Maximum Energy Demand Research Articles

Inelastic response spectra for an integrated displacement and energy-based seismic design (DEBD) of structures

The severe socio-economic impact of recent earthquakes has further highlighted the crucial need for a paradigm shift in performance-based design criteria and objectives towards a low-damage design philosophy, in order to reduce losses in terms of human lives, repair/reconstruction costs, and recovery time (deaths, dollars and downtime). Currently, displacement-based parameters are typically adopted to design/assess the seismic performance of the structures, by limiting the maximum displacement or the maximum interstorey drift ratio (IDR) reached by the structure under different earthquake intensities. However and arguably, displacement-based quantities are characterized by inherent weaknesses, since, for instance, they are not cumulated parameters, thus not able to capture directly the effects of multiple cycles, deterioration and damage cumulation. Therefore, in the last decades, energy-based approaches were investigated and developed in order to establish alternative engineering demand parameters for the assessment of post-event damage through a dynamic energy balance. Towards the main goal of developing an integrated Displacement and Energy-Based Design/assessment procedure (DEBD) for actual use in practice, this research work proposes an innovative approach based on the use of inelastic spectra correlating the energy components with the corresponding maximum displacement response parameters of the structure. In practical terms, the proposal is to further integrate and develop the well-known Direct Displacement-Based Design, by directly adopting the hysteretic energy as an additional design parameter. The energy inelastic spectra are developed through an extensive parametric analysis of Single-Degree-of-Freedom (SDoF) systems, with different nonlinear hysteretic models. In such an approach, the maximum seismic energy demand imparted to a structure can be directly predicted and controlled, whilst distinguishing the various components of the energy balance, including the hysteretic one. The effects of near-field and far-field earthquakes are also investigated. Results show that in the first case the seismic demand is concentrated in the peak of a few large cycles that absorb the demand energy induced by the high component in peak ground velocity in the second case the higher equivalent number of plastic cycles tends to become critical for structures with inadequate structural details and prone to suffer by cumulative cycles and overall plastic fatigue mechanisms.

Process optimization for drying of Shrimp (Metapenaeus dobsoni) under hot air‐assisted microwave drying technology using response surface methodology

AbstractThe study was carried out to optimize the drying conditions of shrimp in the hot air‐assisted microwave drying system using response surface methodology. The drying experiments were performed using a Box–Behnken design with air temperature (50–70°C), air velocity (.5–1.5 m/s), and microwave power level (600–1000 W) as independent variables and drying time, water activity, and rehydration ratio as independent variables. The obtained response variables were fitted into the various regression equations to predict a suitable model. The methodology of desired function was applied to indicate 61.74°C air temperature, 922.61 W microwave power, and 1.0 m/s air velocity which offered a reduced drying time of 2.8 h, the water activity of .424 and improved rehydration ratio of 2.51, respectively with a desirability value of .949. The moisture content, drying efficiency, shrinkage, and total color change were determined for the samples obtained under optimized conditions and were observed as 16.5% (w.b), 35.71%, 14.14%, and 16.95 ± 2.14, respectively. Scanning electron microscopy analysis of dried shrimp showed the formation of pores of diameters ranging from 3.17 to 10.6 μm. The process parameters optimized under the study for hot air‐assisted microwave drying can be used for the production of good‐quality dried shrimps.Practical applicationsGenerally, fish and fish products are dried in the open sun or solar dryers in most developing countries. The traditional methods offer the least process controls with maximum energy and manpower demand to meet the ever‐growing industry requirements with increased awareness of the safety and quality of the dried products. The hot air‐assisted microwave (HAMW) drying system developed under the study could have complete control over the process parameters without compromising the quality of the dried product. The study suggests the HAMW drying system as a potential means of drying technique for large‐scale commercial production of dried shrimps.

Assessment of building energy performance integrated with solar PV: Towards a net zero energy residential campus in India

Building Applied Photovoltaics (BAPV) such as Roof-top Solar PV has gained significant attention in recent years for harnessing the untapped potential of renewable energy sources. However, rooftop PV poses hurdles of space restriction and shadowing in densely packed urban residential neighborhoods. This study aims to design and assess the feasibility of an integrated grid-connected Rooftop and Façade Building Integrated Photovoltaic (BIPV) for meeting the energy demand of residential buildings on an academic campus. Three distinctive groups of residential typologies have been investigated in this study, categorized based on built area and occupants’ past energy usage. Additionally, the variation in the measured Energy Performance index of the three different residential groups is illustrated to pave the path for the development of a typology-based residential energy benchmarking and labelling system. The Solar PV system has been designed for the maximum household energy demand recorded in CoVID-affected years due to high residential electricity usage in this period. The study showcases that integration of façade BIPV for low-rise residential buildings increases the system energy production to up to 62.5 % based on the utilized surface area for active PV. Furthermore, the Net Zero Energy Building (ZEB) potential for each typology has been achieved by integration of the proposed Solar PV, evaluated as a function of the Energy Performance Index (EPI) and Energy Generation Index (EGI). The designed nominal PV power of the proposed grid-connected plant is 5.6 MW, producing 7182 MWh annually, meeting the maximum residential energy demand in the studied academic campus in CoVID affected year.

