25
    Good customer service after-sales and technical support D26
    Maintain good interaction with the company D27
    Consultant service
    B4
    Consultant service details
    C10
    Consultancy fees D28
    Timely response to the company requirements D29
    Assist the company staff in training and education and technology transfer D30
    Consultant team specialty
    C11
    Consultants have a similar experience of successfully implementing the system D31
    Consultants have a good understanding of the company's goals and strategies D32
    Consultant has high familiarity with ERP system modules and operating procedures D33
    Consultant technique support
    C12
    Good communication and coordination skills D34
    Consultant can build in cost-benefit metrics and analytical tools D 35
    Level of control in the system implementation schedules D36
    Source:based on the analysis conducted in this study.

     | Show Table
    DownLoad: CSV

    The AHP survey targeted senior executives and entailed issuing 10 questionnaires using a nine-point scale. After the compilation and analysis of the data, there was no incomplete questionnaire or inconsistent information provided in the questionnaires; hence, the effective recovery rate was 100%. Based on the AHP questionnaire framework (Table 4), we analyzed the key factors that were suggested to affect ERP system implementation, as well as analyzed and compared every two elements in Tier 1 (Tier 2 and Tier 3) to reveal the relative importance of the key success factors.

    To ensure a high confidence interval for the respondents to have a consistent view on the importance level of key factors, a consistency ratio was used to assess the degree of consistency at each tier. The analysis of the consistency ratio shows that the overall aspects in the first tier, four guidelines in the second tier and 12 evaluation criteria in third tier all had consistency ratios less than 0.1, indicating a high level of consistency between the different tiers (Table 5).

    Table 5.  Analysis of ERP key success factor weights for case study company.
    Aspects Tier Weight Guidelines Tier Weight Accumulated Weight Accumulated Ranking Evaluation Criteria Tier Weight Accumulated Weight Overall Ranking
    Enterprise/ Organization resources 0.569 Enterprise environmental resources 0.229 0.130 4 Top management support and commitment 0.658 0.086 3
    Budget support and sufficient economic resources 0.220 0.029 14
    Excellent information environment 0.122 0.016 21
    Organizational and process improvement 0.454 0.258 1 Enablement of business process reengineering 0.156 0.040 9
    Standard operating procedures and institutional processes 0.304 0.079 4
    Clear project plan based on defined ERP capacity requirement, limited scope and focused flowchart 0.540 0.140 1
    Project planning and management 0.317 0.180 2 Goal congruence between ERP project implementation and corporate strategy 0.662 0.119 2
    Feasible and effective project schedule 0.174 0.031 11
    Attention to problem-solving 0.164 0.030 13
    System user 0.202 Employee competence 0.131 0.027 10 Professional competence and the familiarity with the project 0.451 0.012 26
    Staff professional competence and the ability to coordinate the project 0.398 0.011 27
    Staff has ability to understand and use information 0.151 0.004 32
    Execution process 0.546 0.110 5 Strong leadership from the project team 0.361 0.040 10
    Good interdepartmental communication and coordination on focused issue solution 0.490 0.054 8
    Education and training for project team members and users 0.149 0.016 20
    Staff awareness 0.323 0.065 7 Staff acceptance and agreement 0.365 0.024 17
    Staff attitude and resistance to change 0.404 0.026 16
    Employee morale and commitment 0.230 0.015 24
    ERP technique and vendor 0.154 System design and integration capabilities 0.545 0.164 3 User-friendly interface 0.445 0.073 5
    Customizability and flexible for modification 0.190 0.031 12
    Systems integrated with aggressive schedule and timeliness 0.365 0.060 6
    System vendor's specialty 0.300 0.090 6 Manufacturer R & D capacity in new program development 0.176 0.016 22
    Supplier can provide integrated software and can update the software to facilitate the company's growth 0.221 0.020 19
    Provide technical assistance for rapid, effective transfer of best practice interventions 0.603 0.054 7
    Vendor's technical support 0.155 0.047 9 Supplier can assist with the system implementation, testing, operation, maintenance and upgrade 0.602 0.028 15
    Good customer service after-sales and technical support 0.208 0.010 28
    Maintain good interaction with the company 0.189 0.009 29
    Consultant service 0.075 Consultant service details 0.159 0.012 11 Consultancy fees 0.151 0.002 36
    Timely response to the company requirements 0.628 0.007 30
    Assist the company staff in training and education and technology transfer 0.221 0.003 34
    Consultant team specialty 0.697 0.052 8 Consultants have a similar experience of successfully implementing the system 0.458 0.024 18
    Consultants have a good understanding of the company's goals and strategies 0.298 0.015 23
    Consultants have high familiarity with ERP system modules and operating procedures 0.245 0.013 25
    Consultant technique support 0.145 0.011 12 Good communication and coordination skills 0.482 0.005 31
    Consultants can build in cost-benefit metrics and analytical tools 0.190 0.002 35
    Level of control in the system implementation schedules 0.327 0.004 33
    Source: based on the analysis conducted by this study.

