Tariffs energy contracts optimal Distributed is a M.Tech project topic for Electrical Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Tariffs energy contracts optimal Distributed Project Details
| Abstract |
This research looks at the tough planning and optimization problems that big electricity users—like university campuses—face when they add distributed energy resources (DERs). We built a tariff‑aware mixed‑integer linear programming (MILP) model that decides both where to invest in DERs and how to buy electricity each hour for a full year (8760 hours). The model includes: – Different types of photovoltaic (PV) installations placed on rooftops, parking areas, and on the ground. – Separate sizing of battery energy storage system (BESS) power and capacity. – Degradation and replacement costs that are specific to each technology. – Complex utility tariffs, including charges for peak demand. The formulation also lets the user
choose energy contracts, follows rules for exporting excess power, handles curtailment, accounts for battery wear from cycling, and considers resilience during grid outages. We tested the model on a synthetic campus that uses 22 GWh per year and has a 5.50 MW peak demand. The optimization cut total annual costs and billing peaks by a large amount. This approach gives a clear way to assess the economic viability of hybrid PV‑battery systems under multiple tariff structures, helping institutions plan microgrids and make investment decisions.
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| Reference Paper |
Tariffs, energy contracts, and optimal Distributed Energy Resources investment in campus microgrids |
| Domain |
Electrical Engineering |
| Sub-Domain |
Power Systems / Renewable Energy / Hybrid Microgrids |
| PDF Download |
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