Optimization of Local Energy Markets with Multiple Energy Carriers
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This thesis presents a research regarding local energy markets (LEM) with multiple energy carriers. As the energy transition is in full swing, the share of distributed energy generation in the energy landscape is increasing. This presents an opportunity for owners of small intermittent energy generation methods to start getting involved in the energy market. Communities in neighborhoods could start forming (semi)microgrids and efficiently exchange energy. The aim of the research was to fill a part of the research gap, as LEMs have not yet been combined with Energy hubs when analyzing three kinds of participants. LEMs present ample opportunities to develop local communities, improve energy security and get residents involved in the transition towards sustainability. When combining this with using multiple energy carriers at once, it may reduce congestion in the heat and electricity infrastructure and reduce delivery costs. A literature review was conducted, and two market design concepts are proposed and tested by means of five mixed-integer deterministic optimization models. Three weeks of December 2016 were simulated with three participants: an industrial company generating 160 kW electricity and 600 kW heat with a CHP plant, a prosumer that generates electricity and buys heat, and a consumer that can only buy electricity and heat. The Netherlands are used as the boundary with regards to regulation and price settings. The models were built in python, using Gurobi as the optimization tool. When energy is generated sustainably, tax cuts can be filed for and this may reduce the energy price in a LEM. The first model represents a simple peer-to-peer (P2P) market with a set price. The second model adapts the P2P market and applies a dynamic pricing mechanism based on a day-ahead and balancing market. Model 3 introduces a market and grid operator that aggregates all energy and redistributes it to the market players that need it, for the best price. Model 4 applies the dynamic pricing mechanism to the operator market and model 5 adds a storage possibility to model 4. All proposed market concepts lead to benefits for all players, with storage having the lowest energy costs by keeping more energy in the local market. This leads to net decreases in operational expenses for energy, with 38% for consumers, 49% for prosumers and 15% for industry on heat, while turning waste heat into a way to profit. The P2P market structure seems to be more beneficial for industry, while the aggregator market reaps benefits for the prosumer and consumer.