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    The factor weight is also known as the local priority, which indicates the relative weight of each factor for each tier. The overall weight is known as the global priority, calculated as the weight of the prior tier multiplied by the relative weight of various elements of the current tier; it shows the relative importance of various elements of the current tier as compared to the overall weight. For example, in this case study, it is as follows: Overall Weight = Weight of Tier 1 × Weight of Tier 2 × Weight of Tier 3. As a result, the overall weight was derived for the four major aspects, 12 guidelines and 36 key evaluation criteria (see Table 5), showing the rank as per the order of importance.

    This study also graphically explains the key aspects, guidelines and evaluation criteria based on Table 6. The y axis represents the rank of aspects (Figure 1), guidelines (Figure 2) and evaluation criteria (Figure 3) for Tier 1, Tier 2 and Tier 3 in the AHP framework; the x axis shows the weight for each element. Using Microsoft Excel to analyze the weights of the overall factors, Figure 1 was constructed to show that 'Enterprise/ Organization resources' was ranked first, followed by 'System user', 'ERP technique and vendor' and, the last, 'Consultant service'.

    Table 6.  Analysis of AHP consistency ratio.
    Factors by Tier Consistency Ratio
    (Tier 1) Overall factors 0.0192
    (Tier 2) Enterprise/ Organization resources 0.0009
    (Tier 2) System user 0.0001
    (Tier 2) ERP technique and vendor 0.0025
    (Tier 2) Consultant service 0.0019
    (Tier 3) Enterprise environmental resources 0.0045
    (Tier 3) Organizational and process improvement 0.0005
    (Tier 3) Project planning and management 0.0024
    (Tier 3) Employee competence 0.0001
    (Tier 3) Execution process 0.0008
    (Tier 3) Staff awareness 0.0001
    (Tier 3) System design and integration capabilities 0.0002
    (Tier 3) System vendor's specialty 0.0011
    (Tier 3) Vendor's technical support 0.0001
    (Tier 3) Consultant service details 0.0001
    (Tier 3) Consultant team specialty 0.0004
    (Tier 3) Consultant technique support 0.0023

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    Figure 1.  Case company ERP key success factors by aspects.
    Figure 2.  Case company ERP key success factors sorted by 12 guidelines.
    Figure 3.  ERP key success factors sorted by evaluation criteria.

    Figure 2 shows that case company R focuses on comparing the top three or six guidelines in the AHP questionnaire. The top three guidelines and the corresponding accumulated weights were 'Organizational and process improvement' (0.258255937), 'Project planning and management' (0.18042832) and 'System design and integration capabilities' (0.164186237), with a total accumulated weight and combined explanatory power of 60.28%. In addition to the top three ranked guidelines, 'Enterprise environmental resources' (0.130099741) was ranked number four, 'Execution process' (0.110193887) was ranked number five and 'System vendor's specialty' (0.090330484) was ranked number six. In all, the top six guidelines altogether account for 93.34% of the accumulated weight.

    After analyzing the 36 evaluation criteria (Figure 3), the top 10 ranked criteria were 'Clear project plan based on defined ERP capacity requirement, limited scope and focused flowchart' (0.13956222), 'Goal congruence between ERP project implementation and corporate strategy' (0.11949798), 'Top management support and commitment' (0.08556945), 'Extent of standard operating procedures and institutional processes' (0.07850048), 'User-friendly interface' (0.07310360), 'Systems integrated with an aggressive schedule and timeliness' (0.0599498), 'Provide technical assistance for rapid, effective transfer of best practice interventions' (0.05449806), 'Good interdepartmental communication and coordination on focused issue solution' (0.05397480), 'Enablement of business process reengineering' (0.04019322) and 'Solid management for project team building' (0.03980844). In all, the top 10 evaluation criteria had a combined accumulative weight of 74.47%.

