An integrated planning framework for the development of sustainable and resilient cities (the EU FP7 InSMART project) Rocco De Miglio rocco.demiglio@e4sma.com Alessandro Chiodi alessandro.chiodi@e4sma.com This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 314164.

The InSmart Project: “framework” Outline and definitions The InSmart Project: “framework” Goal of the project: Establish and implement a comprehensive methodology for enhancing sustainable planning (focusing on energy). Framework: Combination of tools, data, expert judgment/preferences, practices, engagement procedures, etc. used for and beyond energy/emission projections and aiming to better support decision makers (for energy planning at city level). The InSmart Project: “tool(s)” - Paradigm of the integrated tool - MCDA

Project details (1) WP1 WP4 WP2 WP3 WP4 WP5 WP6 Work Packages WP1: Development of the city’s GIS platform on energy use and needs Analyse the current status of the cities’ energy strategy and data availability, design and conduct city specific surveys and develop a GIS energy database for each city. WP2: Analysis of the city building stock Provide the necessary techno-economic input for the energy modelling of the building sector in each city. WP3: Transport and mobility analysis Analyse the transport and mobility system of each city, identify possible measures for energy saving and sustainable transport and propose actions for further investigation. WP4: Analysis of the cities’ energy systems and networks Analyse the current status of urban spaces, water/sewage system, waste chain and decentralised energy supply at city level, identify applicable technical solutions and develop the GIS energy database for each city. WP1 WP4 WP2 WP3 WP4 WP5 WP6

Project details (2) WP1 WP4 WP2 WP3 WP4 WP5 WP6 Work Packages WP5: Integrated planning tool for the development of Strategic Sustainable Energy Plans Develop city specific energy system models in order to optimise the system’s path towards sustainability targets identifying the economically optimum mix of the measures. Multi-criteria approach taking into account stakeholders’ and decision makers’ input. WP6: Development of mid-term Implementation Action Plans Analyse further the economics of the mid-term sustainability measures and develop realistic and feasible implementation action plans indicating specific capacity needs at city level. WP1 WP4 WP2 WP3 WP4 WP5 WP6

InSMART partners

Geographical representation Key: identification of the basic geographical entities (zones) representing the most suitable geographical distribution of the information for planning purposes.

Structure and data breakdown Surveys + Calibration to a reference year + simulation of alternative savings options

Structure and data breakdown - Surveys - Analysis of the existing and future private/public demand of transportation (by mode). from zone to zone from/to external areas

Technology explicitness - households Several “services” are demanded by the key agent (responsible of investment decisions) placed in the dwelling (dw).  A budget constraint “per household” can be modelled

Integrated scenario analysis for cities Approach A Reference projection of the city energy system is calculated and then modified through a number of actions, measures, or targets aiming at representing alternative planning hypotheses. Benefits and trade-offs of the tested measures can be seen comparing the key outputs of the scenarios.

Results (examples) …...and many other quantitative indicators (eg costs, emissions, consumption profiles, etc.) to provide more information to the local decision makers !

Sustainable Energy Action Plans Approach The prioritised planning hypotheses identified through the MCDA with the stakeholders’ participation (alternatives, criteria, preferences), are used to formulate the cities’ Sustainable Energy Action Plans. Implementation plans includes the necessary steps, the required resources and the monitoring procedures.

Key elements of novelty Existing SEAP approach   Existing SEAP approach INSMART approach Approach Top-down. Downscaling of national targets, policies and measures. Bottom-up & multi-criteria Driven by urban specific needs. Sectors (coverage) Residential, Commercial, Public Administration (very limited analysis of agriculture and industry). Transport is often not included. Residential, Transport, Public Administration. Emissions (location) Direct (within the urban area) and indirect (e.g. due to the generation of electricity consumed in the urban area). Direct (within the system). All the emissions “directly” generated by the players of the system (e.g. households) are taken into consideration. Emissions (type) CO2, CH4, N2O CO2, particulate Measures Simulation. Cost-benefit analysis of individual stand-alone measures. Optimisation/Simulation (what-if analysis). Integrated system approach. Urban / Energy Urban planning and energy planning are carried out separately. Urban planning and energy planning are carried out together. Representation by “zone”.

Key message The “framework” is a general integrated planning approach that can be applied to a variety of case studies (municipalities), and can use different/other tools, as long as the “principles” of the method are maintained.

