Multicriteria and cost benefit analysis for smart grid projects
2 likes736 views
The ISGAN webinar discusses the integrated approach of multicriteria analysis (MCA) and cost-benefit analysis (CBA) for assessing smart grid projects. It highlights the importance of addressing both tangible and intangible impacts in decision-making and identifies gaps in current analytical frameworks. The webinar emphasizes the need for improved methodologies to effectively evaluate smart grid initiatives while considering various criteria and stakeholder perspectives.
![MCA-CBA: a case study
04/09/2018 ISGAN ACADEMY WEBINAR 44
Alternative
PM_ECO PM_SG
NPV
[k€]
KPI1A
[MW]
KPI2A
[MW]
KPI2B
𝒐𝒄𝒄.
𝒚𝒓
KPI2C
𝒉𝒓
𝒚𝒓
KPI2D
[p.u.]
KPI3A
[MWh]
A_1 0 0 0 2.026 0.837 11.48 11216.1
A_2 4.257 66.2 1269.2 2.017 0.751 10.68 10677.7
A_3 3.371 184.2 2903.9 2.017 0.751 10.68 10701.3
A_4 12.905 48.4 984.6 2.017 0.751 10.68 10661.3
A_5 88.587 38.2 574.1 2.017 0.751 10.69 10682.4
Alternative Bus equipped
with DES
PDES
[kW]
EDES
[kWh]
A_1 No DES 0 0
A_2 7 100 100
A_3 14 200 400
A_4 16 100 100
A_5 14 100 100
Performance Matrix
DES Topology information
𝑁𝑃𝑉 = 𝐶𝑖𝑛𝑣
𝑇
+ 𝐶𝑖𝑛𝑣
𝐷𝐸𝑆
+ 𝑄 𝐸𝑋𝐶
KPI1A =
𝑖=1
𝑁 𝐷𝐸𝑆 𝑃𝐷𝐸𝑆,𝑖
(𝑜𝑢𝑡)
+ 𝑃𝐷𝐸𝑆,𝑖
(𝑖𝑛)
2
KPI2A =
𝑖=1
𝑁 𝐷𝐸𝑆
ℎ=1
𝑁ℎ
൯mi n( 𝑆𝑜𝐶ℎ,𝑖 ∙ 𝜂 𝑑𝑖𝑠,𝑖, 𝑃𝑛,𝑖
𝐾𝑃𝐼2𝐵 = 𝑆𝐴𝐼𝐷𝐼 =
σ𝑖=1
𝑛
𝑈𝑖 𝑁𝐶𝑖
σ𝑖=1
𝑛
𝑁𝐶𝑖
𝐾𝑃𝐼2𝐶 = 𝑆𝐴𝐼𝐹𝐼 =
σ𝑖=1
𝑛
𝜆𝑖 𝑁𝐶𝑖
σ𝑖=1
𝑛
𝑁𝐶𝑖
𝐾𝑃𝐼2𝐷 =
𝑖=1
𝑛
ℎ=1
𝑁ℎ
𝑉 𝑚𝑎𝑥.𝑖
ℎ
− 𝑉 𝑚𝑖𝑛.𝑖
ℎ
𝐾𝑃𝐼3𝐴 =
𝑗=1
𝑁 𝑒
𝑘=1
𝑁ℎ
𝐸 𝐿 𝑗,𝑘
Investments and reactive power exchange net value
Maximum use in power of dispachable resources
Active power available for black start
System Average Interruption Duration Index
System Average Interruption Frequency Index
Voltage variation index
Expected network energy losses
n: number of busses; Nh: number of time intervals; NDES: number of DES;
Ne: number of network elements](https://image.slidesharecdn.com/isganwebinar04102018revmt0409-190614071212/85/Multicriteria-and-cost-benefit-analysis-for-smart-grid-projects-44-320.jpg)
Multicriteria and cost benefit analysis for smart grid projects
- 1. ISGAN- WEBINAR Multicriteria and cost benefit analysis for smart grid projects Fabrizio Pilo, Italy Matteo Troncia, Italy 04 September 2018 iea-isgan.org
- 2. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 2
- 3. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 3
- 4. ISGAN in a Nutshell ‘Strategic platform to support high-level government attention and action for the accelerated development and deployment of smarter, cleaner electricity grids around the world’ 04/09/2018 ISGAN ACADEMY WEBINAR 4 • An initiative of the Clean Energy Ministerial (CEM) • Organised as the Implementing Agreement for a Co-Operative Programme on Smart Grids (ISGAN) The CEM is the only multilateral forum dedicated exclusively to the advancement of clean energy technologies and related policies. ISGAN is the only global government forum on smart grids
- 5. Activities of ISGAN 04/09/2018 ISGAN ACADEMY WEBINAR 5 • Annex 1: Global smart grid inventory • Annex 2: Smart grid case studies • Annex 3: Cost-benefits analysis and toolkits • Annex 4: Insight for decision makers • Annex 5: Smart Grid International Research Facility Network (SIRFN) • Annex 6: Power T&D systems • Annex 7: Smart grid transitions • Annex 8: ISGAN smart grid academy
- 6. Geography of ISGAN 04/09/2018 ISGAN ACADEMY WEBINAR 6
- 7. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 7
- 8. Context and motivation The smart grid transition 04/09/2018 ISGAN ACADEMY WEBINAR 8 Key drivers • Environmental and regulatory pressure • Market liberalization • Security of supply and increase quality of service • Copper investment postponement • Increase dispersed renewable energy • Flexibility (storage, electric vehicle, active demand) Main challenges • Increasing complexity • Effective integration of distributed resources • Dynamic optimization of grid operations and resources • Development and integration of demand response • Ensure self-healing, energy efficiency and sustainability • Ensure cyber-security and interoperability Image credits: vector market from the Noun Project (https://thenounproject.com/)