    Overall, among the 36 evaluation criteria, four were ranked the highest, namely, a clear project plan based on a defined ERP capacity requirement, limited scope and focused flowchart; goal congruence between ERP project implementation and corporate strategy; top management support and commitment; and the extent of standard operating procedures and institutional processes. Meanwhile, if the analysis emphasized the aspects, Enterprise/ organization resources carried the highest weight (0.568), indicating a single aspect catches more than half of the total weight of all factors. This result is consistent with previous studies which suggest that organizational resources play a decisive role in shaping successful ERP system implementation (Davenport, 1998; Bingi et al., 1999; Zhang, 2000; Liu, 2003, Ye and Chen, 2005; Chauhan et al., 2012; Zhang et al., 2013). Interestingly, the consultant service factor carried the lowest weight (0.07), at less than 1%, suggesting that future improvement should be focused on strengthening an effective promotion of consultant services and technical support should be delivered to assist the company. Daniel (1961) argued that most companies should have at least three to six factors that are important to ERP success, and that these factors are the critical foundation that should be the focus of companies throughout the whole process to ensure that the system is successfully implemented.

    Based on the analysis of the 12 guidelines, this study suggests that case company R carefully examine the current internal and external environment as it pertains to the company's position in the overall industry, the company's performance relative to its peers and competitors and the economic and environmental resources available inside the entity that R can utilize to gain a competitive advantage. The analysis was purposed to ensure that efficient resource allocation will be applied to the important factors which are ranked top for the R enterprise.

    In addition, the results of this study indicate that senior managers generally recognize that the success of ERP system implementation is dependent on the organizational commitment, sufficient resource support and authorization, the attitude of the project leader, the competency of system users, the coordination and communication for the project, etc. Apart from focusing on the system implementation, the project team should also set up a special task group to constantly meet with each department to convey the aspiration and commitment from the top management and provide feedback to the top management as to whether each department has been able to adapt to the organizational changes.

    In a similar vein, strong support, active envelopment and encouragement and due care should be given to relevant executives and project team members so that they will understand the company's policies, and that these top-end ideas are pragmatic and feasible. This is a crucial step because only the project executives need to change their attitudes toward the new system, as all of the project team members will then embrace the new system with motivation and positive energy. As such, the team will be unified on this project without resistance and the team members will be active in training and education, which makes the whole process much more efficient.

    It is evident that the bottom six evaluation criteria were 'Consultancy fees', 'Consultant can build in cost-benefit metrics and analytical tools', 'Assist the company staff in training and education and technology transfer', 'Level of control in system implementation schedules', 'Staff has ability to understand and use information' and 'Good communication and coordination skills', from bottom one to bottom six, five of which are from 'Consultant service aspect'. This implies that, for the case company R, the future focus is to strengthen the ERP consultant communication and coordination.

    Therefore, the decision-makers should carefully select ERP vendors, and, prior to decision-making, it is necessary for them to do their homework to have some knowledge about vendors, particularly, whether the vendors are capable of analyzing and integrating into the company's base conditions, such as R & D, production, HR function, finance and marketing budget; and, whether consultant services are explicitly in alignment with the current organizational goals and strategies.

    This study involved employing a two-stage questionnaire based on the Delphi and AHP methods to generate the ranking to show the level of importance of key ERP success factors for R enterprise. The findings show that the top 10 key success factors are as follows: 1. clear project plan based on a defined ERP capacity requirement, limited scope and focused flowchart, 2. goal congruence between ERP project implementation and corporate strategy, 3. top management support and commitment, 4. extent of standard operating procedures and institutional processes, 5. user-friendly interface, 6. systems integrated with an aggressive schedule and timelines, 7. provision of technical assistance for rapid, effective transfer of best practice interventions, 8. good interdepartmental communication and coordination on focused issue solution, 9. enablement of business process reengineering and 10. solid management for project team building.

