Thermal energy storage, with its low energy storage cost and wide distribution in industrial processes, is an effective way to improve the operational flexibility of power plants. Due to colossal energy storage capacity and small deployment costs, this article proposes connecting district heating networks to combined cycle gas turbine (CCGT) plants as a thermal energy storage capacity, improving the flexibility of CCGTs. The main focus here is on developing an appropriate control strategy to effectively control the power-heat conversion, meet the heat and power demands of the connected network, and the operational flexibility of the plant. The major problem is that the intrinsic static and dynamic conversion relationship of power and heat in the CCGT and district heating network and the buildings are multi-factor interactive and unknown. Therefore, the CCGT bottom cycle and district heating network, and building models were built to obtain the power-heat conversion parameters and the dynamic model for control design. Then, the energy storage coefficient of 0.105 MW/kg/s is obtained through the model simulation instead of a complex thermodynamic calculation, corresponding to the 113.22 GJ energy storage capacity of the district heating network. Based on the obtained conversion rules, a new control strategy called ‘conversion coordinated control’ is designed and applied, using load signal decomposition and synergistic load response of flue gas mass flow rate and steam extraction valve. The simulation results show that the proposed method can promote a ramping load rate of 8.6 MW/min in the first 30 s with only 0.3 °C building temperature variation. The control strategy can effectively reduce the gap between the grid demand and CCGT power and ensure grid stability without compromising thermal users’ comfort.
The management of produced water (PW) discharges from offshore oil and gas installations in the North Atlantic is under the auspices of OSPAR (Oslo/Paris convention for Protection of the Marine Environment of the North-East Atlantic). In 2010, OSPAR introduced the Risk Based Approach (RBA) for PW management. The RBA includes a hazard assessment estimating PW ecotoxicity using two approaches: Whole Effluent Testing (WET) and Substance Based (SB). Set against the framework of the WET and SB approach, this study conducted a literature review on the magnitude and cause of PW ecotoxicity, respectively, and on the challenges of estimating these. A large variability in the reported magnitude of PW WET was found, with (E/L)C50-values ranging from 100% and a median of 11% (n=301). Metals, hydrocarbons, and production chemicals were identified as causing ecotoxicity across literature. However, this review reveals how knowledge gaps on PW composition and high sample- and species-dependency of PW ecotoxicity makes clear identification and generalization difficult. It also highlights how limitations regarding availability and reliability of ecotoxicity data result in large uncertainties in the subsequent risk estimates, which is not adequately reflected in the RBA output (e.g. environmental impact factors). Thus, it is recommended to increase the focus on improving ecotoxicity data quality before further use in the RBA, and that WET should play a more pronounced role in the testing strategy. To increase the reliability of the SB approach, more attention should be given to the actual composition of PW. Bioassay-directed chemical analysis, combining outcomes of WET and SB in toxicity identification evaluations, may hold the key to identifying drivers of ecotoxicity in PW. Finally, an uncertainty appraisal must be an integrated part of all reporting of risk estimates in the RBA, to avoid mitigation actions based on uncertainties rather than reliable ecotoxicity estimations.
This study exploits service modularity in front-end logistics services in e-fulfillment, from a customer-centric approach, particularly in order management, delivery, and return. Through an online survey of UK customers, the service priorities of 494 respondents via AHP (Analytic Hierarchical Process) were analyzed. Extracting customers' service priorities, ordering behavior, and demographic information as input data, the clustering algorithm KAMILA (KAy-means for MIxed LArge data sets) was further applied. The three identified customer clusters (multichannel shoppers, infrequent shoppers, and online fans) provide preliminary evidence on how commonality and variability aspects of service modularity in front-end logistics services can optimize the number of service options and their performance levels. Therefore, our study, building on value co-creation and modularity, proposes a systematic way of exploiting service modularity for the customer segmentation process that addresses heterogeneous customer preferences cost-efficiently and uncomplicatedly. Furthermore, we provide a framework for the governance of front-end logistics services, guiding outsourcing decisions. Accordingly, it reveals the implications of customer priorities and service decomposition logic choices on value creation. Finally, the propositions formulated aim to develop theoretical foundations for explaining how the heterogeneity in customer priorities for logistics services can be managed with modularity, creating value both for customers and retailers.
Decentralization of the electricity sector has mainly been studied in relation to its infrastructural aspect, particularly location and size of the generation units, and only recently more attention has been paid to the governance aspects. This article examines power sector (de)centralization operationalized along three functional dimensions: political, administrative and economic. We apply this framework to empirically assess the changes in California’s electricity market, which saw the emergence of institutional innovation in the form of community choice aggregation (CCA). Unpacking the Californian case illustrates how decision-making has moved from central state government and regulators to the municipal level in uneven ways and without decentralized generation keeping pace. We also explore the impacts this multidimensional and diversified decentralization has on the ultimate goals of energy transition: decarbonization and energy security. Our framework and empirical findings challenge the conventional view on decentralization and problematize the widespread assumptions of its positive influence on climate mitigation and grid stability.
