Understanding the Energy Transition
About the Project
We developed the KAPSARC Energy Model (KEM) for Saudi Arabia to understand the dynamics of the country’s energy system. It is a partial equilibrium model formulated as a mixed complementarity problem to capture the administered prices that permeate the local economy. KEM has been previously used to study the impacts of various industrial fuel pricing policies, improved residential energy efficiency on the energy economy, the feasibility of installing coalfired power plants in Saudi Arabia, and reforming residential electricity tariffs. In the present paper, we use it to assess the effects of introducing an optimal power flow formulation for electricity transmission on policy-relevant metrics.
The purpose of this study is to assess policy-relevant effects of incorporating a more proper representation of electricity transmission in multi-sector national policy models. This goal is achieved by employing the KAPSARC Energy Model (KEM), which is the first publicly available large-scale energy policy model for Saudi Arabia. Past studies using KEM have examined industrial pricing policy, residential energy efficiency, the prospects of power generation technologies and residential electricity pricing. These studies have shown that under certain fuel pricing scenarios, significant renewable energy capacity is deployed.
Previous versions of KEM used a transshipment formulation for electricity transfer, which basically treats it similar to fuel transport. Electricity transmission formulations, however, represent the physical constraints that govern power flows in reallife. The variability and intermittency of renewable power imposes limitations on the operations of the grid and models that do not incorporate a representation of electricity transmission may miss key insights, particularly when large-scale deployment of renewable technologies is contemplated. This study illustrates the methodology and consequences of moving from a transshipment formulation of KEM to one which includes transmission with a single or multiple nodes within each region.
Our results show:
The optimal investment in photovoltaics (PV) and the marginal costs of delivering electricity change considerably when transmission of electricity both within regions and between regions is incorporated into the model compared to the simple transshipment formulation.
The number of nodes in each region described by the model alters the model outcomes more than whether the model incorporates transmission losses or not. However, a version of KEM with a single node in each region for transmission and without accounting for transmission losses still provides valuable insight compared with the transshipment formulation, while keeping the model size tractable
Introducing transmission into the model gives results that are more affected by the operations of the power system than by the fuel and technology mix. The market-clearing price of natural gas in a deregulated environment only changes slightly because reduced PV deployment (compared to the transshipment version) is mostly offset by a minor increase in dispatch of gas-fired generation.
In a regulatory model where location marginal prices are passed on to consumers, the new model captures the changes in the marginal costs of electricity delivery at the transmission nodes whereas the simpler transshipment formulation would miss this insight. In other words, the transmission component is needed for planning a system where location marginal prices are passed on to consumers.
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