- 9. Context and motivation Smart grids: impacts span over the power system borders 04/09/2018 ISGAN ACADEMY WEBINAR 9 Novel features and enabled services will produce relevant socio-economic impacts Impact characteristics: • Wide range impacts • Indirect/side effects • Intangible impacts • Lack of data availability • Data uncertainty Implications: • Not only monetary aspects are of interest • Identify clearly the impact allocation is difficult • Quantify all impacts is not possible • Strategic decision making is under uncertainty
- 10. Context and motivation Key elements of decision making in planning 04/09/2018 ISGAN ACADEMY WEBINAR 10 Goal: identify the best option > Option analysis: assess the option performances on several conflicting criteria > Decision making: making trade-offs taking into account the stakeholder perspective > The optimal solution: typically achieves a comfortable level of performances by minimising the related cost Smart grid planning calls for effective tools for complex decision-making problems
- 11. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 11
- 12. Cost-Benefit Analysis Economic based tool for project analysis 04/09/2018 ISGAN ACADEMY WEBINAR 12 Cost-Benefit Analysis (CBA) is one of the most acknowledged tool for assessing the financial viability of industrial projects Cost-Benefit Analysis (CBA): • seeks for an optimal resource allocation in which the monetary benefit outclass costs • seeks for the most profitable investment alternative • Makes an incremental analysis with respect to a reference scenario • Produces easy-to-read economic indicators > Net Present Value (NPV): net benefit produced > Internal Rate of Return (IRR): discount rate value that makes the NPV equal to zero > Cost Benefit Ratio (CBR): the ratio of the present value of benefits and costs
- 13. Target and context recognition Cost and benefit quantification Monetising and discounting Cost and benefit aggregation Output indices: NPV, IRR, CBR Sensitivity analysis Cost-Benefit Analysis Steps of CBA 04/09/2018 ISGAN ACADEMY WEBINAR 13 Several regulatory frameworks require a positive CBA for approving the project
- 14. Cost-Benefit Analysis CBA for societal decision-making 04/09/2018 ISGAN ACADEMY WEBINAR 14 • Sector-specific CBA guidelines have been devised by government bodies • CBA of large infrastructural projects that involve public interests is not fully acknowledged • Societal project assessment highlights the weaknesses of CBA, the monetary-based tools show several conceptual flaws when intangible impacts are involved: Quantifying Intangible impacts are not clearly quantifiable Often, only a qualitative assessment is possible Monetizing Monetization techniques misrepresent the point of view of individuals on intangible impacts Discounting Discounting of intangible impacts appears unsound because it leads to an increased burden on future generations
- 15. Cost-Benefit Analysis CBA for societal decision-making 04/09/2018 ISGAN ACADEMY WEBINAR 15 Private sector Public sector • Involve people as customers • Goods and services are exchanged within a market • Tangible impacts are majoritarian • Investor target: maximise the profits • Involve people as citizens (and/or taxpayers) • Goods and services does not have a market • Intangible impacts are not negligible • Investor target: maximise the efficiency and the effectiveness of investment costs Image credits: vector market from the Noun Project (https://thenounproject.com/)
- 16. Cost-Benefit Analysis CBA for smart grids 04/09/2018 ISGAN ACADEMY WEBINAR 16 Key issues: • Obtain an effective classification of impacts • High risk of double counting • Obtain a multiplicity of feasible future scenarios • Forecast the price trend of technologies related to smart grids • Identify and consider the synergy of different smart grid assets • Generalise methods and results on different countries
