Stochastic Planning of a Campus Microgrid Considering Practical CHP and Market Constraints
Bibliographic record
Abstract
This paper presents a stochastic planning framework to determine the optimal sizing of BESS and PV for campus microgrids based on realistic data obtained from the University of Calgary campus microgrid. This grid-connected microgrid includes a combined heat and power (CHP) plant and a 400 kW solar photovoltaic (PV) system. Driven by campus mandates for efficiency, reliability, and sustainability, the planning framework studies and identifies the optimal investment scenario for upgrading the existing PV capacity and incorporating a battery energy storage system (BESS). The practical framework integrates the operational intricacies of the CHP plant and the modeling complexities of the Alberta electricity market, including the pool price and the nonlinear transmission and distribution fees (T&D). By considering various stochastic scenarios regarding electricity price, load growth, and gas price, the study develops a daily optimization approach to consider the intricacies of the electricity market, formulating the optimization framework as a mixed-integer linear programming stochastic problem. Reported key performance metrics include the net present cost (NPC) and the saving-to-investment ratio (SIR) over the planning horizon. Results support investing in distributed energy resources (DERs) to reduce the supplied cost of energy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".