Cloud–Edge Collaborative Energy Management System: Theory and Practical Experience

Rapid growth in renewable generation and electricity-market participation is increasing the number and autonomy of grid-connected resources, challenging conventional centralized energy management systems (EMSs). This paper proposes a cloud–edge collaborative EMS comprising a cloud brain, heterogeneous edge nodes, and a cloud–edge collaboration platform (CCP). The cloud retains wide-area security, market clearing, reserve coordination, and risk-limited dispatch, whereas each edge retains private device models and fast local control. A time-coupled flexibility envelope exposes only aggregate exchange-power, energy, ramp, and reserve limits. A delay-adaptive contraction maps communication latency into a conservative feasible region. Consensus ADMM coordinates the cloud and edge problems, with convergence and complexity discussed. The CCP specifies the data model, messaging protocol, preprocessing, command validation, and failure handling. An illustrative modified IEEE 118-bus benchmark compares centralized, edge-only, basic cloud–edge, and proposed schemes. Under a combined photovoltaic drop and load increase, the proposed method lowers operating cost by 11.1%, curtailment by 52.9%, and peak absolute area control error by 58.1% relative to a deterministic centralized EMS while avoiding load shedding. A 200-edge software emulation reports 4.76 s parallel solver time under the reference configuration. The synthetic study indicates improved coordination, privacy, and delay-aware feasibility.