- 17. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 17
- 18. Multi-Criteria Analysis Operation research tool for decision-making 04/09/2018 ISGAN ACADEMY WEBINAR 18 Multi-Criteria Analysis (MCA): • Helps decision makers in identifying the best option among a given set • Acknowledged tools for addressing complex decision-making problems • Encourages problem decomposition • Appraises mutually conflicting criteria • Tangible and intangible impacts are simultaneously evaluated • Allows for qualitative appraisals • Stakeholder point of view is directly involved in the evaluation process • Allows for probabilistic modelling
- 19. Target and context recognition Identify the alternatives under analysis Identify evaluation criteria Scoring of alternatives performance Weighting of criteria Score and weight combining Result Analysis Sensitivity analysis Multi-Criteria Analysis Operation research tool for decision-making 04/09/2018 ISGAN ACADEMY WEBINAR 19 Plenty of MCA methods exist in Literature, based on different philosophies > MCA/Multi-Objective Decision Making (MODM): design a set of optimal solutions by minimising the objectives > MCA/Multi-Attribute Decision-Making (MADM): find the best alternative among an explicitly known set Steps of MCA/MADM
- 20. Multi-Criteria Analysis MCAMADM approaches 04/09/2018 ISGAN ACADEMY WEBINAR 20 Full Aggregation Approach (FAA) • Linear additive combination of weights and scores • Provide a complete ranking with overall scores • Compensative methods Analytic Hierarchy Process (AHP) Multi-Attribute Utility Theory (MAUT) … Outranking Methods (OM) • Based on the concept of outranking • Provide a partial ranking • Not compensative methods ELECTRE family PROMETHEE … Goal Aspiration Approach (GAA) • Based on the distance between each alternative and an ideal (best or worst) option • The best one has compromising a distance from both TOPSIS VIKOR …
- 21. Multi-Criteria Analysis MCAMADM key elements 04/09/2018 ISGAN ACADEMY WEBINAR 21 Criteria Hierarchy Performance Matrix Stakeholders’ value scale Image credits: vector market and Andrejs Kirma from the Noun Project (https://thenounproject.com/)
- 22. Multi-Criteria Analysis MCAMADM key elements 04/09/2018 ISGAN ACADEMY WEBINAR 22 Criteria Hierarchy Performance Matrix Stakeholders’ value scale MCA Technique Global worthiness of each alternative Image credits: vector market, Andrejs Kirma, and iconcheese from the Noun Project (https://thenounproject.com/)
- 23. Multi-Criteria Analysis Cons of MCA 04/09/2018 ISGAN ACADEMY WEBINAR 23 • No explicit rule such that benefits must exceed costs exists The identified best option may not purse well-being improvement: the "doing nothing" principle might result as preferable • Subjectivity is directly introduced by criteria weights and qualitative appraisals of alternatives Effective strategies for reject personal biases needs to be employed • The multiplicity of MCA/MADM techniques available in Literature makes arduous identify the most suitable one • The complexity of some MCA/MADM technique limits the diffusion outside the academic borders
- 24. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 24
- 25. Gaps of current analytical frameworks Smart grid assessment frameworks 04/09/2018 ISGAN ACADEMY WEBINAR 25 • Several methods are devised on the specific case study • Several methods are devised as general frameworks • Several methods consider only quantitively criteria Most smart grid assessment frameworks descend from EPRI approach Courtesy of ISGAN: Nordling, A., Pädam, S., af Burén, C. & Jörgensen, P., (2018). Social costs and benefits of smart grid technologies
