Electric power systems and the companies and customers that interact with them are
experiencing increasing levels of uncertainty due to factors such as renewable energy …

The fields of power system engineering and operations research are growing rapidly and
becoming increasingly entwined. This survey aims to strengthen the connections between …

A community integrated energy system (CIES) is an important carrier of the energy internet
and smart city in geographical and functional terms. Its emergence provides a new solution …

This paper proposes a data-driven distributionally robust co-optimization model for the peer-
to-peer (P2P) energy trading and network operation of interconnected microgrids (MGs). In …

This paper proposes a data-driven approach for optimal power flow (OPF) based on the
stacked extreme learning machine (SELM) framework. SELM has a fast training speed and …

This paper proposed a Wasserstein metric-based distributionally robust approximate
framework (WDRA), for unit commitment problem to manage the risk from uncertain wind …

Distributed renewable energy requires market-based measures to remain competitive as
subsidies are phased out. However, the intermittence and volatility of renewable energy …

The optimal control of distribution networks often requires monitoring and communication
infrastructure, either centralized or distributed. However, most of the current distribution …

In the context of transition towards sustainable, cost-efficient and reliable energy systems,
the improvement of current energy and reserve dispatch models is crucial to properly cope …

This paper proposes a novel data-driven adaptive robust optimization (ARO) framework for
the unit commitment (UC) problem integrating wind power into smart grids. By leveraging a …