Nowadays, most modern power systems are evolving towards a considerable capacity expansion in their energy storage and interconnection facilities. However, these great developments are not being accomplished fast enough to accommodate the high penetration of variable renewable energy sources. This situation raises demand variability, requiring more flexibility from thermal generators, especially due to their more frequent start-up and shut-down processes. Consequently, the unit commitment requires more accurate and detailed modeling while maintaining computational efficiency. This paper analyzes some of the best models to manage long-duration start-up costs according to the real fuel-consumption curves of a gas-fired generation portfolio. Moreover, we propose a tight and compact MILP piecewise formulation that enhances the resolution of start-up representations and achieves outstanding results compared to the literature benchmarks. The successful performance of this methodology is proven in several large-size case studies focusing on the medium term. Furthermore, conventional day-ahead problems are also run to demonstrate the overall competitiveness of the formulation.

As the penetration of distributed energy resources (DERs) escalates in distribution networks, new network tariffs are needed to cope with this new situation. These tariffs should allocate network costs to users, promoting an efficient use of the distribution network. This paper proposes a methodology to evaluate and compare network tariff designs. Four design attributes are proposed for this aim: (i) network cost recovery; (ii) deferral of network reinforcements; (iii) efficient consumer response; (iv) recognition of side-effects on consumers. Through an analytical hierarchy process (AHP), the evaluation methodology is applied to compare traditional cost allocation methods, on the basis of 100% energy, 100% demand, and 50% energy-50% demand, with more advanced pricing methods based on distribution locational marginal prices in combination with cost-reflective network charges. Numerical results are obtained through a case study based on the IEEE 34-node test feeder with DER integration. The results illustrate the advantage of advanced pricing methods to promote an efficient integration of DER and demand price-response from consumers.