- 26. Gaps of current analytical frameworks Smart grid assessment frameworks 04/09/2018 ISGAN ACADEMY WEBINAR 26 Main requirements • Large amount of input data • High analyst know-how • Low replicability ‒ on different contexts ‒ on different assets • Low comparability of results from different frameworks Courtesy of ISGAN: Nordling, A., Pädam, S., af Burén, C. & Jörgensen, P., (2018). Social costs and benefits of smart grid technologies
- 27. Gaps of current analytical frameworks Gap analysis of smart grid assessment frameworks 04/09/2018 ISGAN ACADEMY WEBINAR 27 Identified gaps Limited feedbacks from real smart grid projects Courtesy of ISGAN: Nordling, A., Pädam, S., af Burén, C. & Jörgensen, P., (2018). Social costs and benefits of smart grid technologies Recommendations Improve: methods for accounting the impacts; data collection and sharing from real smart grids; applications of the assessment frameworks; The gap between users’ requirements and methods for smart grid assessment Develop novel MCA-oriented tools for simplifying decision making processes Lack of unprofitable projects reassessment Add one more step for identifying weaknesses and opportunities to increase the project profitability A gap in how to deal with uncertainty and regulation Update guidelines by adding methodologies for sensitivity and scenario analysis
- 28. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 28
- 29. MCA-CBA: a combined approach Cost-Benefit Analysis vs. Multi-Criteria Analysis 04/09/2018 ISGAN ACADEMY WEBINAR 29 ✓ Rigorous and rational ✓ Formalised ✓ Widely acknowledged ✓ Easy communication of the results Cost-Benefit Analysis (CBA) x Difficult and expensive x Large data requirement (often hardly obtainable) x Impossible to assess “soft effects” ✓ Flexible ✓ Monetisation of impacts is not mandatory ✓ Assesses “soft effects” ✓ Assures participation and legitimacy Multi-Criteria Analysis (MCA) x Potentially subjective x Double counting risk x Lacks in respecting the Kaldon-Hicks criterion
- 30. The joint approach: ✓ relieves the respective lacks ✓ emphasises the respective strengths MCA-CBA: a combined approach Strengths of a combined evaluation approach 04/09/2018 ISGAN ACADEMY WEBINAR 30 CBA: • acknowledged and reliable tool for an economic/financial evaluation of tangible impacts • shows some fundamental shortcomings when a great share of intangible impacts are involved MCA: • allows for considering multiple heterogenous and even conflicting criteria • monetization of all impact is not required, soft effects are directly evaluable MCA-CBA Monetary evaluation CBA Non-monetary evaluation MCACBA and MCA are complementary tools Image credits: vector market, Nithinan Tatah, and iconcheese from the Noun Project (https://thenounproject.com/)
- 31. MCA-CBA: a combined approach Different ways for combining the approaches 04/09/2018 ISGAN ACADEMY WEBINAR 31 CBA as economic criterion of an MCA framework CBA focused on tangible impacts MCA focuses on intangible impacts MCA for selecting a subset of interesting investment options CBA for evaluating the economic viability of the selected options Image credits: vector market from the Noun Project (https://thenounproject.com/)
- 32. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA) • Multicriteria Analysis (MCA) • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 32
- 33. MCA-CBA for smart grid assessment 04/09/2018 ISGAN ACADEMY WEBINAR 33 Complies with international guidelines on project assessment (i.e. EU Joint Research Centre - JRC) Evaluates the options on 3 different areas Economic assessment Smart grid deployment merit assessment Externality impact assessment Overall evaluation Courtesy of ISGAN: Pilo, F. & Troncia, M. (2018). Combined MC-CBA methodology for decision making on Smart Grid.
- 34. MCA-CBA for smart grid assessment 04/09/2018 ISGAN ACADEMY WEBINAR 34 A hierarchy of criteria decomposes the decision-making problem The 3 main branches are independent Courtesy of ISGAN: Pilo, F. & Troncia, M. (2018). Combined MC-CBA methodology for decision making on Smart Grid.
