ارزیابی اقدامات بخش تقاضا در مدل های شبیه سازی برای بازار برق

Increased energy efficiency is one of the pillars for reducing CO2 emissions. However, in models for the electricity market like unit commitment and dispatch models, increased efficiency of demand results in a paradoxical apparent reduction of the total economic surplus. The reason is that these are partial models for the electricity market, which do not take into account the effect of the changes in other markets. This paper shows how the calculation of the consumer surplus in the electricity market should be corrected to take into account the effect in other markets. In different cases we study shifts in the demand curve that are caused by increased energy efficiency, reduced cost for substitutes to electricity and real-time monitoring of demand, and we derive the necessary correction. The correction can easily be included in existing simulation models, and makes it possible to assess the effect of changes in demand on economic surplus.

Increased energy efficiency is commonly seen as one of the main pillars for reducing the dependency on fossil fuels and reducing CO2 emissions. This is clearly demonstrated by EU's goal to increase energy efficiency by 20% within 2020 [1]. Reducing demand is challenging, and targeted policy measures will be necessary. The effects of such measures are hard to foresee, but simulation models can be used to give quantitative predictions. However, simulating the effect of changes in demand is not a trivial task. In this paper we demonstrate that the evaluation of the benefits of demand side policies easily leads to false answers when this is analyzed in, e.g. unit commitment and dispatch models. Subsequently we propose a solution to this problem. The literature on energy efficiency is exhaustive, ranging from improvement of specific industrial or residential applications, analyses to study the impact of increased energy efficiency on energy systems in general, studies of the effect of real-time monitoring, and policy analyses and recommendations. Two examples of the latter categories are Stadler et al. [2] who study the effectiveness of technologies and/or efficiency measures using a new simulation tool and Farinelli et al. [3], who simulate policies and measures using technical-economic models of the well-known MARKAL family. Electricity consumption is also expected to be increasingly influenced by the accelerating introduction of Advanced Metering Infrastructure (AMI). This development can make it attractive for consumers to react on short-term variations in prices, and it also provides a basic infrastructure for load control. General customer response on price changes is described in for example [5], [6], [7] and [8]. Recently also the US Federal Energy Regulatory Commission has issued a report on demand response [9]. More specific load control of water heaters is discussed in [10] and [11].

In partial models for the electricity market like unit commitment and dispatch models it is necessary to adjust the calculated change in the consumer surplus when the value of exogenous changes in the demand curve is assessed. The approach is basically the same for all cases—the consumer surplus must be corrected with the integrated difference between the old and new demand curves. In the cases where the demand curve shifted because of a reduced price for a substitute to electricity or because of increased energy efficiency, the change in the consumer surplus must be adjusted with the area between the old and new demand curve. In the case the demand curve shifted because consumers are exposed to varying prices, it is necessary to adjust the change in consumer surplus with the area between the demand curves on the left of the consumed amount. The proposed approach can easily be included in existing simulation models, and makes it possible to assess how changes in demand affect the total economic surplus compared, e.g. to increased generation. Appendix A. Demand curve for electricity and a substitute Eq. (11) in Section 3 shows the real change in the surplus when the price of the alternative fuel changes. If the same energy-bundle is purchased, consumer-surplus changes by δ · xalt. Therefore, the true consumer surplus is changed by at least this amount. The calculated consumer surplus in a partial model for the electricity market is however the area under the demand curve for electricity minus expenses for purchasing electricity. In the following we will derive this amount. The demand for alternative energy xalt follows from (5) combined with (4), (7) and (8), and the optimal solution is: