 Hallo, mijn naam is Will Tissen. Welkom terug op de tweede deel van deze tutorial op gebruik van systeemanalysen voor problemenstructuur. In deze video zal ik de begrijpteleerde begrijpteleerde punt, uitleggen hoe om en gebruik systeemanalysen in de multieactorsituatie te gebruiken en illustreren deze met de windpowerxample, zoals in de eerste video's. In de eerste video's heb ik gekeken hoe systeemanalysen helpen om je een problemenstructuur te gebruiken van de perspectief van een unieacteur. Je begint van de criteria en gebruikt de kaasanalysen om de systeemfactoren, meenemen en extreemfactoren te ontdekken. Je itereren en checken voor consistentie en analyseren de resultaten met een systeemdiagram en een scorecard. Maar wanneer de multieactoren ingevolgd zijn, waardoor je analyseren aan de monoacteur-perspectief is insufficient. Sommige actoren worden effectueerd door acties geïnteresseerd door de problemenstructuur en verantwoorden hij of haar planen. Andere actoren possessen betekent dat het nodig is om de problemenstructuur te bekijken. En deze andere actoren hebben enthousieel verschillende gole en problemenperceptions. Je moet de percepciënten van deze andere actoren ontdekken, betekenen hun interesse en percepciënten, en ontdekken of deze andere actoren de problemenstructuur zijn gole of niet. En waarom? Systeemanalysen helpen je te identificeren dat de andere actoren hun problemenperception, analyseren dependencies en identiferen strategies voor meer actie en research. Ik suggesteer de volgende generale steppen. Eerst starten we van de monoacteur-systeemdiagram en ontdekken wat relevanten factoren zijn geïnteresseerd door andere actoren en wie deze andere actoren zijn. De tweede, identiferen wat andere actoren zijn geïnteresseerd door veranderingen in systeemfactoren. Deze twee steppen geven de begrijping voor de derde steppe, een meer extensieve actorenanalysie. De actorenanalysie helpen je te ontdekken wie de actoren zijn geïnteresseerd. Deze die de problemenvereniging niet kunnen ignoreren. Bekijk een separate tutorial op actorenanalysie om meer te leren over deze. En de vierde steppen bestrijden een systeemanalysie voor iedere actoren. Focussie je attentie op die manieren en objecties van de actoren die met interesse zijn of anders is het relevant voor je problemenvereniging. En dan uitstek je originele monoactorensysteemdiagram door de relevante criteria en meenemen van de kritische actoren te ontdekken. En weer, zoals vooral, na iedere modificatie van je systeemanalysie moet je itereren en checken voor consistentie. Wilt je ontdekken en de extende systeemanalysie voelen, bekijk voor relevante geïnteresse en conclusies. Doen andere actoren de gole in het verhaal met je problemenvereniging? Is er een directe waalkonflict? We hebben een waalkonflict, is één actoren exact dezelfde van een andere actoren. Bijvoorbeeld, na een drijspel, farmers willen regenen wanneer de toeristen continu te prefereren drij en zonneweer. Ook analyseer ik wat ik probleemde cross-impacten, de impacten van de preferende actoren van één actoren op de criteria die een ander actoren verwelden. Als deze impacten positief geweldig zijn, zijn de twee actoren potentieel ellen. Als de impacten negatief geweldig zijn, hebben de actoren betreffen interesse en alternatieve manieren zijn nodig om de oppositie te brengen. Zoals de inside, helpen de potentieel voor de arrangements tussen actoren te identificeren. En finally, in much the same way as in the mono-actor case, the systems analysis helps you identify knowledge gaps that can guide the direction of further research. Let us now look at our wind power example again. Our problem owner is the Department of Energy. It wants to enlarge the percentage of offshore power generation while not endangering security of supply and while keeping power costs at acceptable levels. Remember the system diagram for the mono-actor perspective explained in the first tutorial on systems analysis. Using this diagram, our first question is, what factors may be influenced by other actors and who are these actors? Let's start at the right-hand side of the diagram. We first note that TENET, the distribution network company, can build new international connections. TENET also manages the operational balance of power supply and demand. The European Union stimulates the international connectivity of the power networks. R&D companies explore and develop new technologies and these may lead to influential breakthroughs in available storage capacity as is also concluded in the tutorial on exploring the future. Energy companies may invest in wind farms and thereby influence their number and size. The Ministry of Infrastructure and Environment is a competent authority for management of the North Sea. It has an important say over where the construction of wind farms is permitted. After the identification of actors who may influence the system, we now turn to looking for actors that may be influenced by changes in the system. Again, going from right to left, the interests of TENET will be affected by changes in the supply-demand balance of power on the network. Other uses of the North Sea, such as shipping and oil companies, may feel the installation of new wind farms at sea will interfere with or limit their own business activities. Investors will have an interest in the availability of subsidies as will energy companies and R&D companies. TENET's business will be affected by energy transport costs. Energy companies will be affected by the costs of energy provision. Finally, the Ministry of Infrastructure and Environment is concerned about an efficient and sustainable use of the space at sea en this may be affected by installing wind farms. This example shows how