District Energy Technoeconomic Modeling for Heating & Cooling Central Plants

Good district energy technoeconomic modeling software has to answer one question: which central plant serves every building on the campus at the lowest cost over its life? A district plant makes heat, cooling and hot water in one place and sends it to many buildings through buried pipes. That makes the choice harder than for a single building.

First, the buildings do not all peak at the same hour. An office, a dorm and a lab each peak at different times, so the campus peak is smaller than the sum of the building peaks. Size the plant to that sum and you buy equipment that never runs. The ratio between the two is called the diversity factor.

Second, the pipes lose heat to the ground all year. That loss does not follow the buildings: it is there on a mild summer night as much as on the coldest morning. It sets a minimum load the plant never escapes, which changes how boilers, cogeneration and storage behave.

Third, the technologies depend on each other. A cogeneration (CHP) unit is sized for electricity and gives off heat as a byproduct. An absorption chiller needs a heat source. Comparing one machine against another on its own gives a wrong answer. The fair comparison is between complete plants that each serve the same loads.

Finally, a district plant is often a business. It sells heat and cooling to its customers on a rate card, or it is built and run by a provider under an Energy-as-a-Service (EaaS) contract. The model has to price that too.

Campus loads. You add each building group: its type, its size and how many there are. CogenS™ builds an hourly profile for each group from its building-type database for your location, or from your own uploaded profile. You choose which loads the plant serves: heating, cooling and hot water by default, with electricity as an option.

One combined load. The building profiles are added hour by hour, for all 8,760 hours of the year, into one coincident load per load type. The diversity factor is reported, so you can see how much smaller the campus peak is than the sum of the building peaks.

Network losses.For each building group you can enter its pipe route length and its heat loss per metre. CogenS adds that loss as a steady load all year, shares it between the thermal loads in proportion to their annual demand, and sizes every plant on the buildings' demand plus that loss. Electricity carries no pipe loss.

Each technology alone, then all together.In the first pass, each technology you selected (boilers, heat pumps, chillers, cogeneration, gensets, water heaters, solar) is sized to its load and run alone through the same full simulation a standalone CogenS project uses, with its part-load curves, pumps and auxiliaries. In the second pass, one optimization looks at every selected technology at once, including batteries and thermal storage, and chooses both the sizes and the hour-by-hour dispatch that cost the least. Each machine's own model then runs on that plan.

Sized to the combined load. You never type a plant size. The run sizes every machine to the campus load it serves, plus a sizing margin you control, and fills in performance from the closest catalog model.

Complete plants, one verdict. CogenS compares whole plants that each serve every load, including an all-electric plant when your selection allows one. A plant that leaves any load unserved is ruled out. The most expensive working plant becomes the base case, and the recommended plant is the one with the strongest investment case against it. Total cost of ownership breaks a tie. Figures are before tax, on an hourly basis, over the study period you set.

Rate cards and deal structures.If the plant sells heat and cooling, you set a rate card for each customer class: connection, capacity, energy and fixed charges. Five common district deal shapes (municipal cost recovery, regulated utility, concession, campus concession and heat-as-a-service) give a new class its starting shape. You can also model the plant under an Energy-as-a-Service contract (power purchase agreement, concession, capacity tolling or shared savings), with the charge solved for the provider's target return.

The report. One report for the district: the verdict, a decision tree that explains it, the recommended system with its diagram and dispatch charts, energy flows, a sensitivity analysis, every complete plant compared side by side, and a full data export.

Usual approach: size each building, then add them up. Many studies size the plant to the sum of building peaks, or to a single assumed diversity factor. CogenS adds the hourly profiles first and sizes to the peak of the combined curve, so the diversity comes from your buildings, not from a rule of thumb.

Usual approach: fold the pipe loss into the building loads. A percentage on top of demand puts too much loss on the winter peak and almost none in summer. CogenS treats the loss as the steady load it is, which is what keeps a cogeneration unit or a boiler running in summer.

Usual approach: compare machines one at a time. Setting a CHP unit against a boiler prices a power plant as if it were a heater. CogenS always compares complete plants: a CHP is bundled with its backup boiler and any chiller its heat drives, and set against equally complete alternatives.

Usual approach: a handful of options in a spreadsheet.Hand-built comparisons usually test three or four plant layouts with fixed sizes and flat efficiencies. CogenS runs every selected technology through a full hourly simulation, then lets an optimizer search sizes and dispatch across the whole mix, and checks the result again with each machine's own model.

Usual approach: cheapest first cost wins. A plant that sells power or stores energy spends more up front and earns some of it back. CogenS ranks plants on their investment case over the study period and rules out any plant that cannot carry the load, so a cheap answer that simply stops serving never wins.