Development of Smart Grids Dr. Virginijus Radziukynas

Transcription

1 & Development of Smart Grids Dr. Virginijus Radziukynas Open R&D Lithuania - Efficient Development of the Energy Sector Dec. 19, 2017, Embassy of Lithuania in Ukraine

2 Smart Grid Structure Distributed Generation Smart customers Energy Storage Systems Flexible Electricity Market Monitoring Control Equipment Electric Vehicles New Services and Businesses 2

3 Smart Grid Structure Source: Siemens 3

4 Smart grid standards map International Electrotechnical Commission 4

5 Facing new realities... which result in energy transition (to smart energy) 5

6 New factors coming... The conventional network planning and development is subjected to a number of new uncertainties and push factors TSO DSO consumer empowerment closed distribution system ESCOs energy service companies 6

7 Just a few new names Active customer, prosumer New concepts and definitions Interoperability Demand response Aggregator Local energy community in response to involved in distributed generation and in performing activities of a DSO, supplier or aggregator at local level market signals, including time-variable electricity prices or incentive payments acceptance of the final customer's bid, alone or through aggregation, to sell demand reduction or increase in organised markets 7

8 EU DSO ENTITY (to be established) 8

9 EU DSO Entity: Tasks A lot of tasks is delegated to upcoming EU DSO Entity Development of demand response Participation in the elaboration of network codes Digitalisation of distribution networks including deployment of smart grids and intelligent metering systems Coordinated operation and planning of transmission and distribution networks Integration of renewable energy resources, distributed generation and other resources embedded in the distribution network such as energy storage; Identify best practices in Europe If the subject-matter of the network code is directly related operation of the distrib. system and less relevant for the transm. system, the Commission may require the EU DSO entity (instead of the ENTSO-E) to submit a proposal for a network code to the ACER Work on introduction of energy efficiency improvements in the distribution network. Data management, cyber security and data protection 9

10 Distribution network development plans 10

11 Distribution network development plans DSOs shall develop distribution network development plans USE OF FLEXIBILITY The development of a distribution system shall be based on a transparent network development plan DSO shall submit a PLAN every two years to the regulatory authority PLAN shall contain the planned investments for the next 10 years PLAN shall give particular emphasis on the main distribution infrastructure required in order to connect new generation capacity and new loads including recharging points for electric vehicles Member States may decide not to apply this obligation to integrated undertakings serving less than connected consumers, or serving isolated systems. PLAN shall demonstrate how the alternative to system expansion is used (demand response, energy efficiency, energy storage facilities or other resources) 11

12 Transmission network development plans 12

13 National ten-year network development plans At least every two years TSOs shall submit to the regulatory authority a PLAN HOW TO DRAFT A PLAN? IMPLEMENTATION OF PLAN PLAN shall contain efficient measures in order to guarantee the adequacy of the system and the security of supply PLAN shall contain all the investments already decided and identify new investments which have to be executed in the next 3 years PLAN shall provide for a time frame for all investment projects. TSOr shall make reasonable assumptions about the evolution of the generation, supply, energy storage, consumption and exchanges with other countries TSO shall take into account investment plans for regional and Union-wide networks The regulatory authority shall monitor and evaluate the implementation of the PLAN If TSO does not execute an investment, the regulatory authority is required to take at least one of the following measures to ensure that the investment in question is made to require the TSO to execute the investments in question to organise a tender procedure open to any investors for the investment in question to oblige the TSO to accept a capital increase to finance the necessary investments and allow independent investors to participate in the capital Authority may oblige the TSO to agree to: financing by any third party; construction by any third party 13

14 Union s ten-year network development plans (TYNDP) Agency for the Cooperation of Energy Regulators shall examine national and Union s TYNDPs ENTSO-E ENTSO-E shall adopt and publish a non binding Unionwide TYNDP (every two years) National investment plans Union-wide PLAN shall: build on national investment plans. taking to account regional investment plans identify investment gaps, notably with repect to cross-border capacities ACER opinion ACER shall provide an opinion on Union-wide TYNDP ACER opinion ACER shall provide an opinion on the national TYNDP to assess their consistency with the Union-wide TYNDP 14

15 Network development/planning model 15

16 Relevance of Network Maintenance Information System querry Network planner/ analyser/ consultant N E T W O R K M A I N T E N A N C E I N F O R M A T I O N S Y S T E M Data layer Substations (HV, MV, LV) Equipment groups, key parameters, performance indicators Statistics: outages, repairs, replacements, inspections, costs Examination of querry appropriateness Query layer Rejection of illegible queries Selection of data retrieval algorithms Retrieval of data Selection of data output formats Validatation of prepared data Statistical aggregation of data (if applicable) Data output Įgyvendinimas data Drafting a new method/ procedure/ technique/ model/ algorithm for reliability evaluation for risk assessment for OPEX minimisation for CAPEX minimisation for other purposes 16

