Merit order is a ranking system used to determine the order in which different sources of electricity should be used to meet demand. It is based on the marginal cost of each source, with the lowest cost sources being used first. This system optimizes the use of different power plants and resources, such as renewable energy, to meet power grid needs in a cost-effective way.
On the electricity exchange, supply and demand determine auction prices. The 'market-clearing price' is the lowest bid accepted in an auction to buy power. The power plant with the highest marginal costs – the marginal power plant – determines the exchange price for all power plants involved. This price formation mechanism is known as 'uniform pricing' in the energy industry because all power plants receive the same price for their feed-in, even if they offered different prices.
The effect of renewable energy on merit order
The high demand for power during peak hours drives up the price of electricity and, as a result, 'peak power plants' install generators that charge a premium for their energy.
Because wind and solar energy have such low marginal costs, larger amounts of renewable energy tend to decrease the average cost per unit of power. Wind and solar energy have very low marginal costs: they do not need to pay for fuel, and the only contributors to their marginal cost are operations and maintenance. Solar and wind power are less expensive on the spot market than coal or natural gas because of the feed-in-tariff income they generate, which means their electricity is typically less expensive there. Transmission companies purchase from them first since solar and wind energy reduce the amount of high-priced peak electricity that they must buy, lowering their overall cost.
In a competitive open electricity market system, however, wind and solar energy's zero marginal cost does not translate to a zero marginal cost of peak load power. Merit order was intended to allow the cheapest net cost electricity to be dispatched first, cutting consumer costs. Intermittent wind and solar are occasionally able to perform this cost-cutting role. The price reduction is greater if the supply peak (or solar) and demand peaks occur at the same time and in equal amounts. Solar energy, by contrast, is most abundant during midday, whereas peak demand occurs late afternoon in warm climates, resulting in what's called the duck curve.
The duck curve pictured above is what happens when solar power starts to become a large percentage of the energy mix and the demand for energy from the net demand is reduced during midday. This is especially true in moderate climates in spring and fall where it can be sunny during the day, but electricity is not needed for heating or cooling. As solar production starts to wane, the production of electricity needs to increase as people are returning home, and the evening peak begins. The issue is that there is a wider and wider difference in the demand for energy between midday and the evening peak, which needs to be compensated by traditional, dispatchable generation. This can be solved by improving energy storage or improving how energy sources are aggregated together such as via a virtual power plant.
The objective of economic dispatch is to automatically select the maximum output of a number of power generation plants at the lowest possible cost, taking into account transmission and operational restrictions, in order to meet the system load. The Economic Dispatch Problem is solved via specialized computer software such as a virtual power plant that must satisfy operational and system requirements for available resources and transmission capabilities.
In order to minimize total cost at a minimum, the set of generators with the lowest marginal costs should be utilized first, with the final generator's marginal cost being used to establish system marginal cost. This is the cost of generating one additional MWh of power. This price may differ based on grid limitations at various locations within the electric network - these "local marginal prices" are known as historic economic dispatch techniques that were developed to manage fossil fuel power plants, relying on calculations involving input/output characteristics of power stations.