- 35. MCA-CBA for smart grid assessment 04/09/2018 ISGAN ACADEMY WEBINAR 35 The economic branch The economic branch evaluates the monetary impacts The economic performance indicators are the indexes obtained from a CBA: > Net Present Value (NPV) > Internal Rate of Return (IRR) > Cost Benefit Ratio (CBR) The CBA may follows international guidelines (e.g.: EPRI, JRC, etc…) Obtain a positive CBA evaluation may represent a requirement for defining a subset of projects
- 36. MCA-CBA for smart grid assessment 04/09/2018 ISGAN ACADEMY WEBINAR 36 The smart grid deployment merit branch The smart grid deployment merit assessment is evaluated according to JRC’s guidelines It is focused on the contribution towards the smart grid realization given by each project option General benefits for the energy sector, organised as Policy criteria (PC) The fulfilment of each PC is is appraised by means of Key Performance Indicators (KPIs) The evaluation is output based. The produced effects of the infrastructure are evaluated instead of its technical features
- 37. MCA-CBA for smart grid assessment 04/09/2018 ISGAN ACADEMY WEBINAR 37 List of the PC and KPIs • PC1: Level of sustainability • PC2: Capacity of transmission and distribution grids to connect and bring electricity from and to users • PC3: Network connectivity and access to all categories of network users • PC4: Security and quality of supply • PC5: Efficiency and service quality in electricity supply and grid operation • PC6: Contribution to cross-border electricity markets by load-flow control to alleviate loop- flows and increase interconnection capacities a. Reduction of greenhouse gas emissions (GHG) b. Environmental impact of electricity grid infrastructure a. Installed capacity of distributed energy resources in distribution networks b. Allowable maximum injection of power without congestion risks in transmission networks c. Energy not withdrawn from renewable sources due to congestion or security risks a. Methods adopted to calculate charges and tariffs, as well as their structure, for generators, consumers and those that do both b. Operational flexibility provided for dynamic balancing of electricity in the network a. Ratio of reliably available generation capacity and peak demand b. Share of electricity generated from renewable sources c. Stability of the electricity system d. Duration and frequency of interruptions per customer, including climate related disruptions e. Voltage quality performance a. Level of losses in transmission and in distribution networks b. Ratio between minimum and maximum electricity demand within a defined time period c. Demand side participation in electricity markets and in energy efficiency measures d. Percentage utilisation (i.e. average loading) of electricity network components e. Availability of network components (related to planned and unplanned maintenance) and its impact on network performances f. Actual availability of network capacity with respect to its standard value a. Ratio between interconnection capacity of a Member State and its electricity demand b. Exploitation of interconnection capacities c. Congestion rents across interconnections PC1 PC2 PC3 PC4 PC5 PC6 Giordano, V., Onyeji, I., Fulli, G., Jiménez, M., & Filiou, C. (2012). Guidelines for cost benefit analysis of smart metering deployment. JRC Scientific and Tech. Research.