17 Development of electric network Risk Investments Risk, (Eur.) Investments, (Eur.) 17

18 Network development framework model Market-based services from third parties Full-scale implementation Development of grid Pilot projects Implementation stage Evaluation studies Network demand assessment Electricity quality estimation Network reliability estimation Estimation of network stability Economical estimation Generation Energy storage New investment project network extension Voltage deviations Harmonics Surges Non-symmetrical loads new connections network rehabilitation Reliability estimation of network elements Ageing estimation of network elements General network reliability assessment network interconnections Dynamic stability Static stability Investments Operation costs Losses consumer empowerment technical upgrade, automation soft projects 18

19 Network development framework model - Universal network development model for infrastructure and soft projects with integrated risk costs for the purposes of TSOs and DSOs C dev = min C ext + C rehab + C conn + C inter + C tech.up + C O&M + C cons.emp + C soft + C PSO + C risk C risk = LOSS x q C ext network extension/new construction cost; C rehab network rehabilitation/renovation cost; C tech.up technological upgrade cost (e.g. automation, smart metering, smart grid, data hubs); C conn network cost for new connection (new grid connection points, new generation facilities, new loads) ; C inter network interconnection cost (DSO-TSO, DSO-DSO, TSO-DSO); C O&M network operation and management cost; C cons.emp. network cost for consumer empowerment (demand response, distributed generation, micro-energy storage, aggregation); C soft network cost for soft projects (e.g. dynamic price cost); C PSO operation cost for public service obligation; C risk risk cost for network and availability; C dev network development cost; LOSS economical loss due to an availability of network services; q probability of network service unavailability. 19

20 Strategic SAIDI and SAIFI planning approach 1. Pressure from business Industry and business are increasingly concerned about higher electricity quality and reliability of supply 3. Added value of better SAIDI and SAIFI Government launches the research study to evaluate the increase of profits from industry and business due to higher reliability of electricity supply within a territory in question 5. Reliability increase strategy Government entitles the Regulating Authority to implement the planned SAIDI and SAIFI values on annual basis in the territories in question 2. Extension of industrial and commercial areas National/regional governements make territorial planning with the view to develop business in specific areas over next 10 years 4. Comparison of added value to increased reliability costs The study finds whether putting in place higher SAIDI and SAIFI is justified by the gains of added value

21 Regulation of reliability indicators in Lithuania National Energy Pricing Commission 5-year regulatory period: Principles from 2018/01/01 New regulatory provisions Momentary Average Interruption Frequency Index ENS, AIT, SAIDI, SAIFI for long unplanned interruptions external events force m a j e u r e Differences between the minimum levels and average actual values are taken to account when setting the new electricity price caps Minumum quality values are set for indicators Average of actual indicator value shall be not below the minimum quality level over regulating period Exceptional events are not taken to account Momentary Interruption : < 3 min Minimum level for restoration of supply in 24 h (% of consumers) : 94.3 % in % in % in % in % in % in 2020 customers of III reliability category Minimum quality level is introduced for MAIFI index: 0.36 times/year for a customer The third and subsequent force majeure events in one year in the same substation shall not be recognised DSO is obligated to pay compensations to customers for infringement of supply restoration time limit of 24 h 15 Eur for infringement as such extra 0.63 Eur for each delayed hour 21

22 Reliability of electric network Reliability, (SAIDI) 1 2 Time, (years) 10 22

23 Unplanned long interruptions including all events (minutes lost per year) Minutes lost per year Austria Belgium Croatia Cyprus Czech Republic Denmark Estonia Finland France Germany Great Britain Greece Hungary Ireland Italy Latvia Lithuania Luxembourg Malta The Netherlands Norway Poland Portugal Romania Slovak Republic Slovenia Spain Sweden Switzerland 23

24 Structure of self healing networks BUS A a a4 1 1 a1 a3 a5 a7 a9 b6 b4 R1 R1 R2 R2 R6 R4 R4 R3 R c8 a a41 a81 R c a22 a42 a c c a43 a c c26 c c c23 c24 10 R5 250 c3 360 optimal placement of reclosers 20 R5 c reason-based placement of reclosers 300 c2 c21 c22 42 I, П, T, H a a dx 370 c BUS C b b b3 1.5 b31 b b b1 DMS BUS B 24

25 Network reinforcement case study: Moletai substation (10 kv) COST [NCU] dsaidi [%] Total number of customers Pre-defined branches for network reinforcement 59, total length 55.2 km number of combinatorial sets of reinforcement measures (for brute-force method) Optimally selected branches 20, total length 19.6 km no combinatorial problems, cumulation of SAIDI gains from most effective branches 25