    The ERP systems are different from the packaged software, so the vendor needs to accurately tailor and deliver a customized system that suits the enterprise (often, the preparation stage requires one year, but the problem-solving is on a daily basis starting from the implementation); and, for the corporation, it is about communication and coordination between the enterprise and the vendor and how to achieve a mutual agreement between the both parties. The company should have ongoing meetings and consultation with the ERP vendor, as well as the consultant. It is recommended that each department sends one or two special representatives to participate in the future meetings and work on the system's planning and implementation issues. Likewise, the consultant can also achieve a full understanding of the current state of organizational functions and characteristics through a close and practical working relationship; as a result, this is helpful in reducing the level of resistance and failure rate of reengineering processes throughout the business.

    The authors declare they have not used artificial intelligence tools in the creation of this article.

    All authors declare no conflict of interest regarding the publication of this paper.



    [1] Solomon AA (2019) Large scale photovoltaics and the future energy system requirement. AIMS Energy 7: 600-618. doi: 10.3934/energy.2019.5.600
    [2] Denholm P, Margolis RM (2007) Evaluating the limits of solar photovoltaics (PV) in electric power systems utilizing energy storage and other enabling technologies. Energy Policy 35: 4424-4433. doi: 10.1016/j.enpol.2007.03.004
    [3] Lund PD, Lindgren J, Mikkola J, et al. (2015) Review of energy system flexibility measures to enable high levels of variable renewable electricity. Renewable Sustainable Energy Rev 45: 785-807. doi: 10.1016/j.rser.2015.01.057
    [4] Konziella H, Bruckner T (2016) Flexibility requirements of renewable energy based electricity systems-a review of research results and methodologies. Renewable Sustainable Energy Rev 53: 10-22. doi: 10.1016/j.rser.2015.07.199
    [5] Heide DM, Greiner Bremen L, Hoffmann C (2011) Reduced storage and balancing needs in a fully renewable European power system with excess wind and solar power generation. Renewable Energy 36: 2515-2523. doi: 10.1016/j.renene.2011.02.009
    [6] Solomon AA, Kammen DM, Callaway D (2016) Investigating the impact of wind-solar complementarities on energy storage requirement and the corresponding supply reliability criteria. Appl Energ 168: 130-145. doi: 10.1016/j.apenergy.2016.01.070
    [7] Heide D, Bremen L, Greiner M, et al. (2010) Seasonal optimal mix of wind and solar power in a future, highly renewable Europe. Renewable Energy 35: 2483-2489. doi: 10.1016/j.renene.2010.03.012
    [8] Esteban M, Zhang Q, Utama A (2012) Estimation of the energy storage requirement of a future 100% renewable energy system in Japan. Energy Policy 47: 22-31. doi: 10.1016/j.enpol.2012.03.078
    [9] Budischak C, Sewell D, Thomson H, et al. (2013) Cost-minimized combinations of wind power, solar power and electrochemical storage, powering the grid up to 99.9% of the time. J Power Sources 225: 60-74.
    [10] Child M, Breyer C (2016) The role of energy storage solutions in a 100% renewable Finnish energy system. Energy Procedia 99: 25-34. doi: 10.1016/j.egypro.2016.10.094
    [11] Caldera U, Bogdanov D, Afanasyeva S, et al. (2016) Integration of reverse osmosis seawater desalination in the power sector, based on PV and wind energy, for the Kingdom of Saudi Arabia. Proceedings of 32nd European Photovoltaic Solar Energy Conference, Munchen, 21-24.
    [12] Bogdanov D, Breyer C (2016) North-East Asian Super Grid for 100% renewable energy supply: Optimal mix of energy technologies for electricity, gas and heat supply options. Energ Convers Manage 112: 176-190. doi: 10.1016/j.enconman.2016.01.019
