Energy management of a building cooling system with thermal storage: A randomized solution with feedforward disturbance compensation

We consider a cooling system that comprises a building composed of multiple thermally conditioned zones, a chiller plant, and a thermal storage unit. The electrical energy price is time-varying, and the goal is to minimize the electrical energy cost along some look-ahead time horizon while guaranteeing an appropriate level of comfort for the occupants of the building. To this purpose, we can appropriately set the temperatures profiles in the zones of the building and the cooling energy exchange with the storage. Since the cooling system is affected by stochastic disturbances, we adopt a stochastic formulation of the control problem, where constraints are imposed in probability and measurable disturbances are possibly compensated. The resulting chance-constrained optimization problem is then solved via a randomized approach. Numerical results show a significant reduction of the cost when the feedforward disturbance compensation scheme is adopted

An iterative scheme to hierarchically structured optimal energy management of a microgrid

In this paper we address the optimal energy management of a microgrid composed of multiple sub-units, each one including one or more buildings sharing some common resources. The goal of the microgrid operator is to match a given electrical energy profile agreed with the operator of the main grid. We propose a decentralized solution scheme based on a hierarchical structure involving three layers: single building, sub-unit, and microgrid operator. At the level of each building, thermal and electrical energy requests are minimized while guaranteeing a certain comfort and quality of service to the building occupants. Optimization of the use of common resources (storages and technological devices) is performed by each sub-unit based on the energy requests of the buildings composing the sub-unit and the cost signal received by the microgrid operator. Each sub-unit minimizes its electrical energy cost as computed based on its own cost signal, while the microgrid operator updates all cost signals based on the outcome of the decentralized optimization, so as to coordinate the sub-units and match the given reference profile. A numerical example shows the efficacy of the approach

Optimal energy management of a building cooling system with thermal storage: A convex formulation

This paper addresses the optimal energy management of a cooling system, which comprises a building composed of a number of thermally conditioned zones, a chiller plant that converts the electrical energy in cooling energy, and a thermal storage unit. The electrical energy price is time-varying, and the goal is to minimize the electrical energy cost along some look-ahead time horizon while guaranteeing an appropriate level of comfort in the building. A key feature of the approach is that the temperatures in the zones are treated as control inputs together with the cooling energy exchange with the storage. This simplifies the enforcement of comfort, which can be directly imposed through appropriate constraints on the control inputs. Furthermore, a model that is easily scalable in the number of zones and convex as a function of the control inputs is derived based on energy balance equations. A convex constrained optimization program is then formulated to address the optimal energy management with reference to the forecasted operating conditions of the building. Simulation results show the efficacy of the proposed approach

An approximate dynamic programming approach to the energy management of a building cooling system

This paper is concerned with optimal energy management of micro-grids. The goal is to show that the problem of minimizing the operating costs of a micro-grid by coordinating and scheduling its components can be formulated as a constrained optimal control problem for a stochastic hybrid system. This, in turn can be addressed through the Dynamic Programming (DP) approach, and the resulting DP equations solved through approximate DP techniques. A simple case study of a building cooling system with two chillers serving a cooling load is presented to this purpose