Transmission system planning considering solar distributed generation penetration

Abstract

In recent years, power systems have been watching important advancements related with Plug-in-Electrical Vehicles (PEVs), Demand Side Management (DSM), Distributed Generation (DG), Microgrid and Smart Grid installations that directly affect distribution networks while impacting indirectly on Transmission studies. These changes will lead to an extra flexibility on the transmission-distribution boundary and to a significant modification of the load patterns, that are an essential input to planning studies. In this scope, this paper describes a multiyear Transmission Expansion Planning (TEP) solved by Evolutionary Particle Swarm Optimization (EPSO) and incorporating the impact of solar DG penetration. The primary substation load profiles and the solar generation profiles are taken into account on the planning problem. The numerical simulations were conducted using the IEEE 24 bus reliability test system in which the planning horizon is 3 years and the load growth is 2.5 % per year. If demand and solar DG peaks are coincident, then the liquid demand seen by the transmission network gets reduced enabling a reduction of investment costs. In the tested cases, these peaks were not coincident so that the optimal expansion plan remains unchanged even though the injected power from DG is large. This stresses the fact that solar DG may not on an isolated way contribute to alleviate the demand seen by transmission networks but should be associated with storage devices or demand side management programs.

A lattice method for jump-diffusion process applied to transmission expansion investments under demand and distributed generation uncertainties

“…They model DG penetration as certain percentages in overall power supply that need to be met by DGs. In a different study, Gomes and Saraiva [13] assume that a DG would account for 0%, 10%, 15%, and 20% of annual peak demand in each bus and observe their influences on transmission expansion investments. Similarly, Rathore and Roy [14] consider that DG capacities can be 15% or 20% of demand for electricity at each bus in a given power network.…”

Vertical Load Uncertainty at the T/D Boundary under different spatial DER allocation techniques

“…The modifications of the load patterns caused by distributed generation and anticipated flexibility additions at the transmission-distribution boundary have been presented in [16]. Results indicate that the penetration of distributed generation (PV) can provide added value to system through the reduction of operation costs, transmission losses and CO2 emissions.…”

Sharing Is Caring: Exploring Distributed Solar Photovoltaics and Local Electricity Consumption through a Renewable Energy Community

“…Nevertheless, a key challenge of PVs applied to residential prosumers is the observed mismatch between the generated energy profile and the energy demand profile: PV generation starts at the beginning of the morning, facing a peak close to midday (higher levels of irradiance) and ending with dusk [12]. In contrast, the average energy household demand profile presents one peak in the early morning (citizens using electricity for morning routines) and another one during the evening (citizens coming back home) [13]. In the context of an increasing number of distributed energy systems based on PVs, this mismatch may lead to problems associated with reverse power flows in the low voltage grid in neighborhoods with a high concentration of prosumers due to high amounts of energy injected into the grid during the PV peak hours.…”