    [13] Child M, Breyer C (2016) Vision and initial feasibility analysis of a recarbonised Finnish energy system. Renewable Sustainable Energy Rev 66: 517-536. doi: 10.1016/j.rser.2016.07.001
    [14] Babrowski S, Jochem P, Fichtner W (2016) Electricity storage systems in the future German energy sector-An optimization of the German electricity generation system until 2040 considering grid restrictions. Comput Oper Res 66: 228-240. doi: 10.1016/j.cor.2015.01.014
    [15] Mileva A, Nelson JH, Johnston J, et al. (2013) Sunshot solar power reduces costs and uncertainty in future low-carbon electricity systems. Environ Sci Technol 47: 9053-9060. doi: 10.1021/es401898f
    [16] Brouwer A, van den Broek M, Zappa W, et al. (2016) Least-cost options for integrating intermittent renewables in low-carbon power systems. Appl Energ 161: 48-74. doi: 10.1016/j.apenergy.2015.09.090
    [17] Solomon AA, Faiman D, Meron G (2010) Properties and uses of storage for enhancing the grid penetration of very large-scale photovoltaic systems. Energy Policy 38: 5208-5222. doi: 10.1016/j.enpol.2010.05.006
    [18] Solomon AA, Faiman D, Meron G (2011) Appropriate storage for high-penetration grid-connected photovoltaic plants. Energy Policy 40: 335-344.
    [19] Solomon AA, Kammen DM, Callaway D (2014) The role of large-scale energy storage design and dispatch in the power grid: a study of very high grid penetration of variable renewable resources. Appl Energ 134: 75-89. doi: 10.1016/j.apenergy.2014.07.095
    [20] Solomon AA, Faiman D, Meron G (2010) Grid matching of large-scale wind energy conversion systems, alone and in tandem with large-scale photovoltaic systems: An Israeli case study. Energy Policy 38: 7070-7081. doi: 10.1016/j.enpol.2010.07.026
    [21] Solomon AA, Faiman D, Meron G (2010) The effects on grid matching and ramping requirements, of single and distributed PV systems employing various fixed and sun-tracking technologies. Energy Policy 38: 5469-5481. doi: 10.1016/j.enpol.2010.02.056
    [22] Solomon AA, Faiman D, Meron G (2010) An energy-based evaluation of the matching possibilities of very large photovoltaic plants to the electricity grid: Israel as a case study. Energy Policy 38: 5457-5468. doi: 10.1016/j.enpol.2009.12.024
    [23] Kroposki B (2017) Integrating high level of variable renewable energy into electricity power systems. J Mod Power Syst Cle 5: 831-827. doi: 10.1007/s40565-017-0339-3
    [24] Solomon AA, Bogdanov D, Breyer C (2019) Curtailment-storage-penetration nexus in energy transition. Appl Energ 235: 1351-1368. doi: 10.1016/j.apenergy.2018.11.069
    [25] Miglietta MM, Huld T, Monforti-Ferrario F (2017) Local complementarity of wind and solar energy resources over Europe: An assessment study from a meteorological perspective. J Appl Meteorol Climatol 56: 217-234. doi: 10.1175/JAMC-D-16-0031.1
    [26] Monferti F, Huld T, Bódis K, et al. (2014) Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach. Renewable Energy 63: 576-586.
    [27] Hoicha, EC, Rowlands IH (2011) Solar and wind resource complementarity: Advancing options for renewable electricity integration in Ontario, Canada. Renewable Energy 36: 97-107. doi: 10.1016/j.renene.2010.06.004
    [28] Gerlach AK, Stetter D, Schmid J, et al. (2011) PV and wind power-complementary technologies. 26th European Photovoltaic Solar Energy Conference, Hamburg, 5-9.
    [29] Huber M, Dimkova D, Hamacher T (2014) Integration of wind and solar power in Europe: Assessment of flexibility requirements. Energy 69: 236-246. doi: 10.1016/j.energy.2014.02.109
    [30] Rosa CDOCS, Costa KA, Christo EDS, et al. (2017) Complementarity of hydro, photovoltaic, and wind power in Rio de Janeiro State. Sustainability 9: 1130. doi: 10.3390/su9071130
    [31] Lund H (2006) Large-scale integration of optimal combinations of PV, wind and wave power into the electricity supply. Renewable Energy 31: 503-515. doi: 10.1016/j.renene.2005.04.008
