To trade or not to trade
What is the impact of the regulatory framework for transmission investments on the cost of renewable energy in the EU? Under the current regulatory framework transmission investment planning is mainly done at a national level. This may result in suboptimal transmission investments, i.e. maximising national rather than European welfare, as cross-border projects initiated by one member can be vetoed or delayed by the other member states involved. However, investments in transmission infrastructure are important to enable cross-border renewable energy trade. Why? Because such trade would help reduce the costs of achieving the national targets for renewable energy. So, the question is whether the current imperfect regulatory framework is actually a problem?
To answer that question, Vlerick professor Leonardo Meeus and Marcelo Saguan, consultant at Microeconomixs, developed a novel competitive equilibrium model* that determined the ‘optimum’ transmission capacity for different scenarios, calculating the impact of the imperfect regulatory framework on the cost of renewable energy in each of the scenarios. The results were detailed in a research paper published in the Elsevier Journal Energy Economics.
Four states of the world
The equilibrium model considered four ‘states of the world’, or scenarios, defined by the combination of renewable energy trade and transmission investment planning:
(1) no trade and national planning,
(2) perfect trade and national planning,
(3) no trade and international planning,
(4) perfect trade and international planning.
Note that scenario (1), no renewable energy trade and national transmission investment planning, corresponds to the current situation in the EU.
These four states or scenarios were each modelled as a three-stage decision process:
(1) decide on the transmission capacity,
(2) decide on electricity generation investments, assuming a mix of conventional and renewable technologies and
(3) decide on production and consumption schedules (supply and demand).
The outcome of each stage set the constraints for the next: in the third stage consumption and production decisions were made for a given electricity generation capacity, which in turn had been decided by the electricity generators taking into account the transmission capacity of the interconnector.
Two zones and three cases
The model was applied to a small, but realistic, power system consisting of two interconnected zones regulated by different national authorities, each zone being managed by its own transmission system operator (TSO), with the TSOs jointly deciding on the transmission capacity of the interconnector. The model assumed that the electricity demand, access to conventional energy resources, transmission costs and renewable energy targets were the same for both zones; only their access to renewable energy resources being different.
To analyse the sensitivity of the results (the cost of renewable energy at equilibrium) to the difference between the two zones in terms of their access to renewable energy resources, three cases were considered in each of the scenarios:
(1) in both zones renewable energy availability and demand were not correlated and the investment costs and average availability of renewable energy resources were different in each zone,
(2) investment costs and average availability of renewable energy resources were the same in each zone, but in zone 1 renewable energy availability and demand were positively correlated while in zone 2 they were negatively correlated,
(3) investment costs and average availability of renewable energy resources were different in each zone and in zone 1 renewable energy availability and demand were positively correlated while they were negatively correlated in zone 2.
Note that while case (3) is the closest to reality, cases (1) and (2) made it possible to analyse which differences have the biggest impact.
Transmission capacity at equilibrium was determined for 36 simulations (4 scenarios x 3 cases x 3 renewable energy targets of 30%, 40% and 50% respectively). In the scenarios with international transmission investment planning the transmission capacity at equilibrium maximised the total welfare of the two zones. In those with national transmission investment planning, the ‘optimum’ transmission capacity for each zone was determined by maximising local welfare while the transmission capacity at equilibrium was determined by the lower of the two optimum investment decisions.
From the simulations the following conclusions could be drawn:
- National transmission investment planning results in suboptimal transmission investments, which has a negative impact on the cost of renewable energy.
- The negative impact of national transmission investment planning and suboptimal transmission investments on the cost of renewable energy is significant but case specific, with cost increases of 1% up to 89%, depending on the renewable energy target as well as the access to renewable energy resources.
- The negative impact of national transmission investment planning and suboptimal transmission investments on the cost of renewable energy is more significant when there is renewable energy trade.
- The effects of renewable energy trade are of a different order of magnitude than the effects of transmission investment planning. The renewable energy cost increase due to the lack of renewable energy trade ranges from 36% to 887%.
- The costs of renewable energy are the highest when transmission investment planning is organised on a national level and in the absence of renewable energy trade.
The simulations show that the costs of renewable energy are the highest in the scenario corresponding to the current situation in the EU.
The potential benefits of renewable energy trade, however, are known and therefore some member states have already started trading despite the fact that, under the current regulatory framework, transmission investment planning is a national issue. While the simulations indicate that trading amplifies the negative impact of such an imperfect regulatory framework on the cost of renewable energy, the simulations also show that the positive effect of renewable energy trade outweighs the negative effect of suboptimal transmission investments resulting from national transmission investment planning.
In summary: the imperfect regulatory framework for transmission investments has a negative impact on the cost for renewable energy in the EU, but it should not stop member states from already trading renewable energy to help reduce that cost.
What is a competitive equilibrium model?
In a competitive equilibrium model the interaction of profit-maximizing producers and utility-maximizing consumers in competitive markets with freely determined prices will give rise to an equilibrium price. At this equilibrium price, the quantity supplied is equal to the quantity demanded. The presence of a surplus or a shortage causes the market price to adjust towards equilibrium.
Source: The full paper ‘Impact of the Regulatory Framework for Transmission Investments on the Cost of Renewable Energy in the EU’ was published in Energy Economics Volume 43, May 2014, Pages 185–194. The post-script version is freely available. Readers will find valuable background information and details on the various parameters used as well as a comprehensive overview of the equations describing the optimality conditions at the different stages. The paper also includes a detailed discussion of one specific simulation, explaining how the model exactly works by illustrating the impact of transmission investment decisions on total and zonal welfare, electricity market price and renewable energy premium price, electricity generation investments, renewable energy subsidy and different welfare components (i.e. consumer surplus, congestion revenue and transmission cost).
About the authors
Leonardo Meeus is Associate Professor of Energy Markets at Vlerick and Director of the Energy Centre. He is also a part-time professor of the Florence School of Regulation and a visiting professor of the KU Leuven. Marcelo Saguan is a senior consultant in economics and leads the Energy & Climate Practice at Microeconomix. He is also an engineering adviser at the Florence School of Regulation for the Loyola de Palacio Energy Policy Programme.