Scheduling and operation of RES-based virtual power plants with e-mobility: A novel integrated stochastic model

In the present paper, an Energy Management System is proposed to optimally schedule and operate a Virtual Power Plant (VPP) composed of charging stations for e-vehicles, stationary batteries, and renewable energy sources. The model is capable to optimize the bidding process on the Day-Ahead Market (DAM) through a two-stage stochastic formulation, which considers the uncertainties affecting the evaluation of the energy required for the next day. The stochastic scenarios are generated through a Monte Carlo procedure and clustered by a reduced domain k-means algorithm. To manage in real-time the operation of the VPP, a new Rolling Horizon mixed-integer linear programming model is adopted. The effectiveness of the tools developed is proved by numerical simulations reproducing the different operating conditions of the VPP. The benefits of the approach are confirmed by extensive analyses performed over a 4-month period. An increase of the profits of 23 % compared to a non-optimized strategy and of 6 % with respect to a deterministic optimization is observed

Flexibility Provision by an Aggregate of Electric Boilers in the Italian Regulatory Framework

The present work provides a numerical evaluation of the flexibility that an aggregate of electric boilers can supply to the power system in the Italian framework. To this purpose, the paper firstly outlines the current national regulations regarding the provision of flexibility by distributed energy resources. Then, considering the Italian discipline as a reference, a sensitivity analysis is performed on the regulating capability of an aggregate of electric boilers. In the analysis, the effects on the users' thermal comfort are also taken into account. To control boilers, enabling the provision of ancillary services, a heuristic based on a Greedy-Indexing algorithm is proposed, while the hot water usage is simulated by real data. The heuristic strategy implemented resulted to be particularly effective, enabling the provision of services without introducing significant detrimental effects on the users' thermal comfort

Residential Users as Flexibility Providers: a Techno-Economic Analysis

The increasing spreading of generation affected by uncertainty and the gradual phase-out of fossil-based power plants are requesting many countries to open the Ancillary Service Markets (ASMs) to new actors, such as the aggregators. In this framework, this paper presents a study aimed to evaluate the regulating capabilities, from both a technical and an economic point of view, of an aggregate composed of residential users equipped with small-scale renewable power plants and flexible loads (V2Ge-vehicles, electrical water boilers). To this purpose, two numerical models are proposed: the former quantifies the flexibility that can be offered in the ASM, while the latter simulates the operation of the aggregate, assessing the flexibility available and evaluating the possible unwanted effects caused to the users in case of ancillary service activation. Extensive analyses are performed, considering the Italian scenario as a reference

Short-term uncertainty in the dispatch of energy resources for VPP: A novel rolling horizon model based on stochastic programming

The intermittent nature of distributed energy resources introduces new degrees of uncertainty in the operation of energy systems; hence, short-term decisions can no longer be considered fully deterministic. In this article, an energy management system (EMS) was proposed to optimize the market participation and the real-time operation of a virtual power plant (VPP) composed of photovoltaic generators, non-flexible loads, and storage systems (e-vehicle, stationary battery, and thermal storage). The market bidding process was optimized through a two-stage stochastic formulation, which considered the day-ahead forecast uncertainty to minimize the energy cost and make available reserve margins in the ancillary service market. The real-time management of regulating resources was obtained through an innovative rolling horizon stochastic programming model, taking into account the effects of short-term uncertainties. Numerical simulations were carried out to demonstrate the effectiveness of the proposed EMS. The architecture proved to be effective in managing several distributed resources, enabling the provision of ancillary services to the power system. In particular, the model developed allowed an increase in the VPP's profits of up to 11% and a reduction in the energy imbalance of 25.1% compared to a deterministic optimization