    [32] Slusarewicz JH, Cohan DS (2018) Assessing solar and wind complementarity in Texas. Renew Wind Water Solar 5: 7. doi: 10.1186/s40807-018-0054-3
    [33] da Luz T, Moura P (2019) Power generation expansion planning with complementarity between renewable sources and regions for 100% renewable energy systems. Int T Electr Energy 29: e2817.
    [34] Shaner MR, Davis SJ, Lewis NS, et al. (2018) Geophysical constraints on the reliability of solar and wind power in the United States. Energy Environ Sci 11: 914-925. doi: 10.1039/C7EE03029K
    [35] Huang B, Krishnan V, Hodge BM (2018) Analyzing the impacts of variable renewable resources on California net-load ramp events. 2018 IEEE Power & Energy Society General Meeting, Portland, 5-10.
    [36] Risso A, Beluco A, Alves RCM (2018) Complementarity roses evaluating spatial complementarity in time between energy resources. Energies 11: 1918. doi: 10.3390/en11071918
    [37] Min CG, Kim MK (2017) Impact of the complementarity between variable generation resources and load on the flexibility of the Korean power system. Energies 10: 1719. doi: 10.3390/en10111719
    [38] Santos-Alamillos FJ, Pozo-Vazques D, Ruiz-Arias JA, et al. (2015) Combining wind farms with concentrating solar plants to provide stable renewable power. Renewable Energy 76: 539-550. doi: 10.1016/j.renene.2014.11.055
    [39] Gallardo RP, Rios AM, Ramirez JS (2020) Analysis of the solar and wind energetic complementarity in Mexico. J Clean Prod 268: 122323. doi: 10.1016/j.jclepro.2020.122323
    [40] Han S, Zhang L, Liu Y, et al. (2019) Quantitative evaluation method for the complementarity of wind-solar-hydro power and optimization of wind-solar ratio. Appl Energ 236: 973-984. doi: 10.1016/j.apenergy.2018.12.059
    [41] Sterl S, Vanderkelen I, Chawanda CJ, et al. (2020) Smart renewable electricity portfolios in West Africa. Nat Sustain
    [42] Oyewo AS, Aghahosseini A, Ram M, et al. (2020) Transition towards decarbonized power systems and its socio-economic impacts in West Africa. Renewable Energy 154: 1092-1112. doi: 10.1016/j.renene.2020.03.085
    [43] Jurasz J, Beluco A, Canales FA (2018) The impact of complementarity on power supply reliability of small scale hybrid energy systems. Energy 161: 737-743. doi: 10.1016/j.energy.2018.07.182
    [44] Demissie AA, Solomon AA (2016) Power system sensitivity to extreme hydrological conditions as studied using an integrated reservoir and power system dispatch model, the case of Ethiopia. Appl Energ 182: 442-463. doi: 10.1016/j.apenergy.2016.08.106
    [45] Barbosa LDSNS, Orozco JF, Bogdanov D, et al. (2016) Hydropower and power-to-gas storage options: The Brazilian energy system case. Energy Procedia 99: 89-107. doi: 10.1016/j.egypro.2016.10.101
    [46] Solomon AA, Child M, Caldera U, et al. (2017) How much energy storage is needed to incorporate very large intermittent renewables? Energy Procedia 135: 283-293. doi: 10.1016/j.egypro.2017.09.520
    [47] Pensini A, Rasmussen CN, Kempton W (2014) Economic analysis of using excess renewable electricity to displace heating fuels. Appl Energ 131: 530-543. doi: 10.1016/j.apenergy.2014.04.111
    [48] Mensah TNO The role of modern bioenergy in solar photovoltaic driven and defossilised power systems-The case of Ghana. MSc Thesis, LUT University, Lappeenranta, 2019
    [49] Weschenfelder F, Leite GNP, Costa AC, et al. (2020) A review on the complementarity between grid-connected solar and wind power systems. J Clean Prod 257: 120617. doi: 10.1016/j.jclepro.2020.120617
    [50] Jurasz J, Canales FA, Kies A, et al. (2020) A review on the complementarity of renewable energy sources: Concept, metrics, application and future research directions. Sol Energy 195: 703-724. doi: 10.1016/j.solener.2019.11.087