26 Analysis and assessment of electric power systems reliability Estimation reliability of substation Events tree analysis Monte Carlo method Markov chain method Stochastic Automata Networks method L 1 L 2 L 3 π π π 0 1 A μ μ 2 T 0 ( 1) I 1 n2 ( 1) In 2 ( 1) ( 1) In λ I 1 2 n 1 n 1 2 λ A = 0 1, n2 n1 1 ( 1) 1, n2 μ I n 1 n 0 A 2 n T B 1 S 1 C 1 S 2 S 3 C 2 S 7 S 10 C 4 S 11 S 12 C 5 S 16 C 7 S 18 S 19 C 8 S 17 S 23 Q = ( 1) ( 2) ( Q Q ) I + I d ( 3) ( 3) Λ ( 3) ( 3) A μ = μ ( 1 ) μ I 0 ( 1) I 1 n ( 1) I n 2 ( 1) ( 1) ( 1) I n λ I n λ 1 ( 3) Q 0 n1 * 0 + ( ). 3 0n 1, n I n n 1 Q n n n Μ D n1 1 n2 λ 1 A n1 1 n2 A 0 I n1 1 S 4 S 5 C 3 S 6 B 2 S 8 S 9 S 13 S 14 C 6 S 15 T 1 T 2 S 20 S 21 C 9 S 22 T 3 S 24

27 Mathematical modelling of electric power systems, analysis and estimation of parameters Software: PSS Sincal PSSE PowerWorld Matlab MESSAGE BALMOREL GAMS ir IBM ILOG CPLEX TIMES Decision Tools Suite

28 Mathematical modelling of electric power systems

29 Analysis and assessment of electric power systems reliability Network reliability methodology set-up (when fault occurs in several different places of PS) Heuristic/deterministic estimation and outline of power system heavy operation scenarios (multi-emergency situation) Analysis of steady-state operation Assessment of research results and ranking of power system modes by hardness Selection of variants and analysis of transient PS modes Assessment of research results and ranking by hardness Reliability calculation after evaluation of results for transient PS modes analysis Selection of data And their statistical analysis Drafting the network reliability methodology using probabilistic mathematical model (when fault occurs in one place of PS, e.g. in transformer substation) Selection of network failure variants (transformers, substations, power lines) and reliability calculations Assessment of results for network reliability calculation and selection of variants for evaluation of steady-state power system modes Analysis of PS steady-state operation Assessment of research results of PS steadystate operation and ranking by hardness of power system modes Selection of variants and analysis of transient PS modes Creation of methodology for ranking Set-up of methodology for power system modes analysis (steady-state and transient processes) Assessment of research results of PS transient operation and ranking by hardness of power system modes Evaluation of overall relia-bility of network. Building network reliability dependence on network loading Evaluation of possible risk/loss basing on system operation analysis Selection of optimal measures for power system risk reduction Assessment of research results, conclusions and recommendations Development of network reliability methodology. Giving the overall network reliability and reliabilitynetwork loading characteristics Drafting the methodology for power system risk assessment Drafting the methodology by optimal measures for power system risk reduction 29

30 Advanced cost-benefit analysis 30

31 Comprehensive Cost/Benefit Analysis (CBA) for modern networks EVALUATION OF ECONOMIC BENEFITS EVALUATION OF NON-MONETARY BENEFITS Define boundary conditions and set parameters Perform monetary analysis with economic benefits Evaluation of non-monetary benefits Perform sensitivity analysis WITHOUT non-monetary benefits WITH non-monetary benefits Sum up CBA results, specify the limits of the parameters corresponding to the positive result Sum up CBA results, specify the limits of the parameters corresponding to the positive result 31

32 Economic CBA: Steps Determine the scope of the project, objectives, technological solutions Assumptions outlined Determine the number of users, estimate energy consumption Smart grid services provided Defining the objectives of the project 2 Identify smart grids features that will be created by the project's technological solutions Smart grid technology solutions are reviewed according to a typical function list Technological solutions Determine benefits that smart grid functions will create 3 Functionality Functionality Create a basic scenario for comparison with a smart grid project 4 Benefits function 7 function 15 function 19 Smart grid functions are reviewed according to a typical benefits list device A1 technology B5 Basic scenario - network development / use without smart technology project algorithm C2 32

33 Economic CBA: Steps Evaluate monetary benefits, identify beneficiaries The benefits must be significant, clear Quantify project costs Measured quantitatively Expressed in cash Estimate the uncertainty of benefit (±20%, ±40%, ±100%) For each benefit identifies its beneficiaries and the benefits to them 6 Costs must be based on market research The mass implementation project includes the cost of the pilot project Estimate the uncertainty of cost (±20%, ±40%) 7 Compare costs and benefits Compares the usefulness of the basic scenario and the smart grid project by year and over the entire period NPV (Net Present Value) IRR (Internal Rate of Return) Benefit-to-cost ratio 33

