Load modulation strategies of residential heat pumps for demand-response programs with different thermal storage options

This research work presents a methodology to assess the potential of load modulation strategies of HVAC systems for demand response programs at different scales. Two different demand response programs are considered: feed-in tariff signals for renewable production load matching and signals from the distribution grid operator for operational planning and congestion management at the distribution level. The resulting control problems are solved using optimal control formulations. First, the strategies are applied to four typical Belgian houses to match on-site PV production. Different thermal storage options are considered: on the one hand, thermal storage in the building envelope and in water tanks for domestic hot water, and, on the other hand, additional water tanks for space heating needs either in a parallel four-pipe or in a parallel two-pipe configuration. According to the type of house and the modulation strategy considered, a ranking of the most suitable storage option is proposed. Secondly, the method is extended to the scale of a distribution feeder with 50% PV penetration rate. Results show that with 20% heat pump penetration with suitable storage options, residual load reduction reach 28 to 73.4% with ADR#1 and 43.7 to 51.4% with ADR#2. ADR#1 outperforms ADR#2 for short modulation intervals, but can lead to up to 70% additional overconsumption if the chosen thermal storage option is not adapted to the house insulation level

Aggregation of flexible domestic heat pumps for the provision of reserve in power systems

The integration of renewable energy sources in the electricity production mix has an important impact on the management of the electricity grid, due to their intermittency. In particular, there is a rising need for flexibility, both on the supply and demand sides. This paper assesses the amount of flexibility that could be reserved from a set of flexible residential heat pumps in a given geographical area. It addresses the problem of a load aggregator controlling a set of heat pumps used to provide both space-heating and domestic hot water. The flexibility of the heat pumps is unlocked in order to reduce electricity procurement costs in the day-ahead electricity market, while ensuring the provision of a predefined amount of reserve for real-time grid management. The objective of the paper is two-fold. On the one hand, an aggregation method of large sets of heat pumps based on physics-based models and random sampling techniques is proposed. On the other hand, a combined optimization problem is formulated to determine both the optimal electricity demand profile to be bought on the day-ahead market and the cost associated to the reservation of a defined amount of power. The method is applied to a set of 40000 residential heat pumps in Belgian houses. Results show that these houses can provide up to 100MW of upward reserve for 50% of the current costs. The provision of downward reserve at competitive cost is hampered by significant overconsumption

Design of a small-scale organic Rankine cycle engine used in a solar power plant

peer reviewedUnder the economic and political pressure due to the depletion of fossil fuels and global warming concerns, it is necessary to develop more sustainable techniques to provide electrical power. In this context, the present study aims at designing, building and testing a small-scale organic Rankine cycle (ORC) solar power plant ( 3 kWe) in order to define and optimize control strategies that could be applied to larger systems. This paper presents a first step of the design of the solar power plant and focuses more specifically on the ORC engine. This design is defined on the basis of simulation models of the ORC engine and takes into account some technical limitations such as the allowed operating ranges and the technical maturity of the components. The final configuration includes a diaphragm pump, two plate heat exchangers for the regenerator and the evaporator, an air-cooled condenser, two hermetic scroll expanders in series and R245fa as the working fluid. Simulations indicate that an efficiency close to 12% for the ORC engine can be reached for evaporating and condensing temperatures of 140 and 358C, respectively

ORCSim: a generalized Organic Rankine cycle simulation tool

An increasing interest in organic Rankine cycle (ORC) technology has led to numerous simulation and optimization studies. In the open-literature different modeling approaches can be found, but general software tools available to the academic/industrial community are limited. A generalized ORC simulation tool, named ORCSim, is proposed in this paper. The framework is developed using object-oriented programming that easily allows improvements and future extensions. Currently two cycle configurations are implemented, i.e. a basic ORC and an ORC with liquid-flooded expansion. The software architecture, the thermo-physical property wrappers, the component library and the solution algorithm are discussed with particular emphasis on the ORC with liquid-flooded expansion. A thorough validation both at component and cycle levels is proposed by considering the aforementioned cycle architectures

Smart Grid Energy Flexible Buildings through the use of Heat Pumps in the Belgian context

The management of electricity grids requires the supply and demand of electricity to be in balance at any point in time. To this end, electricity suppliers have to nominate their electricity bids on the day-ahead electricity market such that the forecasted supply and demand are in balance. At the intraday-level, mismatches between the forecasted and actual supply and demand can be compensated for by reserve capacity or by real-time demand response. In this context, there are three ways to minimize the cost of electricity supply. A first one is to predict electricity demand profiles associated to local consumers equipped with smart metering devices as accurately as possible. A second one is to minimize the procurement costs of electricity by shifting flexible loads from peak to off-peak hours. This can be done by offering consumers time-of-use (ToU) variable electricity tariffs as an incentive to shift their demand. A third one is to minimize the imbalance costs resulting from mismatches between forecasted supply and demand, by real-time demand response. Smart control of HVAC equipment with embedded model predictive control (MPC) can be used in that context. They have to be provided with dynamic building simulation models. The first part of this study provides typologies of Smart Grid Energy ready Buildings within the context of the Belgian building stock. A typical new residential building is considered, equipped with an air-to-water heat pump that supplies either radiators or a floor heating system. Different occupancy profiles are considered as well as three heating control strategies guaranteeing equivalent thermal comfort. The flexibility is assessed according to a cost-weighted electricity consumption of the heat pump. The impact of building thermal mass storage on the electricity consumption is also evaluated. A ranking of the building characteristics affecting its flexibility is deduced as well as recommendations to avoid overconsumption associated to energy storage. The second part of this study assesses the flexibility potential of these Smart Grid Energy Ready Buildings within the context of the Belgian day-ahead electricity market. Flexibility will be quantified in terms of load volumes shifted and in terms of procurement costs avoided. The methodology implemented considers both the energy supplier and the end-user. On the electricity suppliers’ side, a ToU-price profile is determined based on an analysis of the day-ahead electricity prices in Belgium (Belpex power exchange, 2008-2012). On the consumers’ side, this ToU-profile serves as an input for the local heat pump controller. This controller uses MPC to determine the heat pump power profile for the next day such that thermal comfort is guaranteed at minimal energy cost. The study will be generalized to the intraday and real time markets in future work