- 38. MCA-CBA for smart grid assessment 04/09/2018 ISGAN ACADEMY WEBINAR 38 The externality branch The externality branch assesses the project options in terms of their externalities Non-monetizable impacts excluded from previous branches (e.g., enviromental impacts) Single impacts (INX) Thematic areas (EXT) Each impact is measured by a quantitative or qualitative index. It is assumed that the second level criteria are mutually dependent
- 39. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA), description, pros and cons • Multicriteria Analysis (MCA), description, pros and cons • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 39
- 40. MCA-CBA: a case study 04/09/2018 ISGAN ACADEMY WEBINAR 40 Distribution grid planning of a MV rural grid Evaluation of several Active Distribution Network (ADN) planning options devised by a multi-objective algorithm (NSGA-II) Each considered planning option consists in: • traditional network reinforcement • siting and sizing of distributed energy storage (DES) o Time horizon: 10 years o Topology of the network is fixed o Load growth rate: 3% for each bus o Operation is evaluated by a probabilistic load flow
- 41. MCA-CBA: a case study 04/09/2018 ISGAN ACADEMY WEBINAR 41 The economic branch The CBA is evaluated for each alternative The economic performance indicator is the Net Present Value: NPV It considers: • the network reinforcement cost • the cost of reactive power exchange with the Transmission System Operator • the cost of Distribution Energy Storage (DES) devices
- 42. MCA-CBA: a case study 04/09/2018 ISGAN ACADEMY WEBINAR 42 The smart grid deployment merit branch 3 Policy criteria with 6 related KPI are identified as relevant 1. PC1: Network connectivity and access to all categories of network users KPI1A: Operational flexibility provided for dynamic balancing of electricity in the network 2. PC2: Security and quality of supply KPI2A: Stability of the electricity system KPI2B: Duration of interruptions per customer KPI2C: Frequency of interruptions per customer KPI2D: : Voltage quality performance – voltage variations 3. PC3: Efficiency and service quality in electricity supply and grid operation KPI3A: Level of losses in distribution networks
- 43. MCA-CBA: a case study 04/09/2018 ISGAN ACADEMY WEBINAR 43 Overview of the decision-making problem Branch Local Priority Economic 0.5 Smart grid paradigm 0.5 Terminal Criterion Global Priority NPV 0.500 KPI1A 0.1667 KPI2A 0.0417 KPI2B 0.0417 KPI2C 0.0417 KPI2D 0.0417 KPI3A 0.1667 Assigned criteria weights
- 44. MCA-CBA: a case study 04/09/2018 ISGAN ACADEMY WEBINAR 44 Alternative PM_ECO PM_SG NPV [k€] KPI1A [MW] KPI2A [MW] KPI2B 𝒐𝒄𝒄. 𝒚𝒓 KPI2C 𝒉𝒓 𝒚𝒓 KPI2D [p.u.] KPI3A [MWh] A_1 0 0 0 2.026 0.837 11.48 11216.1 A_2 4.257 66.2 1269.2 2.017 0.751 10.68 10677.7 A_3 3.371 184.2 2903.9 2.017 0.751 10.68 10701.3 A_4 12.905 48.4 984.6 2.017 0.751 10.68 10661.3 A_5 88.587 38.2 574.1 2.017 0.751 10.69 10682.4 Alternative Bus equipped with DES PDES [kW] EDES [kWh] A_1 No DES 0 0 A_2 7 100 100 A_3 14 200 400 A_4 16 100 100 A_5 14 100 100 Performance Matrix DES Topology information 𝑁𝑃𝑉 = 𝐶𝑖𝑛𝑣 𝑇 + 𝐶𝑖𝑛𝑣 𝐷𝐸𝑆 + 𝑄 𝐸𝑋𝐶 KPI1A = 𝑖=1 𝑁 𝐷𝐸𝑆 𝑃𝐷𝐸𝑆,𝑖 (𝑜𝑢𝑡) + 𝑃𝐷𝐸𝑆,𝑖 (𝑖𝑛) 2 KPI2A = 𝑖=1 𝑁 𝐷𝐸𝑆 ℎ=1 𝑁ℎ ൯mi n( 𝑆𝑜𝐶ℎ,𝑖 ∙ 𝜂 𝑑𝑖𝑠,𝑖, 𝑃𝑛,𝑖 𝐾𝑃𝐼2𝐵 = 𝑆𝐴𝐼𝐷𝐼 = σ𝑖=1 𝑛 𝑈𝑖 𝑁𝐶𝑖 σ𝑖=1 𝑛 𝑁𝐶𝑖 𝐾𝑃𝐼2𝐶 = 𝑆𝐴𝐼𝐹𝐼 = σ𝑖=1 𝑛 𝜆𝑖 𝑁𝐶𝑖 σ𝑖=1 𝑛 𝑁𝐶𝑖 𝐾𝑃𝐼2𝐷 = 𝑖=1 𝑛 ℎ=1 𝑁ℎ 𝑉 𝑚𝑎𝑥.𝑖 ℎ − 𝑉 𝑚𝑖𝑛.𝑖 ℎ 𝐾𝑃𝐼3𝐴 = 𝑗=1 𝑁 𝑒 𝑘=1 𝑁ℎ 𝐸 𝐿 𝑗,𝑘 Investments and reactive power exchange net value Maximum use in power of dispachable resources Active power available for black start System Average Interruption Duration Index System Average Interruption Frequency Index Voltage variation index Expected network energy losses n: number of busses; Nh: number of time intervals; NDES: number of DES; Ne: number of network elements