This paper presents a new approach for estimating encountered wave elevation sequences by use of measured ship responses, where wind-waves and swell may come from different directions, i.e. bi-directional waves. The main assumption of the approach, making use of Prolate Spheroidal Wave Functions (PSWF), is that the wave field is represented by multi-directional irregular waves. Thus, combining available measured responses, the phases and amplitudes of the multi-directional irregular waves are derived as the solution, by which the wave profiles can be estimated. Numerical investigations using artificially generated response measurements (sway, heave, pitch, vertical bending moment) of a bulk carrier in uni-directional and bi-directional long-crested as well as short-crested sea states are made. It is shown that the present approach can accurately estimate wave elevation sequences in such sea states.
In a premixed dual-fuel (DF) methane-diesel engine, the ignition of the lean premixed methane/air mixture starts with the assistance of a pilot diesel injection. Auto-ignition of pilot fuel is important as it triggers the subsequent combustion processes. A delay in the auto-ignition process may lead to misfiring, incomplete combustion, and thus higher greenhouse emissions due to methane slip. Hence, a better understanding of the auto-ignition process for the pilot fuel can help to improve the overall engine performance, combustion efficiency, and to lower exhaust emission levels. In the present study, large eddy simulation (LES) is used to investigate the auto-ignition process of micro-pilot diesel in premixed DF combustion in a constant volume combustion chamber (CVCC). The entire DF combustion processes including methane gas injection, methane/air mixing, pilot diesel injection, and ignition are simulated. The numerical model is validated against experimental data. The present numerical model is able to capture the ignition delay time (IDT) within a maximum relative difference of 7% to the measurements. A higher relative difference of 38% is obtained when methane gas injection and mixing are omitted in the simulation and the methane/air is assumed homogeneous. This demonstrates the importance of inhomogeneity pockets. To study the effects of temperature and methane inhomogeneities separately, different idealized inhomogeneities in temperature and methane distribution are considered inside the CVCC. The inhomogeneity in the temperature is observed to have a more profound influence on the IDT than the methane inhomogeneity. The inhomogeneity pockets of temperature advance the first-stage ignition and, subsequently, the second-stage ignition. A sensitivity analysis on the effect of inhomogeneity wavelength reveals that the larger wavelengths enhance the combustion due to the presence of pilot diesel jets in the desirable regions for a longer time duration.
Havebrugsindustrien i nordiske lande er meget afhængig af drivhussystemer på grund af begrænsningen af det naturlige miljø og de strenge plantekrav for bestemte plantetyper. Kommercielle avlere i disse regioner støder på betydelige udfordringer med at garantere kvaliteten af planterne, mens de minimerer produktionsomkostningerne. På den ene side skal et drivhussystem forbruge en stor mængde energi for at give et tilfredsstillende klima for plantevækst. På den anden side, i de senere år, har energiprisen stigende i Europa ført til en stigning i produktionsomkostningerne for drivhuse, hvilket gør energibesparelse og optimering imperativ. Det er dog udfordrende for avlere at håndtere dette dilemma, fordi drivhusklimakontrol er et meget dynamisk og meget koblet komplekst system. Ved at analysere funktionerne i ikke-linearitet og dynamik i drivhusklimaet kan de eksisterende løsninger ikke korrekt opfylde de praktiske krav i gartneriindustrien.
For at tackle disse problemer foreslås en digital tvilling af drivhusklimakontrol (DT-GCC) rammer i denne forskning for at optimere aktuatorens driftsplan til minimering af energiforbrug og produktionsomkostninger uden at gå på kompromis med produktionskvaliteten. Arkitekturen i DT-GCC-rammen og de anvendte metoder er uddybet modulært, herunder fysisk tvilling af drivhusklimakontrol (PT-GCC) systemforståelse, design af DT-GCC-system, sammenkobling af DTGCC og PT-GCC og integration med andre digitale tvillinger (DTS).
DT-GCC omfatter en virtuel drivhus (VGH) og en multi-objektiv optimeringsbaseret klimakontrol (MOOCC) platform. VGH er den digitale repræsentation af det fysiske drivhus gennem modellering af de faktorer, der kan påvirke drivhusklimaet markant og aktuatorens driftsstrategier. MOOCC er ansvarlig for at definere drivhusklimakontrol som et multi-objektivt optimeringsproblem (MOO) og optimere driftsplanen for kunstigt lys (lysplan) og varmesystem (varmeplan). Desuden er en hierarkisk struktur af DT-GCC designet i henhold til funktionerne og ansvaret for individuelle lag, der gavner den praktiske realisering af DT-GCC med en organiseret arkitektur af design og styring.