Technical Energy Assessment and Sizing of a Second Life Battery Energy Storage System for a Residential Building Equipped with EV Charging Station

This study investigates the design and sizing of the second life battery energy storage system applied to a residential building with an EV charging station. Lithium-ion batteries have an approximate remaining capacity of 75–80% when disposed from Electric Vehicles (EV). Given the increasing demand of EVs, aligned with global net zero targets, and their associated environmental impacts, the service life of these batteries, could be prolonged with their adoption in less demanding second life applications. In this study, a technical assessment of an electric storage system based on second life batteries from electric vehicles (EVs) is conducted for a residential building in the UK, including an EV charging station. The technical and energy performance of the system is evaluated, considering different scenarios and assuming that the EV charging load demand is added to the off-grid photovoltaic (PV) system equipped with energy storage. Furthermore, the Nissan Leaf second life batteries are used as the energy storage system in this study. The proposed off-grid solar driven energy system is modelled and simulated using MATLAB Simulink. The system is simulated on a mid-winter day with minimum solar irradiance and maximum energy demand, as the worst case scenario. A switch for the PV system has been introduced to control the overcharging of the second life battery pack. The results demonstrate that adding the EV charging load to the off-grid system increased the instability of the system. This, however, could be rectified by connecting additional battery packs (with a capacity of 5.850 kWh for each pack) to the system, assuming that increasing the PV installation area is not possible due to physical limitations on site.

A priority-based approach for peer-to-peer energy trading using cooperative game theory in local energy community

The energy sector is undergoing a paradigm shift to integrate the increasing volume of embedded renewable energy generation and create Local Energy Communities (LEC). Peer-to-Peer (P2P) energy trading is an encouraging paradigm used to increase usage of renewable energy, decrease consumers' electricity bills, and provide revenue to prosumers. It also improves the usage of Distributed Energy Resources (DERs) in the smart grid and reduces transmission and distribution losses. However, challenges such as unpredictability and intermittency of DER's may result in instability of P2P energy trading. In our work, we propose a cooperative game theory framework to expedite stable trading algorithms and incentivize individual users. This trading algorithm offers various priorities at each time interval depending on parameters such as geographic location, maximum energy demand, maximum energy generated, and pricing mechanism. We have considered a grand coalition whose objective is to maximize the coalition's social welfare and ensure a win-win approach for both consumers and prosumers. Hence the grand coalition made by the cooperative game is in Nash equilibrium as no peer wants to perform the merge and split from its current location. In the proposed algorithm, LEC includes 100 players (50 prosumers and 50 consumers), a community energy storage system (CES), and 15 Electric Vehicle charging points. The best operational output priority was also evaluated in this work for each time interval with associated distributed solar PV and CES. Results strongly support that using the best suitable priority for each time interval is beneficial rather than having one priority for an entire day. An economic analysis to distribute the revenue generated from the grand coalition in a fair manner is analyzed in this work. From the economic evaluation, it is apparent that prosumers have high revenue, and consumers save electricity bills when using the proposed algorithm.

Potential evaluation and analysis of near-to-net zero energy building in hot and dry climate