34 Additional CBA: Steps Sensitivity analysis Their changes affect the profitability of the project The critical project parameters are determined according to the standard list Critical Parameter The growth rate of energy consumption, % Peak reduction, % Smaller losses in TSO/DSO networks, % Duration of interruptions, min Damage to the user Discount rate Benefit 12. Lower electrical losses Higher power savings? 13. Lower electricity costs 6. The expansion of the distribution network is delayed 12. Lower electrical losses 17. Lower duration of interruption (more electricity sold) 17. Lower duration of interruption (less damage to the user) 9 Non-monetary benefits (internal, external) analysis Final decision on the usefulness of the project 10 Project implementation schedule } Project NPV (Net Present Value) NPV, IRR IRR (Internal Rate of Return) 34

35 List of typical monetary benefits 22. Less blackouts 21. Lower consumption of petroleum products (electric vehicle!) C=C base -C SG 17. Less short term interruptions 28 formulas are submitted to calculate the benefits 20. Less SO X, NO X and particulate emissions 18. Lower voltage deviations / distortions 19. Less CO 2 emissions 35

36 Example: Smart Network Services A-F and Typical Functions (1-33) The ability of the network to integrate users with the new requirements A Functions Make it easy to connect any type of electrical device to any location on all voltage steps B Increase efficiency in network day mode Functions Identification of technical and non-technical losses through the analysis of flows Network security, system management and quality assurance of supply C Functions System security evaluation and network repair management Promoting stronger direct users inclusion in their energy consumption and management F Functions Remote control of meters E Improving market performance and customer service Functions The participation of virtual power plants and aggregators in the electricity market Better future investment planning for the network D Functions Improvement of asset management and replacement strategies 36

37 Internal non-monetary benefits I-XI and key influence indicators (1-54) I II III IV Greater sustainability Indicators quantified reduction of carbon emission Adequate network capability for receiving and transmission of electricity to consumers Indicators Distribution network transfer capability for distributed generation Good connectivity and network access for all users Indicators User connection time Sufficient safety of power system/networks and highquality electrical supply Indicators Power system stability V VI VII VIII Greater efficiency in network and power supply Indicators Average load capacity of network devices, % To improve the cross-border electricity market by better distributing power flows in order to reduce loop flows Indicators Ratio of inter-system transfer capability and the load of the whole system Optimize the transmission network infrastructure by better coordinating the development of networks through the principle of joint planning "European, regional and local levels" Indicators Increased consumer awareness and emergence of new entrants in the electricity market Indicators The number of users who have chosen special tariffs IX X XI Increased consumer exposure to choices that are in line with EU energy efficiency goals Indicators Creates the dependence of consumer behavior on energy prices Developing a market mechanism for new energy services (eg. energy efficiency improvement, advisory activities) Indicators Clearly regulated data ownership issues and processes for managing them, enabling service providers to function effectively Reducing consumer bills for electricity, avoiding their growth Indicators A regulatory mechanism that benefits from smart grids deployments reduces user accounts 37

38 External non-monetary benefits For national security Public acceptance For economic growth Workplaces Public favour contributes to the success of the project Consumer time expenditures whether the time will be saved? Privacy and Cyber Security For public health lost / new - in the project implementing company new - project contractors For environmental quality possible new ones - for manufacturers and suppliers of electrical and communication equipment - for aggregators - for new industry players (RES power plants, electric cars production) Physical safety what impact does it have on consumer data protection and cyber security? will you need funds for prevention? Social impacts Environmental impact noise landscape to evaluate new sources of danger or risk reduction 38

39 Example of CBA graphical results of new services Service Cost F F Service Cost A A Service Cost B B Service Cost EE Service Cost C C Service Cost D Benefit X Benefit IX Benefit XI Benefit I Benefit II Benefit III Benefit IV Benefit VIII Benefit V Benefit VII Benefit VI 39

40 Optimal integration of future technologies into energy sector Local resources Country Local resources Energy sector Oil, gas, other fuel, electricity (smart grids), district heating and other sectors Goods, Services, Cost Branches of economy Industry, Construction, Transport, Agriculture, Commerce and services, Household Max GDP Import/ export Import/ export Block-scheme of mathematical model for analysis of optimal integration of future technologies into energy sector 40

41 Thank you for your attention! Presenter: Dr. Virginijus Radziukynas System control and automation laboratory Lithuanian Energy Institute Phone number: Questions? 41