a system diagram can assist you in identifying who the relevant other actors may be. That provides one of the stepping stones for a more extensive actor analysis. The actor network analysis helps you identify what actors the problem owner cannot ignore, the so-called critical actors. Als je de tutorial op actorenalysis hebt, kan je de volgende tabelen van het actoren rememberen. Actoren met hoge interesse en hoge kracht zijn listeerd in de top-right-hand-corner. Actorenanalysisen zijn de vijf actoren die langs de analis in de analis zijn. Ik illustreer nu de volgende stappen in het volgen van de monoactorsystemsanalysis op de multieactorsituatie maar ik voel me op twee van de kritische actoren de ministerie van Infrastructuur, de environment en de energiacompany. Eerst gaan we terug naar het monoactor diagram voor de perspectief van de departement van energie. Expanding het in deze vorm met criteria, meens en extra factoren voor de andere actoren maakt de grafis te groter. Dus heb ik geïnteresseerd om de originele diagram een beetje te simpliferen. Ik geaggrateerde wat van de factoren zoals de nummer en de zijkant van de windfarm. Ik heb ook een aantal van de intermediate factoren en de minder essentieel effecten van de scaleadvantages. De essentieel relatie blijven, maar. Om de effecten van de locatioontwikkeling op capaciteit te emphaseren heb ik de factoren overigens de windspeed op de locatie gevoel. Ik heb ook geïnteresseerd dat de departement van energie de eigenaar van de criteria en van de betekenis is om de letter D.E. aan te adden op die factoren en betekenis respectief. Laten we beginnen met de ministerie van Infrastructure en Environment als extra actoren. Ze zijn verantwoordelijk, geïnteresseerd, efficiënt en sustainabel gebruik van de Noord-T en voor de veiligheid van de zee. En moeten we met een variety van gebruikers die vervangen voor spas. Bijvoorbeeld windfarm, geïnteresseerd, olieexploratie en natuurpresentatie. Gelderlijk, niet alle van deze gebruikers bevinden op een en dezelfde plaats en de veiligheid kan worden geïnteresseerd. We gaan nu terug naar de systeemdiagram en gebruiken een blauwe kool voor de ministerie van Infrastructure en Environment en add de twee relevante prime criteria voor de Noord-T naar de diagram. Efficiëntie van spasuse en veiligheid van de zee. Installing windfarms kan de efficiëntie van de zee contributeren maar minder spas zal blijven voor andere gebruikers mogelijk ook veiligheid van de zee effecteren. Het lijkt op de ministerie van Infrastructure en Environment is de prime responsieve agentie voor de aandrijving voor windenergie van de zee en we veranderen de originele diagram door de originele aandrijving veranderen van de zee voor de aandrijving voor de aandrijving en de aandrijving voor de ministerie. We leren ook dat het licentieproces de aandrijving van de ministerie van Infrastructure en Environment en de ministerie van Infrastructure en Environment en we kunnen het doen met een bluwe en witte schading. Om de distinctionskleed te houden, gebruiken we de initiaties INE om de criteria en de betere van de ministerie van Infrastructure en Environment te ontdekken. Besef deze diagram kunnen we nu de volgende schoekhard ontbouwen. Door de originele schoekhard voor de monoactieve perspectief de twee criteria van de ministerie van INE zijn bezocht. A green color indicates that the impact on the criteria is considered desirable. A red color indicates that the impact is undesirable. And gray indicates that the impact seems to be neutral or is unknown. For example, if you go back to the diagram you will see that there are both positive as well as negative impacts in the causal chain between the various means on the one hand and efficiency of space use on the other. Therefore, the impacts on efficiency of space use are labeled as uncertain. The impacts of installing wind farms on safety at sea are negative according to the system diagram but I note that the extent to which this is the case may strongly depend on the choice of location. What can we now learn from this analysis? First, there are no direct value conflicts. The Ministry of Infrastructure and Environment is interested in other things than the Department of Energy. However, using space for wind farms may negatively affect safety at sea. And the impacts of adding wind farms on efficiency of space use are uncertain and depend on opportunities for other uses, location and perhaps other factors. Therefore, while the interests of the ministry of infrastructure and environment are not directly conflicting with those of the Department of Energy it will not be a natural alley either. Let us now turn to a second critical actor, the energy companies, and perform a similar system analysis. Again, we go back to the original diagram in simplified form. The energy companies have two main objectives. Security of supply and an attractive return on investment. We add return on investment as a criterion and choose an orange color to distinguish it from the criteria of the other actors. And also use the label EC to indicate that these criteria belong to the energy companies. Security of supply is a criterion for both the Department of Energy and the energy companies and therefore we shade it orange and gray. Working backwards from the criteria again, return on investments is determined by the revenues and costs. Revenues from wind farms in turn are determined by installed capacity and by the prices received per kilowatt hour. This signals the need for a new external factor. Market prices for electricity depend on costs of alternative energy sources and are generally outside the control of the actors concerned. Energy companies are prime decision makers regarding the number and