BOLETÍN OFICIAL DEL ESTADO
MÓDULO FORMATIVO 4
Since the wind is determined by random meteorological processes, it is inherently variable and, therefore, wind power presents high variations not only seasonally, but also on shorter time scales, namely on hourly basis. Several extreme ramp rates of reduction on wind power generation were already recorded in Portugal and elsewhere. Additionally, the supply of power from wind turbines is stochastic in nature and the actual power is more or less proportional to the third power of the wind velocity. Therefore, wind power cannot be perfectly forecasted since a small error on the wind velocity leads to a high error on the forecast of the power. Figure 5.20 presents one example of a recent event (January 6, 2014) with a large ramp rate of generation reduction and a large forecasting error. In this situation, there is a reduction of 1190 MW (40%) between 13 and 17 hours (average reduction of 300 MW/hour) and simultaneously there are large errors on the forecast, reaching a maximum error of 29.5% (476 MW). As far as security of supply is concerned, the most severe problems due to the wind power intermittence occur in the peak load hours, since the largest part of the available system resources to deal with the intermittence is already used and a sudden reduction of the wind power production can have critical consequences on the system reliability. Thus, instead of
acting in the supply side, to avoid the most severe intermittent situations, Demand Side Management measures can be promoted to achieve consumption reductions and, mainly, to balance supply and demand. Therefore, the use of efficient space conditioning solutions is very important to avoid such problems. However, in cases of high wind power penetration, the energy consumption reduction during the peak hours may not be enough, due to the large generation variations, in situations with a large forecasting error. In such situations it will be very important to have Demand Response (DR) technologies to “force” consumption reductions at near real time, in the precise moment in which the critical situations occur. In a smart grid context this can be implemented by controlling the space conditioning loads, with a change in the temperature of the system or even with a temporary shutdown. Figure 5.20: Wind generation and forecast on January 6, 2014. As it was previously demonstrated for the experimental GSHP installation, the shutdown of the system space conditioning during one hour can be done without a relevant impact on the comfort level. Therefore, such strategy was implemented by considering the shutdown of the system between 1 and 2 p.m. The reduction of consumption achieved with the shutdown can therefore be considered as a virtual increase of the wind generation. Figure 5.21 presents the achieved impact and, as can be seen, during such period the difference between the real generation and the forecast can be substantially decreased (a reduction of 55.5% was achieved). This is achieved just by controlling 25% of the office buildings, and therefore by expanding this control strategy to all office buildings and other types of buildings a total compensation of the error would be possible.
Figure 5.21: Impact of DR on the reduction of wind forecasting errors on January 6, 2014.
The DR action was implemented in the beginning of the variation and not in the moment of the highest error, since the main problems to the electrical grid occur in the beginning of the variation, due to the need of a fast answer from the system to compensate the lost generation capacity. If the system does not have enough flexibility to react immediately, e.g., with the increase of hydropower generation, it can have critical consequences on the system reliability. Therefore, concentrating the load reduction in the beginning of the variation, to give enough time to increase the generation ensured by other sources, is usually the best solution to avoid major reliability problems. The implementation of DR presents as a main benefit the increase on the electrical grid reliability, but it can also represent an economic benefit for the consumer, since the users that accept the implementation of a DR action are usually compensated with a reduction of tariffs or a payment by each DR action implemented.
5.5 ‐ C
ONCLUSIONSUsing the experimental GSHP system, it was demonstrated that heat pumps, when combined with the building thermal mass, can be used as a flexible load to balance supply and demand, and to allow the reduction of operation costs at the consumer side. For this purpose, several strategies of heating loads management were proposed and tested.
To assess the thermal response of the building, a model based on the lumped capacitance method was applied. This model allowed determining the required preheating time as a
function of the building parameters, building unoccupied period, desired indoor temperature, outdoor temperature and HP thermal power.
The indoor air temperature decay was analyzed after shutting down the heating system one hour before the ending of the occupation period. After turning off the system for one hour, the indoor air temperature only decreased 1 °C (for 1.5 hours the decrease is 1.5 °C). Assuming that this temperature decrease is acceptable for users, the curtailment strategy can be used for periods up to 1.5 hours.
To guarantee thermal comfort to the users when they arrive and to take advantage from the lower electricity prices, two preheating strategies were applied. The main purpose is that at 9 a.m. the building temperature is near to the steady state to minimize or even to avoid the energy consumption during the morning peak period. Different preheating times were tested, taking into account the outdoor temperature, associated to a curtailment strategy at the end of the day and costs savings of 16‐19% were achieved. Higher costs savings can be achieved (about 34%) with longer preheating periods in order to be possible to avoid energy consumption during the morning peak, as well as by shutting off earlier the heating system, one hour before the ending of the working day, to avoid the second electricity peak period. The impacts on the national electric diagram of applying the preheating strategy and the curtailment strategies were assessed. These strategies were extrapolated to other office buildings with similar occupancy periods, assuming that only 25% of the office buildings can be controlled. The preheating strategy of the office buildings was used as a way to integrate the surplus of renewable energy generation. Based on the two examples studied, it was found that significant part of the renewable energy generated during night and early morning (19‐30%) can be absorbed. It was also demonstrated that by shutting down temporarily the space conditioning it is possible to substantially compensate the variations of wind power generation and forecasting errors during the first hour of variation (55.5% in the presented scenario), giving enough time to adapt the other resources of the electrical system.
The role of high efficient heat pumps combined with building thermal mass (as flexible load) can play a key role for sustainable and efficient building space heating, as well as contribute to integrate electricity generated by intermittent renewable resources and to improve grid management using load leveling and Demand Response strategies.