Funktionaliteterne i DT-GCC er udviklet i en drivhusklimakontrolplatform, der er navngivet af Dynalight, som er kombineret med en genetisk algoritme (GA) ramme kaldet Controleum. Dynalight definerer et MOO -problem til at abstrahere drivhusklimakontrolsystemet med flere objektive funktioner, og omkostningerne beregnes baseret på modelleringsresultaterne fra VGH. Controleum er ansvarlig for implementeringen af GA for at generere en Pareto Frontier (PF) og endelig løsning af løsning til let plan og varmeplan.
Forskellige scenarier og tilsvarende eksperimenter er designet til at evaluere ydelsen af DT-GCC fra individuelle perspektiver, herunder VGH, MOOCC og DT-integration. Eksperimenterne på VGH verificerer forudsigelsesydelsen for kunstigt neuralt netværk (ANN) metoder på indendørs temperatur, opvarmning af forbrug og netto fotosyntese (PN). Hvad angår de to standaloneeksperimenter, garanterer resultaterne DT-GCCs evne til at kortlægge avlernes beslutningstagning om let plan og varmeplan og verificere MOOCC-ydelsen for at opfylde voksende krav og samtidig reducere energiforbruget og omkostningerne. Endelig, i DT-integrationseksperimenterne med Digital Twin of Production Twin (DT-PF) og Digital Twin of Energy System (DT-ES), afslutter DT-GCC det tilsvarende svar på forudsigelser og optimeringsanmodninger.
This work presents the verification and validation of the freely available simulation tool MoodyMarine, developed to help meet some of the demands for early stage development of MRE devices. MoodyMarine extends the previously released mooring module MoodyCore (Discontinuous Galerkin Finite Elements) with linear radiation-diffraction bodies, integrated pre-processing workflows and a graphical user interface. It is a C++ implementation of finite element mooring dynamics and Cummins equations for floating bodies with weak nonlinear corrections. A newly developed nonlinear Froude-Krylov implementation is verified in the paper, and MoodyMarine is compared to CFD simulations for two complex structures: a slack-moored floating offshore wind turbine and a self-reacting point-absorber with hybrid mooring.
High-fidelity models become more and more used in the wave energy sector. They offer a fully nonlinear simulation tool that in theory should encompass all linear and nonlinear forces acting on a wave energy converter (WEC). Studies using high-fidelity models are usually focusing on validation of the model. However, a validated model does not necessarily provide reliable solutions. Solution verification is the methodology to estimate the numerical uncertainties related to a simulation. In this work we test four different approaches: the classical grid convergence index (GCI); a least-squares version (LS-GCI); a simplified version of the least-square method (SLS-GCI); and the ITTC recommended practice. The LS-GCI requires four or more solutions whereas the other three methods only need three solutions. We apply these methods to four different high-fidelity models for the case of a heaving sphere. We evaluate the numerical uncertainties for two parameters in the time domain and two parameters in the frequency domain. It was found that the GCI and ITTC were hard to use on the frequency domain parameters as they require monotonic convergence which sometimes does not happen due to the differences in the solutions being very small. The SLS-GCI performed almost as well as the SL-GCI method and will be further investigated.
Savonius hydrokinetic turbines (SHTs), categorized as emerging cyclic-type wave energy converters (WECs), have demonstrated notable potential in achieving elevated energy conversion efficiency and consistent power output. This performance is particularly observed when operating under the initial phase-locked strategy (IPLS), marking a significant advancement in the realm of wave energy harvesting. However, a thorough exploration of the influences stemming from wave conditions and turbine design remains an area that warrants further investigation for advancing the performance of SHT-WECs under the proper operational strategy. This study undertakes an exhaustive analysis of geometric parameters, encompassing turbine diameter, blade number, and thickness. An experiment-validated numerical model based on the unsteady two-phase Reynolds-averaged Navier-Stokes equations is adopted in the research. Comprehensive investigations include analyzes of flow fields around the turbine, pressure distributions on blade surfaces, and dynamic torque variations. These analyzes serve to elucidate the variation rules of hydrodynamic characteristics and their influential mechanisms. The results highlight the notable impact of the proposed "relative-short wavelength impact" on the performance of SHT-WECs operating under IPLS conditions. Notably, no significant impact is observed when the relative wavelength exceeds 17. Optimal performance is achieved with the thinnest and two-bladed turbine configuration. Moreover, optimizing the turbine diameter significantly enhances SHT-WEC conversion efficiency, with the attained maximum value reaching approximately 18.6%. This study offers a concise guideline for designing turbine diameters in alignment with specific wave conditions.