size of new wind farms, so we add their investment decisions as a means to the diagram. Now again, we can derive the following scorecard. Focusing on the criterion return on investment for the energy companies, we see that the means of both the ministry of infrastructure and environment and the Department of Energy contribute positively. The eventual impact of energy company investments will however partly depend on an external factor and hence be uncertain. Investments of energy companies in offshore wind farms will have a positive effect on the percentage of offshore power and a negative effect on security of supply on the cost of energy provision. What can we conclude from this particular scorecard? First, energy companies share some of the goals and the same dilemma as our problem owner. There is no direct conflict as both value security of supply in the same way. Second, energy companies have a strong interest in close to coast locations to keep the costs of investment and transport within bounds. Most actions of the Department of Energy will also benefit the energy companies. They are therefore potential alleys for the department. But the return on investment for the energy companies also depends on other factors, notably the market prices for energy which are outside the control of any of the actors considered. As a next step, we combine the analyses for the two critical actors. The following integrated diagram results. It includes all the relevant criteria and means of both the problem owner and the two critical actors in a single diagram. The coloring enables us to keep the distinction between the criteria and the means of the different actors. The corresponding scorecard now includes all the means and criteria of the three actors considered. Nieuwe elements in this scorecard are the cross-impacts of energy company investments on efficiency of space use and safety at sea. These are uncertain and negative, respectively. So, again, what overall conclusions can we draw based on this extended systems analysis? Well, first, there do not seem to be immediate conflicts between our problem owner en the two critical actors considered. Second, support by the Ministry of Infrastructure and Environment is crucial. Energy companies will prefer near-cost locations, but these are not necessarily preferred by the ministry. For the ministry, such locations may be acceptable only if interference with other desirable uses of the space at sea is minimal. Third, as also concluded in the tutorial on exploration of the future for the same example, important external factors, notably market prices for electricity, will determine the attractiveness for energy companies to invest. Fourth, concerns about security of supply remain. They may be alleviated if more international connections will be realized and if new ways of large-scale power storage would become available in the future. But this also is highly uncertain. Other actors, such as Tenet and the European Union, may be of assistance in this respect. And of course, according to the findings of the actor analysis, we should extend the analysis to include other critical actors, notably Tenet and the shipping companies. I conclude the discussion of the example by identifying knowledge gaps that should be investigated further in light of our analysis. As indicated above, it is important to search for attractive locations where wind farms can be built without interfering with other usage functions and without endangering safety at sea. Investment decisions by energy companies are critical and therefore further research into the factors determining their return on investment is also indicated. The first end will subsidies work. What is the influence of location choice on benefits and costs? What risks do energy companies face in light of uncertain energy markets? Of course, further research into the security of supply and how and what costs it may be guaranteed when a larger fraction of power is generated at sea should also be on our list. I conclude this tutorial with a number of more general remarks and suggestions. First, if you've been watching the development of the example attentively, you may have noted slight modifications and inconsistencies on the way. This illustrates the fact that there is not a single best system model. You will need to adapt as you proceed and learn more and more about the problem situation. As more actors are included, complexity of the model will generally rise. For example, if we also include tenet and the shipping companies in the integrated systems analysis, their criteria and means are added and system boundaries may shift. For complicated cases and more advanced analyses, we suggest the use of dynamic actor network analysis or DANA. It is a package of software that was especially designed for applying systems analysis concepts in multi-actor settings and you may find the software instructions on the blackboard page for this course. Second, at a more general level, we have developed separate tutorials on actor analysis and systems analysis. However, as we have seen, the two approaches are not independent of each other. On the one hand, systems analysis provides starting points for actor analysis. On the other, actor analysis provides insights into who the critical actors are and into their positions. In turn, systems analysis helps to sharpen the insights in the mechanisms at play and to specify the dependencies between the critical actors. Iteration between systems analysis, actor analysis and exploration of the future is key to an effective approach. Together, these methods will help you in providing the building blocks for your storyline and your research plan. Thank you for your attention.