- 45. MCA-CBA: a case study 04/09/2018 ISGAN ACADEMY WEBINAR 45 Result Alternative Economic score Smart grid merit score Alternative A_1 0.027 0.027 Alternative A_2 0.207 0.241 Alternative A_3 0.207 0.248 Alternative A_4 0.239 0.255 Alternative A_5 0.320 0.230 Alternative Overall Score Alternative A_5 0.275 Alternative A_4 0.247 Alternative A_3 0.227 Alternative A_2 0.224 Alternative A_1 0.027 Overall scores Partial scores Sensitivity analysis on criteria weights Breakpoint A_5 A_4 A_1 A_2 A_3 Best: A_5Best: A_4
- 46. MCA&CBA: other applications 04/09/2018 ISGAN ACADEMY WEBINAR 46 Cost-benefit analysis for energy storage exploitation in distribution systems, 2017 A sequential MCA-CBA funded by the Italian Regulator to define the condition for remunerating DSOs which owns and operates storage for network issues. A large number of plans involving storage devices are devised by using a multi-objective optimisation approach. Then, the economic sustainability of the alternatives belonging to the Pareto front is assessed by a CBA. G. Celli, F. Pilo, G. Pisano, and G. G. Soma, “Cost-benefit analysis for energy storage exploitation in distribution systems,” in CIRED - Open Access Proceedings Journal, 2017, vol. 2017, no. 1. Smart Grid Multi-Criteria Analysis (SG-MCA) of the Sino-Singapore TEC Project, 2016 A MCA is used for evaluating the TEC smart grid demonstration project which is divided in three sub-projects: Distributed Automation, MicroGrid, and Smart SubStation. Four different evaluation domains are considered: technological, economic, social, and practical. An index is assigned to each subproject according to the performances on each domain. An overall score is computed by using the proposed SG-MCA method which combines AHP and fuzzy evaluation method. Marnay, C., Liu, L., Yu, J., Zhang, D., Mauzy, J., Shaffer, B., ... & He, G. (2016). White Paper on Benefits Analysis of Smart Grid Projects. Multicriterial decision making: the smart metering case, 2018 The upgrading plan of the Italian smart metering infrastructure is evaluated by means of MC-CBA approach. Three different area of interest are investigated: economic, enhanced smartness of the grid, and externalities. Three different MCA techniques to investigate the effects on the provided result. Pilo, F. & Troncia, M. (2018). Multicriterial decision making: the smart metering case, .ISGAN discussion paper, Ricerca sul Sistema Energetico (RSE). Available soon on http://www.iea-isgan.org/.
- 47. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA), description, pros and cons • Multicriteria Analysis (MCA), description, pros and cons • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 47
- 48. Conclusions 04/09/2018 ISGAN ACADEMY WEBINAR 48 • Smart grids generate wide range impacts which outclass the power system borders • A new assessment approach for properly considering the potential of smart grid technologies and their effects on the society is required • A joint MCA-CBA approach outclasses the weaknesses of both CBA and MCA by emphasizing their respective strengths • MCA-CBA assessment framework allows decision makers to: • Assess impacts on different areas of interest • Assess monetary and intangible impacts • Reduce data requirements for the assessment • Promote an active participation of stakeholders Develop automatized MCA-CBA tools allows to analyse large sets of planning options
- 49. Outline • About ISGAN • Context and motivation • Cost-Benefit Analysis (CBA), description, pros and cons • Multicriteria Analysis (MCA), description, pros and cons • Gaps of current analytical frameworks • MCA-CBA: a combined approach • MCA-CBA for smart grid assessment • MCA-CBA: a case study • Conclusions • Future works 04/09/2018 ISGAN ACADEMY WEBINAR 49
