SCCER-FURIES - Report on the role of multi-carrier, multi-services, multi-grids integrated energy conversion systems and their possible role in the Swiss energy 2050 - Deliverable D1.5.3

The optimisation of distributed and renewable energy systems in buildings has shown that zero energy systems, using existing technologies, is within reach in the household sector where the thermal and the systems can support each other to increase renewable energy harvesting, co-generation and waste heat recovery. Smart and sustainable systems can be deployed rapidly using solar collectors, heat pumps, energy storages and smart power grid driven by a Smart Energy Management strategy (SEM), based on Model Predictive Control (MPC). Targeting energy autonomous systems will indeed require a step further in the development of the infrastructure. In line with the design of future 100% renewable energy systems and autonomous cities, advanced concepts of multi-service energy systems have been proposed. These concepts of multi-carrier, multi-services and multi-grids systems (electricity, gas, heat distribution and mobility) are built around a "smart thermal grid" connecting buildings, centralised plants and distributed heating and cooling producing units, including individual contributions from the connected buildings and Power to Gas storage (P2G). It has been demonstrated that reasonable investments in advanced heat distribution system could lead to substantial benefits for both the economy and individual consumers, with a break-even time shorter than 6 year.

Model Predictive Control Strategies for Polygeneration systems and microgrids

Ramanunni Parakkal Menon

Increasing electricity and thermal demand in all sectors, an increasing focus on the reduction in carbon emissions and use of nuclear power, advent of distributed generation and greater use of renewable technologies on an aging electrical and thermal grid system has necessitated the need for modern control and management systems. These new control and management systems need to be able to integrate new technologies, stochasticities and maximise the utilisation of the existing infrastructure while satisfying demands, without requiring complete overhaul of the pre-existing centralised grid system and the transmission and distribution systems. A model predictive control system has been proposed and demonstrated here which is able to create strategies for thermal and electrical systems such that the grid efficiency and security is maintained while minimising resource usage and emissions, while, simultaneously reducing the operating costs in the grid. The model predictive control(MPC) utilises a fully energetic approach for low-voltage microgrids and houses in the residential and commercial sector which comprises of CHP units, heat pumps, storage systems(electric and thermal) and stochastic renewable resources, while accounting for the varying dynamics of the electrical and thermal systems. Finally, validation of the MPC is performed on a testbed with physical units and building emulators which have access to meteorological and resource market data. The capability of the MPC to provide strategies for systems with photovoltaics (PV), heat pumps and CHP units is demonstrated. The MPC implementation developed is input into an optimal system design algorithm based on a multi-objective optimisation genetic algorithm developed for microgrids and urban systems/grids with end-users and polygeneration systems and storage devices. The optimal design of the system is so that the optimal sizes of the polygeneration systems can be identified. This will help in maximising the utilisation of heat pumps, storage devices and other systems in a LV microgrid equipped with an MPC-based thermo-electric energy management system. The work also aims to compare the cost effectiveness versus ability of thermal storage devices compared to electrical storage devices for the same grid in question.

EPFL2017

Thermoeconomic Analysis of a Solar Enhanced Energy Storage Concept Based on Thermodynamic Cycles

Samuel Henchoz

Large scale energy storage may play an increasingly important role in the power generation and distribution sector, especially when large shares of renewable energies will have to be integrated into the electrical grid. Up to now pumped-hydro is the only technology that has been widely used for that purpose. However the spread of this technology is limited by geographic constraints. In the present work, a particular implementation of the storage concept based on thermodynamic cycles, as introduced by ABB Switzerland ltd. Corporate Research, has been analysed thermoeconomically. This concept can be scaled up to a GWh range of stored energy, and is site independent. The underlying idea is to use electricity to power a heat pump transferring heat from a cold source to a hot source (charging mode), while storing the heat and the cold at both sources. Subsequently the energy that has been stored/removed to/from the hot/cold sources can be used to run a heat engine, hence re-delivering the electricity when it is needed (discharging mode). In the implementation presented here, using the ambient temperature as the hot source for both the heat pump and the heat engine allows taking benefit from daily variations of the atmospheric temperature. Indeed, the heat-pump can operate with a higher Coefficient of Performance (CoP) during the night and the heat-engine at higher efficiency during the day. This results in an effective increase of the ratio between the redelivered electricity (discharge) and the stored electricity (charging), compared to a situation where the hot source of both cycles are at the same temperature. The use of solar collectors is a further way to enhance this ratio by increasing the hot source temperature above the ambient temperature during the day. In charging mode, the system consists in an ammonia based Rankine heat pump interfaced at the evaporator with a latent heat cold storage, and at the condenser to the ambient through aircoolers. In discharging mode an ammonia based Rankine heat-engine is interfaced at the condenser with the latent heat cold storage, and the evaporator(boiler) of the thermal engine is interfaced with hot water produced by a field of flat plate solar collectors. A steady state multiobjective optimization of a 50 MW power output plant was carried out, with the objectives of minimizing the investment costs, and maximizing the ratio between electricity output and input. Several types of cold storage substances have been implemented in the formulation and two different types of solar collector were investigated. A storage efficiency of 57% at a cost of 1200 USD/kW was calculated for an optimized plant using solar energy. Finally, a computation of the behaviour of the plant along the year was carried out, reaching a yearly availability of 84.4%.

Pergamon-Elsevier Science Ltd2011

The Performance Optimization of a Gas Turbine Cogeneration / Heat Pump Facility with Thermal Storage

Vinicio Curti

With the push for greater energy conservation, the need for heating and/or power production is being filled by cogeneration facilities. Thus, the search for the best performance at the least cost for such multipurpose plants is made much more difficult by the fact that such facilities must meet differing goals or demands. Such a facility exists at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and has been studied in order to find the optimum modes of operation as a function of time for variations in both the heating and electrical demands this facility must meet. The results of this study are presented here. The plant itself provides heat and electricity for both the EPFL and the University of Lausanne and is projected to supply electricity to the exterior utility grid provided it can be shown to be economically viable. The plant’s primary components include two gas turbines, a heat recovery system, two heat pumps, a set of heat storage tanks, and both medium and low-temperature district heating networks. In order to find the optimum mode of operation, a mixed-integer linear programming approach was used, which balances the competing costs of operation and minimizes these costs subject to the operational constraints placed on the system. The effects of both the cost of the fuel and the costs of electricity sold and bought on the best performance of the system are evaluated. In addition, the important features of the modeling process are discussed, in particular the heat storage tanks, which complicate the optimization of the series of steady-state models used to model the overall quasi-steady-state behavior of the system.