Strategies for Charging Electric Vehicles in the Electricity Market

This paper analyses different charging strategies for a fleet of electric vehicles. Along with increasing the realism of the strategies, the opportunity for acting on the regulating market is also included. We test the value of a vehicle owner that can choose when and how to charge; by presenting a model of four alternative charging strategies. We think of them as increasing in sophistication from dumb via delayed to deterministic and stochastic model-based charging. We show that 29% of the total savings from ‘dumb’ are due to delayed charging and that substantial additional gains come charging optimally in response to predicted spot prices, and – in some settings – additional gains from using the up and down regulating prices. Particularly, strategies are chosen from uncontrolled charging through deterministic optimization, to modelling the charging and bidding problem with stochastic programming. We show that all vehicle owners will benefit from acting more intelligently on the energy market. Furthermore, the high value of the stochastic solution shows that, in case the regulating price differs from the expected, the solution to the deterministic problem becomes infeasible

Demand side management - electricity savings in Danish households reduce load variation, capacity requirements and associated emission

Energy savings are seen as contributing substantially to reducing the fossil fuel dependence in Denmark and improving energy efficiency. Electricity savings in households is contributing to this through the marginal effect of generating the electricity. As the fossil fuel content of generation varies across the hours also the fossil fuel reduction varies based on the hourly profile of the electricity saved. Using the hourly profile of savings, the different effect on emissions and power capacity requirements from varying electricity savings in households is compared. The value of the savings hereby depends on the profile of the reduced electricity demand. We establish the link between the aggregated hourly household load profile in Denmark and specific categories of household appliances. The objective is to evaluate the fossil fuel effect and value of increasing the average efficiency of different types of appliances. More efficient appliances are assumed to reduce the load curve for each appliance category proportionally. Policy implications relate to the finding that different types of electricity savings have very different emissions and capacity value effects. Potentially it may be relevant to support electricity savings (investment in efficient appliances) differently depending on the hourly profile of the savings. We want to clarify if some end-uses provide better social return on the investment in the efficient appliance model/version than others? The result suggests that savings in efficient lighting have much higher value than a corresponding annual saving in cold appliances

Demand side management - electricity savings in Danish households reduce load variation, capacity requirements and associated emission

Energy savings are seen as contributing substantially to reducing the fossil fuel dependence in Denmark and improving energy efficiency. Electricity savings in households is contributing to this through the marginal effect of generating the electricity. As the fossil fuel content of generation varies across the hours also the fossil fuel reduction varies based on the hourly profile of the electricity saved. Using the hourly profile of savings, the different effect on emissions and power capacity requirements from varying electricity savings in households is compared. The value of the savings hereby depends on the profile of the reduced electricity demand. We establish the link between the aggregated hourly household load profile in Denmark and specific categories of household appliances. The objective is to evaluate the fossil fuel effect and value of increasing the average efficiency of different types of appliances. More efficient appliances are assumed to reduce the load curve for each appliance category proportionally. Policy implications relate to the finding that different types of electricity savings have very different emissions and capacity value effects. Potentially it may be relevant to support electricity savings (investment in efficient appliances) differently depending on the hourly profile of the savings. We want to clarify if some end-uses provide better social return on the investment in the efficient appliance model/version than others? The result suggests that savings in efficient lighting have much higher value than a corresponding annual saving in cold appliances