Forecasting and Smart Hybrid Grids

W&CSs have a key role to play in smart hybrid grids management. Although many utilities already use forecasting to address their current challenges, forecasting will increase in importance because of the growing contribution of Renewables (RE) and the complexity of challenges ahead. Traditionally historical information on weather and demand was used to predict future demand under certain weather conditions, but changing climate patterns are effectively making these models less accurate. Revised models need to be developed to include weather volatility, which directly affects generation of renewable energy. These models also need to be able to efficiently process large amount of data (many Gigabyte or more, also referred to as big data) from a data-rich smart grid environment, which must anticipate customer response and changing attitudes about energy consumption in addition to the traditional economic and weather influences. Forecast systems must be able to build disaggregated forecast models that look at a variety of weather factors. One-variable models are no longer the primary forecasting option and forecasting models must be able to determine more indicators of factors affecting load (Jamal et al., 2020, SAS, 2022), including social behaviour (Chapagain, 2020, Table 1 and Figure 1).

Table 1. Example of selected variables – including temperature and holidays – used to forecast energy demand in Thailand (see Figure 1). Source: Chapagain, 2020

Figure 1. Forecasting energy demand using the variables defined in table 1, showing changes in model skill according to social activity; a) during Songkran festival and b) last week of the year. Source: Chapagain et al., 2020

Weather and Climate Services for energy forecasting in smart grids can provide key insights for planning, investment, and decision-making purposes by understanding and trying to predict:

Energy generation changes according to RE type and average fluctuation of the RE resource used
Energy use patterns by geographic location, which are exposed to particular weather conditions
Energy patterns of costumers on an hourly or monthly basis given their relation to weather conditions and seasonality
Customers’ response to prices, weather and climate change
Customer awareness about energy consumption
Energy use patterns by demographic and economic conditions – customer segmentation
Energy demand due to a transition to electric vehicles, heat pumps and the use of smart meters

The nature of the questions that forecasters need to ask is also changing:

How can I improve renewables forecasting for utility-owned and customer-owned solar and wind generation?
How do I plan for and operate a power system that now includes solar, wind and storage?
If the temperature varies significantly from the forecast on any given day, how much will that influence customers’ behaviour?
What is the range of loads that can be expected not only on the system as a whole but also at the substation and transformer level?
What is the resource variability at different time scales?
How much will my utility’s pricing programs (time of use, critical peak, etc.) influence the forecasted demand during periods of energy curtailment?

Another important W&CSs contribution in the context of hybrid grids is the provision of climate projections for Weather Readiness Assessments (useful to plan the actions required to reinforce infrastructure and for utility management), and also Adequacy Assessments (used to ensure that the electricity system can supply sufficient energy to meet the demand over the next few years or decade). And of course, their role is invaluable for identifying and advising where and how hybrid grids can grow in developing countries, particularly those with limited energy access.

Some of the common technical barriers faced by utilities operating hybrid systems and where W&CSs can help optimise supply and demand balance are:

Power reliability and power quality due to comparatively weak networks. Short term forecasts can greatly improve power reliability by allowing companies to buy energy from other sources or use storage (e.g. hydropower pumped storage) if available.
Output variability of PV and Eolic producing power fluctuations in the grid. To best manage fluctuations wind farms are required to leave some headroom, that is to generate under their capacity so they have the capacity to respond quickly to energy demand; also hydro-electric plants play a key role stabilising the grid as their output is relatively constant. In this context, W&CSs are critical in helping respond to shifts in energy generation by requesting alternate generators to ramp up their production.
Energy generation scheduling during peak demand hours when renewable output is insufficient (cf. Figure 2). In this case a systemic approach is needed, with actions from the provider, distributor and the user. Users receive information about energy availability based on weather forecasting, to allow them to adjust their energy demand to forecasted availability. Power plants can reschedule their energy generation to match resource availability providing that there is an energy-storing facility in the grid (e.g. batteries, Pumped Storage Hydropower)
Operational and safety standards that need regular evaluation and updating. Weather and Climate Risk Assessments are becoming essential to evaluate and design such standards so companies can respond safely to weather and climate hazards and also weather-proof their facilities.

Forecasting and Smart Hybrid Grids

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