HYPERLOCAL WEATHER FORECASTS
Cutting down unnecessary initiation of power plants and excessive district heating water temperature with hyperlocal weather forecasts is a new way forward.
By Tuukka Teppola, Growth Manager – Wx Beacon Vaisala Xweather
more efficiently and effectively, improving customer satisfac- tion, lowering environmental burdens, and increasing profits. Two key factors that impact load forecast are human behav- iour and weather. While human behaviour is quite predicta- ble — based on daily, weekly, and annual patterns — weather prediction is a much trickier case. That is why district heating companies depend heavily on weather forecasts. Unfortunate- ly, significant forecast errors are not uncommon; plants then waste fuel and increase emissions. It all comes down to cor- rectly forecasting the weather in the location that matters for your energy operations — for upcoming minutes, hours, and days.
Every district heating company faces this challenge: there is an upcoming cold weather front, and as a heating provider, you strive to meet the demand. You must decide how much heat to produce and adjust your network’s water temperature. It’s cold outside, so you initiate your additional heating plant and start burning fuel. You raise the water temperature and get ready to pump the water to every corner of the network. But the cold weather never comes, and you end up with increased emissions and heat loss, all for nothing. It would help if you had better weather forecasting in your planning, one that can ac- count for your city’s unique characteristics and minimizes the errors in the forecast. Minimizing unnecessary plant initiations, and optimizing wa- ter temperature are feasible and relatively easy ways to reduce environmental footprint (and potentially increase profits). In- itiating and running additional plants consumes enormous amounts of energy and other resources. The same is true for the excessively high water temperature in the network: extra fuel, unnecessary production mix, electricity for pumping, per- son-hours, heat losses in pipes; you name it. When trying to choose the perfect mix of optimal heat pro- duction, the right supply temperature, and the correct heat distribution, heat load forecast is everything. Accurate heat load forecasting helps district heating companies operate
Now, regarding weather forecasts, the number of errors is everything.
Accurately representing the current state of the atmosphere be- gins with observations. Today, we leverage both in-situ (in place) and remote sensing networks to observe the atmosphere. In-si- tu, surface-based networks are numerous but only represent a small part of the atmosphere. Remote sensing capabilities, primarily from space, measure more significant portions of the atmosphere but struggle to see all variables (especially near the surface) and have their own challenges (like getting satellites to space and keeping them functioning there). Continues on page 6
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