Design and modeling of a local energy market

The possibility withmicro grids, smart energy buildings, customers with photovoltaic, storage or demand flexibility enables new opportunities for the energy system. This thesis is done in collaboration with an on-going-EU-funded project - Fossil- Free Energy District (FED), where Chalmers is one of the partners. The project aims to design and model a local energy market to establish what financial and energy gain there might be. This thesis sets out to design a local energy market, implement it in a computational model and simulate how this behaves during different scenarios. A model for a local energymarket has therefore been developed. The designed model is based on theory from energy markets as well as previous attempts to design a local energy market. The designed market has the possibility to trade both energy and reserve energy. The reason for this is to have the possibility to handle the inevitable demand and supply commitment errors made on the market ahead of delivery. The reserve market then balances the local energy market to deal with this issue. The model has then been implemented in GAMS with the purpose to simulate how the market would behave in different scenarios. The result from the computational model showed how the market players is able to trade both energy and reserve energy. The increase in energy equipment did not give a noticeable difference in energy traded but a major increase in reserve energy. The amount of energy traded was about 10% of the total demand in the local energy market throughout all scenarios. The market was therefor highly dependent on the grid to provide the rest. The amount of reserve energy provided was increased with about 45% if comparing the scenario with the least amount of energy equipment installation compared with the one with the most. The results illustrated how forecast errors, both regarding production and consumption, could use the reserves to balance their needs. The model results also showcase the problems, mainly with the price relations, occurring when it is integrated with other energy market such as Nordpool. The price of energy on the local energy market are very dependent of the intelligence obtained by the market players. If the market should be efficient, every market player needs to actively participating and every market player also needs to make wise decisions. Since these decisions are based on forecast, the intelligence required by the market players to make these is very high.