Short-term operating requirements and constraints in power systems are becoming increasingly important with the greater flexibility needed due to the integration of variable renewables. However, large problem sizes and computational barriers have limited the extent to which they are included in long-term planning models. Our objective is to understand the role of electricity storage in future renewable-based systems by including an accurate representation of short-term operation with high temporal detail within a long-term planning framework. Specifically, we discuss the development of a long-term investment model including a continuous relaxation of the technology-clustered formulation of the short-term unit commitment problem, including detailed operating reserve sizing and supply. This model is solved for a full year, and is applied to a test system with system load and renewable generation characteristics from the Belgian power system in a greenfield setting, i.e., assuming no pre-existing capacities, to analyze the role of storage at different renewable penetration levels. Both pumped-hydro storage and battery energy storage is considered, and their role in providing energy services and frequency control is investigated. We derive broadly applicable conclusions on the benefits and role of electricity storage to motivate why it may be built and operated. Results show that, in general, the integration of storage resources decreases total system cost, partially replaces flexible power plants, facilitates the integration of renewable energy sources, and allows inflexible technologies to perform better.
This work presents a new method to quantify the flexibility of automatic demand response, combined with real time pricing, applied to residential electricity demand using price elasticities. A stochastic bottom-up model of flexible electricity demand in 2050 is presented. Three types of flexible devices are implemented: electric heating, electric vehicles and wet appliances. Each house schedules its flexible demand w.r.t. a varying price signal, in order to minimize its electricity cost. Own-and cross-price elasticities are obtained through a regression analysis. Via a Monte Carlo approach-based method, the elasticities are scaled up to a country level. The results show that the electric energy demand will double and that, when combining automatic demand response with real time pricing, power peaks in demand could be incurred that are 5 to 8 times greater than today. The elasticity matrices show that for Belgium most flexibility is available in winter and least in summer.
Energy system integration can bring several benefits to energy systems, notably to those that are in transition to high shares of renewable energy. Strategies are needed to realize the theoretical benefits of this approach in practice. Therefore, this paper proposes the organization and mathematical formulation of a multi-carrier day-ahead market in which electricity, gas and heat are traded simultaneously. This market set-up is applied to a conceptual test case to identify how -compared to a reference set-up mimicking the current practice -the multi-carrier market is able to unlock the benefits of energy system integration. It is quantitatively shown that the multi-carrier market (1) eliminates the need for forecasts of prices on subsequent markets and the consequences of the related errors, (2) allows to use the flexibility available in one carrier to facilitate the balancing in another, e.g. using the flexibility of a heat system to help balance the electricity system, and (3) enables specific market outcomes, unachievable in a sequential set-up, which increase the optimality of the market outcome.
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