    [51] Yan J, Qu T, Han S, et al. (2020) Reviews on characteristic of renewables: Evaluating the variability and complementarity. Int T Electr Energy 30: e12281.
    [52] Liu LJ, Wang Z, Wang Y, et al. (2020) Optimizing wind/solar combinations at finer scales to mitigate renewable energy variability in China. Renewable Sustainable Energy Rev 132: 110151. doi: 10.1016/j.rser.2020.110151
    [53] Xu L, Wang ZW, Liu YF (2017) The spatial and temporal variation features of wind-sun complementarity in China. Energ Convers Manage 154: 138-148. doi: 10.1016/j.enconman.2017.10.031
    [54] Zhang HX, Cao YJ, Zhang Y, et al. (2018) Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data. Appl Energ 216: 172-182. doi: 10.1016/j.apenergy.2018.02.094
    [55] Holttinen H, Kiviluoma J, Levy T, et al. (2016) Design and Operation of Power Systems with Large Amounts of Wind Power: Final Summary Report, IEA WIND Task 25. Available from: https://www.vttresearch.com/sites/default/files/pdf/technology/2016/T268.pdf.
    [56] Child M, Kemfert C, Bogdanov D, et al. (2019) Flexible electricity generation, grid exchange and storage for the transition to a 100% renewable energy system in Europe. Renewable Energy 139: 80-101. doi: 10.1016/j.renene.2019.02.077
    [57] Cui M, Zhang J, Florita AR, et al. (2015) An Optimized swinging door algorithm for wind power ramp event detection. 2015 IEEE Power & Energy Society General Meeting, 26-30.
    [58] Debnath K, Goel L (1995) Power system planning-a reliability perspective. Electr Pow Syst Res 34: 179-185. doi: 10.1016/0378-7796(95)00976-X
    [59] Breyer C, Bogdanov D, Aghahosseini A, et al. (2020) On the techno-economic benefits of a global energy interconnection. EEEP 9: 83-102.
    [60] Bogdanov D, Farfan J, Sadovskaia K, et al. (2019) Radical transformation pathway towards sustainable electricity via evolutionary steps. Nat Commun 10: 1077. doi: 10.1038/s41467-019-08855-1
    [61] Ram M, Bogdanov D, Aghahosseini A, et al. (2019) Global Energy System Based on 100% Renewable Energy-Power, Heat, Transport and Desalination Sectors, Lappeenranta: LUT University and Energy Watch Group.
    [62] Ram M, Bogdanov D, Aghahosseini A, et al. (2020) 100% Renewable Europe: How to Make Europe's Energy System Climate-Neutral Before 2050, Brussels and Lappeenranta: SolarPower Europe and LUT University.
    [63] Caldera U, Bogdanov D, Breyer C (2016) Local cost of seawater RO desalination based on solar PV and wind energy-A global estimate. Desalination 385: 207-216. doi: 10.1016/j.desal.2016.02.004
    [64] Breyer C, Bogdanov D, Gulagi A, et al. (2017) On the role of solar photovoltaics in global energy transition scenarios. Prog Photovolt 25: 727-745. doi: 10.1002/pip.2885
    [65] Soder L, Tomasson E, Estanqueiro A, et al. (2020) Review of wind generation within adequacy calculations and capacity markets for different power systems. Renewable Sustainable Energy Rev 119: 109540. doi: 10.1016/j.rser.2019.109540
    [66] Caldera U, Breyer C (2018) The role that battery and water storage play in Saudi Arabia's transition to an integrated 100% renewable energy power system. J Energy Storage 17: 299-310. doi: 10.1016/j.est.2018.03.009
    [67] Azzuni A, Breyer C (2020) Global Energy Security index and its Application on National level. Energies 13: 2502. doi: 10.3390/en13102502
    [68] Breyer C, Tsupari E, Tikka V, et al. (2015) Power-to-gas as an emerging profitable business through creating an integrated value chain. Energy Procedia 73: 182-189. doi: 10.1016/j.egypro.2015.07.668
    [69] Child M, Nordling A, Breyer C (2018) The impacts of high V2G participation in a 100% renewable Åland energy system. Energies 11: 2206. doi: 10.3390/en11092206
    [70] Taljegard M, Walter V, Goransson L, et al. (2019) Impact of electric vehicles on the cost-competitiveness of generation and storage technologies in electricity system. Environ Res Lett 14: 12.
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