Yvon Besanger

The transition toward intelligent and sustainable power systems requires practical schemes to integrate industrial demand flexibility into short-term operation, particularly in emerging electricity markets. This paper proposes an integrated framework that combines data-driven flexibility characterisation with a bi-level optimisation model for an industrial demand-side aggregator participating in the short-term balancing market. Flexibility is identified from AMI data and process information of large consumers, yielding around 2 MW of interruptible load and 3 MW of reducible load over a 24 h horizon. At the upper level, the aggregator maximises its profit by submitting flexibility offers; at the lower level, the system operator minimises balancing costs by co-optimising thermal generation and activated flexibility. The problem is formulated as a mixed-integer linear programming model and is evaluated on a real subtransmission and distribution network of a local utility in Ecuador, with ex-post power flow validation in DIgSILENT PowerFactory. Numerical results show that, despite the limited flexible capacity, the aggregator reduces the maximum energy price from USD/MWh 172.32 to 139.59 (about 19%), generating a daily revenue of USD 2475.15. From a network perspective, demand flexibility eliminates undervoltage at the most critical bus (from 0.93 to 1.03 p.u.) without creating overvoltages, while line loadings remain below 50% in all cases and total daily technical losses decrease from 89.46 to 89.10 MWh (about 0.4%). These results highlight both the potential and current limitations of industrial demand flexibility in short-term markets.

Time-delay is inherent to communications schemes in power systems, and in a closed loop strategy the presence of latencies increases inter-area oscillations and security problems in tie-lines. Recently, Wide Area Measurement Systems (WAMS) have been introduced to improve observability and overcome slow-rate communications from traditional Supervisory Control and Data Acquisition (SCADA). However, there is a need for tackling time-delays in control strategies based in WAMS. For this purpose, this paper proposes an Enhanced Time Delay Compensator (ETDC) approach which manages varying time delays introducing the perspective of network latency instead dead time; also, ETDC takes advantage of real signals and measurements transmission procedure in WAMS building a closed-loop memory control for power systems. The strength of the proposal was tested satisfactorily in a widely studied benchmark model in which inter-area oscillations were excited properly.

Cyber-Physical Energy System (CPES) - complex juxtaposition of multiple energy domains and communication and automation technologies - requires a sophisticated testing framework to achieve holistic assessment and validation, especially at large scale. In this paper, the real Supervision, Control and Data Acquisition (SCADA) system of CPES is integrated with the advanced techniques: Real-Time Simulation (RTS) and Power-hardware-in-the-loop (PHIL), in a cross-infrastructure manner to create a realistic validation environment for CPES. On the one hand, the method can be applied to extend the capacity of the infrastructures as well as creating a common resource and expertise pool. On the other hand, this approach combines the realistic data and advanced SCADA services with the flexibility of the real-time simulation platform, which provides the possibility to emulate extreme and faulty scenarios with virtual equipment and topology. The proposed approach is demonstrated via a case study of analysing the impact of communication on advanced voltage and frequency restoration in an isolated microgrid. The case study is implemented on two remote platforms PREDIS-PRISMES (70 km apart). The validation framework comprises the RTS and PHIL platform coupled with the OPC UA SCADA system in PRISMES, the control algorithm and the communication network simulator located in PREDIS platform.

Cyber-Physical Energy System, due to its multi-domain nature, requires a holistic validation methodology, which may involve the integration of assets and expertise from various research infrastructures. In this paper, the integration of Supervisory Control and Data Acquisition services to cross-infrastructure experiment is proposed. The method requires a high degree of interoperability among the participating partners and can be applied to extend the capacity as well as the degree of realism of advanced validation method such as co-simulation, remote hardware-in-the-loop or hybrid simulation. The proposed method is applied to a case study of multi-agent system based control for islanded microgrid where real devices from one platform is integrated to real-time simulation and control platform in a distanced infrastructure, in a holistic experimental implementation.

As more and more distributed renewable energy resources are integrated to the grid, the traditional consumers have become the prosumers who can sell back their surplus energy to the others who are in energy shortage. This peer-to-peer (P2P) energy transaction framework benefits the end users, financially and in term of energy security; and the network operators, in term of flexibility in DRES management, peak load shifting and regulation of voltage/frequency. Environmentally, P2P energy transaction also helps to reduce carbon footprint, reduces DRES payback period and incentivizes the installation of DRES. The current centralized market model is no longer suitable and it is therefore necessary to develop an adapted decentralized architecture for the advanced P2P energy transaction framework intra/inter-microgrid. In this paper, we discuss several distributed ledger approaches for such framework: Blockchain, Block Lattice and Directed Acyclic Graph (the Tangle). The technical advantages of these architectures as well as the persistent challenges are then considered.

Co-simulation is an emerging method for cyber-physical energy system (CPES) assessment and validation. Combining simulators of different domains into a joint experiment, co-simulation provides a holistic framework to consider the whole CPES at system level. In this paper, we present a systematic structuration of co-simulation based on a conceptual point of view. A co-simulation framework is then considered in its conceptual, semantic, syntactic, dynamic and technical layers. Coupling methods are investigated and classified according to these layers. This paper would serve as a solid theoretical base for specification of future applications of co-simulation and selection of coupling methods in CPES assessment and validation.