Introduction
The main premise behind BSAM is that the dynamics in a given market are driven mainly by the choices of the micro-level actors involved. An actor represents a group of relatively homogeneous stakeholders, where homogeneity implies that the actors in the identified group have common interests and a common set of options at their disposal.
In BSAM, actor behaviour is treated as evaluation and ranking of different available options for energy generation; some options may correspond to specific technologies, and others to ways in which these technologies are used (e.g., bidding behaviour in the wholesale electricity market).
The BSAM modelling framework requires the following steps:
- Identification of the alternative energy generation options
- Identification of the attributes of the options that affect the value that actors attribute to these options
- Modelling of the decision rules according to which actors choose to adopt or use these options
The added value from this modelling approach is that it supports a specific way of evaluating energy policies. A policy is effective in promoting certain energy generation or efficiency options if it is able to affect their perceived value. Affecting the perceived value can take place either by affecting the respective attributes of the options or by changing the decision rules of the actors.
What does the model do?
The BSAM model is a power sector model, focusing on the expected behaviour of power generators. It can model case study variations of the energy and climate framework on a national level and, in particular, the financial and operational behaviour of privately-owned power generation units in a deregulated electricity market. The model explores the economic viability of the units through the computation of their total profits under different market scenarios. The following table outlines the policy analysis that can be carried out by BSAM.
Policy Framework |
Policy analysis (Policy scenarios) |
Energy & Climate |
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The BSAM approach for scenario development is guided by the expected behaviour of the actors that are involved in the modelled system (here a national power market). In particular, scenario development for BSAM is based on the notion of focusing on the actor-contingent elements, i.e. the developments which are within the power of system actors to change or bring about, if they choose so. As a result, the scenario development begins with the identification of the actors that are affected by the policy instruments under study or the behaviour of whom may support or impair the instruments’ effectiveness. The factors and events that are most influential on the actors’ decision making process and criteria are in fact the ones with the greatest influence on the evolution of a policy instrument’s impact through time. Thus, these factors and events define the parameters that should constitute the scenarios utilised for the policy instrument’s assessment.
What kind of questions can the model address?
Questions related to the centralised energy system:
- How can energy policy facilitate investments into cleaner technologies by influencing their value as perceived by the potential investors?
- How can energy policy incentivise energy producers into engaging in “learning by investment” projects?
- How does the impact of a policy instrument differentiate between dominant market players with existing energy portfolio investments and new entering power producers? How is the instrument expected to affect the evolution of the market?
Questions related to the decentralized energy system:
- How can we influence the adoption of technology options by consumers: value of bundled options, information diffusion, sharing infrastructure and local markets?
- What are the interactions between decentralized energy generation and the wholesale electricity market (BSAM already includes a model for simulating the operation of the Greek wholesale electricity market)?
What kind of answers can the model provide?
The model can generate plausible transition pathways in the energy sector by simulating:
- The effect of, and the drivers for, phasing out different technology options
- The competition between different emerging technology options for market share
- The conditions that affect the technology adoption decisions of the involved actors
- The conditions under which conflicts or collaboration opportunities between the involved actors may take place