Development and a Validation of a Charge Sensitive Organic Rankine Cycle (ORC) Simulation Tool

Despite the increasing interest in organic Rankine cycle (ORC) systems and the large number of cycle models proposed in the literature, charge-based ORC models are still almost absent. In this paper, a detailed overall ORC simulation model is presented based on two solution strategies: condenser subcooling and total working fluid charge of the system. The latter allows the subcooling level to be predicted rather than specified as an input. The overall cycle model is composed of independent models for pump, expander, line sets, liquid receiver and heat exchangers. Empirical and semi-empirical models are adopted for the pump and expander, respectively. A generalized steady-state moving boundary method is used to model the heat exchangers. The line sets and liquid receiver are used to better estimate the total charge of the system and pressure drops. Finally, the individual components are connected to form a cycle model in an object-oriented fashion. The solution algorithm includes a preconditioner to guess reasonable values for the evaporating and condensing temperatures and a main cycle solver loop which drives to zero a set of residuals to ensure the convergence of the solution. The model has been developed in the Python programming language. A thorough validation is then carried out against experimental data obtained from two test setups having different nominal size, working fluids and individual components: (i) a regenerative ORC with a 5 kW scroll expander and an oil flooding loop; (ii) a regenerative ORC with a 11 kW single-screw expander. The computer code is made available through open-source dissemination

Genome-wide analysis of Brucella melitensis genes required throughout intranasal infection in mice

Brucellae are facultative intracellular Gram-negative coccobacilli that chronically infect various mammals and cause brucellosis. Human brucellosis is among the most common bacterial zoonoses and the vast majority of cases are attributed to B .melitensis .Using transposon sequencing (Tn-seq) analysis, we showed that among 3369 predicted genes of the B .melitensis genome, 861 are required for optimal growth in rich medium and 186 additional genes appeared necessary for survival of B .melitensis in RAW 264.7 macrophages in vitro .As the mucosal immune system represents the first defense against Brucella infection, we investigated the early phase of pulmonary infection in mice. In situ analysis at the single cell level indicates a succession of killing and growth phases, followed by heterogenous proliferation of B .melitensis in alveolar macrophages during the first 48 hours of infection. Tn-seq analysis identified 94 additional genes that are required for survival in the lung at 48 hours post infection. Among them, 42 genes are common to RAW 264.7 macrophages and the lung conditions, including the T4SS and purine synthesis genes. But 52 genes are not identified in RAW 264.7 macrophages, including genes implicated in lipopolysaccharide (LPS) biosynthesis, methionine transport, tryptophan synthesis as well as fatty acid and carbohydrate metabolism. Interestingly, genes implicated in LPS synthesis and β oxidation of fatty acids are no longer required in Interleukin (IL)-17RA -/- mice and asthmatic mice, respectively. This demonstrates that the immune status determines which genes are required for optimal survival and growth of B .melitensis in vivo .info:eu-repo/semantics/publishe

Microbial Ecology of French Dry Fermented Sausages and Mycotoxin Risk Evaluation During Storage

Dry fermented sausages are produced worldwide by well-controlled fermentationprocesses involving complex microbiota including many bacterial and fungal species with key technological roles. However, to date, fungal diversity on sausage casings during storage has not been fully described. In this context, we studied the microbial communities from dry fermented sausages naturally colonized or voluntarily surface inoculated with molds during storage using both culture-dependent and metabarcoding methods. Staphylococci and lactic acid bacteria largely dominated in samples, although some halotolerant genera (e.g., Halomonas, Tetragenococcus, and Celerinatantimonas spp.) were also frequently observed. Fungal populations varied from 7.2 to 9.8 log TFU/cm2 sausage casing during storage, suggesting relatively low count variability among products. Fungal diversity identified on voluntarily inoculated casings was lower (dominated by Penicillium nalgiovense and Debaryomyces hansenii) than naturally environment-inoculated fermented sausages (colonized by P. nalgiovense, Penicillium nordicum, and other Penicillium spp. and sporadically by Scopulariopsis sp., D. hansenii, and Candida zeylanoïdes). P. nalgiovense and D. hansenii were systematically identified, highlighting their key technological role. The mycotoxin risk was then evaluated, and in situ mycotoxin production of selected mold isolates was determined during pilot-scale sausage productions. Among the identified fungal species, P. nalgiovense was confirmed not to produce mycotoxins. However, some P. nordicum, Penicillium chrysogenum, Penicillium bialowienzense, Penicillium brevicompactum, and Penicillium citreonigrum isolates produced one or more mycotoxins in vitro. P. nordicum also produced ochratoxin A during pilotscale sausage productions using “worst-case” conditions in the absence of biotic competition. These data provide new knowledge on fermented sausage microbiota and the potential mycotoxin risk during storage