More information Project Book Available from: WP deliverables http://www.insmartenergy.com/wp-content/uploads/2014/11/54263_Insmart-brochure_36pp_FINAL_LR.pdf WP deliverables Available from: http://www.insmartenergy.com/work-packages/

”Tools” for policy evaluation Ideal City Planning Platform for the INSMART application Technology explicitness Microeconomic realism Macroeconomic robustness Consumer behavior Regulatory instruments (e.g. in the building sector) Financial incentives (in the building sector, in renewables, …) “Integrated” “Participatory” City Planning Platform ESM Energy System Model MCDA Multiple Criteria Decision Analysis “Essentially, all models are wrong but some are useful” (G. Box)

Energy System Model (ESM) at city level A technology-explicit model of the city is designed to be used as a test-bed for exploring the evolution of energy-environmental variables in the urban area and assess the impacts of different energy strategies. Developed using the TIMES modelling framework Integrated modelling of the entire energy system Cost-optimal technology selection Combines both technical/engineering and economic approaches Explores possible energy futures based on contrasted scenarios Reproduces environmental/financial/policy constraints Links with Transport models & MCDA tools

Energy System Model (ESM) at city level Chains/substitutions/interdependencies

Multiple-criteria decision analysis (MCDA) Analisi multicriteriale The expectation of any decision-maker is to identify the best strategy. There is no “absolute” best alternative (generally), solution depends on individual preferences of each decision maker. The relevant criteria against which decisions are taken, are sometimes conflicting each with other. The objective of MCDA is thus to identify the best “compromise” decisions. MCDA involves the participation of stakeholders to: Identify the relevant criteria Evaluate criteria based on priorities and perceptions

Criteria identification and performance Scenario Unit: TJ Unit: t Unit: kg Unit: kEuro Unit: Mpass-km S1 1,965 273,868 11,296 2,353,204 1,358 1.168 S2 1,809 255,730 10,924 2,471,972 1.123 S3 1,828 272,480 12,324 2,787,580 1.165 S4 1,877 254,160 9,542 2,228,977 1,361 1.151 S5 1,874 305,136 13,055 2,846,468 1.198 S6 1,886 227,719 6,901 2,118,472 1.076 S7 1,838 246,819 9,624 2,381,794 1,673 Quantitative (determined by running the City-ESM) C7 C8 C9 Scenario Qualitative S1 Average Very good Very bad S2 Good S3 S4 Bad S5 S6 S7 Qualitative (determined in collaboration with an independent group of technicians of the municipality and experts) Local stakeholders are called to specify priorities and perceptions between criteria ( “outranking” method).

MCDA: selection of the alternatives Software: Visual Promethee Method: Outranking relation from pairwise comparison of the alternatives  Generation of “flows of preference” Ranking Alternative planning hypotheses Phi Phi+ Phi- 1 S7 0.2871 0.4777 0.1906 2 S2 0.1986 0.381 0.1824 3 S4 0.0455 0.3863 0.3408 4 S3 -0.0338 0.2729 0.3066 5 S6 -0.1552 0.3121 0.4674 6 S5 -0.3421 0.5407 The planning hypotheses which ranked high will form the basis of a deeper explorations and will feed the technical part of Sustainable Energy Action Plan for the city Ranking Alternative planning hypotheses Results / Decisions 1 S7 Shortlisted 2 S2 3 S4 Below the threshold 4 S3 Likely not of interest 5 S6 6 S5 Discarded

Key message Large numbers of “tools” with different approaches and philosophies are available for energy planning. The choice of specific applications shall be always guided by the planning and policy questions that the planner aim to answer to.

More details in the next webinar Join us! October 25th, 2017 (14.00 CET) Webinar on INSMART applications: “Exploring integrated energy action plans for a sustainable transition in the InSmart project: The case of Cesena (Italy), The case of Nottingham (UK), and The case of Évora (Portugal)” Cesena (Italy) Nottingham (U.K.) Évora (Portugal)

Thank you! Rocco De Miglio rocco.demiglio@e4sma.com Alessandro Chiodi Via Livorno 60 – Environment Park Torino, Italy +39 011.225.7351 e4sma.com e4sma@e4sma.com Rocco De Miglio rocco.demiglio@e4sma.com Alessandro Chiodi alessandro.chiodi@e4sma.com Twitter: @E4SMAsrl LinkedIn: E4SMA