- 50. Future works 04/09/2018 ISGAN ACADEMY WEBINAR 50 For promoting smart grids: • a simple and shared framework for project assessment will encourage the comparison of projects among different regions • data sharing about smart grid initiatives needs to be promoted for improving the effectiveness of the proposed assessment frameworks • technological coverage of assessment frameworks needs to be extended • effective strategies for considering uncertainties needs to be investigated • common feasible scenarios needs to be devised for foreseeing the influence on smart grid development • subjectivity in the analysis have to be rejected by devising effective weight elicitation processes
- 51. Further readings 04/09/2018 ISGAN ACADEMY WEBINAR 51 • Pilo, F. & Troncia, M. (2018). Combined MC-CBA methodology for decision making on Smart Grid. International Smart Grid Action Network (ISGAN), Ricerca sul Sistema Energetico (RSE). Available soon on http://www.iea-isgan.org/. • Nordling, A., Pädam, S., af Burén, C. & Jörgensen, P., (2018). Social costs and benefits of smart grid technologies. Swedish Smart Grid Forum, International Smart Grid Action Network (ISGAN) and Swedish Energy Market Inspectorate. Available soon on http://www.iea-isgan.org/. • Pilo, F. & Troncia, M. (2018). Multicriterial decision making: the smart metering case. ISGAN discussion paper, Ricerca sul Sistema Energetico (RSE). Available soon on http://www.iea-isgan.org/. • Celli, G., Chowdhury, N., Pilo, F., Soma, G. G., Troncia, M., & Gianinoni, I. M. (2018). Multi-Criteria Analysis for decision making applied to active distribution network planning. Electric Power Systems Research, 164, 103-111. Available on https://authors.elsevier.com/c/1XWsZ1M7~0cDYO. • Celli, G., Pilo, F., Pisano, G., & Soma, G. G. (2018). Distribution energy storage investment prioritization with a real coded multi-objective Genetic Algorithm. Electric Power Systems Research, 163, 154-163. • Pilo, F., Celli, G., Ghiani, E., & Soma, G. G. (2013). New electricity distribution network planning approaches for integrating renewable. Wiley Interdisciplinary Reviews: Energy and Environment, 2(2), 140-157. • Dodgson, J. S., Spackman, M., Pearman, A., & Phillips, L. D. (2009). Multi-criteria analysis: a manual. • Ishizaka, A., & Nemery, P. (2013). Multi-criteria decision analysis: methods and software. John Wiley & Sons. • Ackerman, F., & Heinzerling, L. (2002). Pricing the priceless: Cost-benefit analysis of environmental protection. University of Pennsylvania Law Review, 150(5), 1553-1584. • Jiménez, M. S., Onyeji, I., Giordano, V., Fulli, G., & Filiou, C. (2012). Guidelines for Conducting a Cost-benefit analysis of Smart Grid projects . JRC Scientific and Tech. Research. Publications Office: Luxembourg, Luxembourg. • Giordano, V., Onyeji, I., Fulli, G., Jiménez, M., & Filiou, C. (2012). Guidelines for cost benefit analysis of smart metering deployment. JRC Scientific and Tech. Research. Publications Office: Luxembourg, Luxembourg. • Giordano, V., Vitiello, S., & Vasiljevska, J. (2014). Definition of an assessment framework for projects of common interest in the field of smart grids. JRC Science and policy reports. Publications Office: Luxembourg, Luxembourg. • Electric Power Research Institute (EPRI). (2015). Guidebook for Cost/Benefit Analysis of Smart Grid Demonstration Projects, Revision 3, Technical Update. • Marnay, C., Liu, L., Yu, J., Zhang, D., Mauzy, J., Shaffer, B., ... & He, G. (2016). White Paper on Benefits Analysis of Smart Grid Projects.
- 52. Thank you Fabrizio Pilo, Italy pilo@diee.unica.it Matteo Troncia, Italy matteo.troncia@diee.unica.it iea-isgan.og
- 53. Image Credits 04/09/2018 ISGAN ACADEMY WEBINAR 53 The graphics have been designed by composing the artworks of Vectors Market, slides 8, 15, 21, 22, 30, 31, 33. Nithinan Tatah, slides 30. Iconcheese, slides 9, 14, 22, 26, 27, 30, 33, 36, 38. Andrejs Kirma, slides 21, 22. from the Noun Project (https://thenounproject.com/).