Smart prosumers with Distributed Generation (DGs) and controllable loads can provide cost-effective grid services. However, realizing this potential requires distributed optimization mechanisms that ensure market efficiency, participant privacy, and compliance with electricity market regulations. This paper presents a bi-level distributed optimization mechanism to maximize flexibility services from industrial parks and Internet Data Centers (IDCs) in distribution-level Congestion Management (CM) markets. The upper-level models the Distribution System Operator (DSO), which identifies congested lines using linear AC power flow analysis on pre-settled energy market results and sends corrective signals to prosumers. The lower level allows prosumers to adjust their operations accordingly and communicate updated transactions back to the DSO. A novel proxy-driven algorithm is proposed to facilitate service-sharing among geo-distributed IDCs, considering congestion issues. Additionally, an adaptive Alternating Direction Method of Multipliers (ADMM) algorithm enables decentralized coordination among market agents, achieving 74.52 % faster convergence than the standard ADMM. A real-world case study from Spain demonstrates that the proposed mechanism enables the grid operator to maximize grid services from prosumers, reducing congestion alleviation costs by 35.27 %. Moreover, IDCs reduced daily costs by 11.07 % through service-sharing and task-shifting aligned with CM market signals, while industrial parks achieved a 13.68 % cost reduction by aligning material production processes with CM market signals, both enabled by the proposed bi-level mechanism.

Integrated community energy systems (ICESs) are emerging as a modern development to re-organize local energy systems allowing simultaneous integration of distributed energy resources (DERs) and engagement of local communities. Although local energy initiatives, such as ICESs are rapidly emerging due to community objectives, such as cost and emission reductions as well as resiliency, assessment and evaluation are still lacking on the value that these systems can provide both to the local communities as well as to the whole energy system. In this paper, we present a model-based framework to assess the value of ICESs for the local communities. The distributed energy resources-consumer adoption model (DER-CAM) based ICES model is used to assess the value of an ICES in the Netherlands. For the considered community size and local conditions, grid-connected ICESs are already beneficial to the alternative of solely being supplied from the grid both in terms of total energy costs and CO2 emissions, whereas grid-defected systems, although performing very well in terms of CO2 emission reduction, are still rather expensive.

Integrated Community Energy Systems (ICESs) are emerging as a modern development to re-organize the local energy systems allowing integration of distributed energy resources (DERs) and engagement of local communities. Although local energy initiatives such as ICESs are rapidly emerging, assessment and evaluation are still lacking on the value these systems can provide both to the local communities as well as to the whole energy system. In this paper, we present a framework to assess the value of ICESs for local communities. We apply this framework to assess the value of ICES in Spain. For a block of 10 households, investments and operations of DERs together with local exchange is simulated in DER-CAM model. For the considered community size and local conditions, ICESs are beneficial to the alternative of solely being supplied from the grid. An ICES that gets remunerated the excess energy to the grid has higher benefits than the system where energy exports are not remunerated as currently in Spain.