• Near-to-net zero energy building in hot and dry climate has been investigated. • NZEBs model has been developed and simulated using TRNSYS models/components. • Space cooling, space heating, and electrical energy outcomes was developed. • Maximum reduction rate ratio in energy demand 48.2% was achieved. In a hot and dry climate like the weather of Iraq, near-to-net zero energy buildings (NNZEBs) can become one of the effective solutions to reduce energy demands in the residential buildings sector. Therefore, the current work aims to cornerstone of the developed solution combined the different scenarios for residential building with a total living area of 240 m 2 has been considered. The investigated scenarios include different building constructions, orientations, control strategies, and using solar PV panels as renewable energy techniques. The proposed scenarios have been developed and simulated using TRNSYS models/components. The energy demand for space cooling, space heating, and electrical energy outcomes from an NNZEB model was developed using the TRNSYS simulation workspace. The data input of the residential multi-zone building envelope is configured using TRNBuild (i.e., building simulation software) and then introduced into TRNSYS. Moreover, the solar PV panels tool is developed in TRNSYS to evaluate the impact of renewable energy on energy consumptions. A full cost analysis of the energy consumption has been carried out to see if this technology is viable. In terms of maximum energy demand, the preliminary building requires 340 kWh/m 2 per year as a cooling demand compared with 65 kWh/m 2 per year as a heating demand. The results showed that the maximum reduction rate in energy demand for cooling demand of 33.9% was achieved by changing the construction, ventilation, and control systems. The scenarios of using double glaze and insulating the building showed the most significant impact on the reducing of energy demand with a total reduction rate ratio of 34.40% compared with other scenarios. From economic analysis, it can be concluded that the increase in the energy tariff led to an increase in the yearly energy cost for the preliminary building without solar PV panels. The results highlighted that the effects of key investigated scenarios should be considered in combination through a parametric investigation.

A methodological framework for optimal siting of offshore wind farms: A case study on the island of Crete

Land-use conflicts, along with the increasing demand for green energy and the unexploited offshore wind potential, intensify the necessity of the development of Offshore Wind Farms (OWFs). Their sustainable siting remains still a research gap to be further analysed due to: (i) the need of the insular energy self-efficiency; the great distances from the mainland); (ii) the freeing of land; and (iii) the high unexploited offshore wind potential.The Analytical Hierarchy Process method and Geographic Information Systems incorporating 14 exclusion and 16 evaluation criteria are employed tο identify sustainable siting. This research integrates the opinions of a wide range of local stakeholders and experts, considering the insular specific characteristics of Crete. The high suitable marine areas are evaluated according to their energy capacity, assessed with seven different commercially available models.Most respondents estimate that the distance from environmental interest areas is the most critical criterion. The analysis proved that the final available areas for OWFs siting are 205.5 km2; 126.25 km2 of high suitability with a high potential of 620–900 MW. Since the maximum annual energy demand of the island amounted to 676 MW (2019) this demand could actually be overcovered by four main OWFs near the island.

Climate-driven variability in the context of the water-energy nexus: A case study in southern Portugal

Research on climate-driven variability in the water and energy sectors is required to drive adaptative policies to climate change and boost cross-sectorial synergies. This study addresses the role of the North Atlantic Oscillation (NAO) and East Atlantic pattern (EA) on the water-energy nexus in southern Portugal (Algarve region) from the point of view of water demand, instead of the usual point of view of hydropower production. Water at surface reservoirs and aquifers and solar and wind energy potentials (SP and WP, respectively) do not share the same dominant variability scales, but their interrelationships have implications for leveraging the use of renewable energy in the water sector, particularly through water pumping efficiency gains. Water availability is dominated by interannual fluctuations (70% of the total variance), whereas SP and WP are characterized by seasonal variability scales (98% and 41% of the total variance, respectively). At interannual scales NAO is the main driver of low-frequency variability governing cycles in the 6–8 -year band, whereas fluctuations in the 2–4 -year band are mainly associated with EA. Coupling or synchronizations between opposite phases of NAO and EA correspond to extremes in water availability. Minimum water levels in the summer and during droughts, corresponding to maximum energy demand in the water sector, are clearly connected to synchronized positive NAO and negative EA phases in the preceding winter. Recent advances in the seasonal and long-term predictability of NAO and EA climate patterns can help to improve drought resilience and groundwater sustainability and have huge potential benefits for the water-energy nexus in the Algarve region. Finally, to decarbonize freshwater supply in the Algarve, policy instruments will need to account for unregulated pumping which enables conditions for groundwater depletion, encourage energy and water management integration, and explore innovative energy investments.

Forecasting the Electricity Demand with Increasing Population by Using System Dynamic Approach - A Case Study of Karnal City (India)

Electricity has become an important source of energy in human society. The enormous use of electricity necessitates a mechanism to predict future demand. Modelling and simulation of electricity markets have increasingly involved the use of a System Dynamics (SD) approach. The basis for population growth and policy option scenario is the variation in birth, death and migration rates. Accordingly, the resulting dynamic hypothesis and the stock-flow structures are represented and simulated using software such as Stella. The present study has been undertaken to assess the future electricity demand and the population dynamics in Karnal city (Haryana), India, covering an area of 90.4 km2 with a population of 0.28 million. The System Dynamic Approach (Stella version 9.1) was successfully used to predict the future energy demands versus population growth dynamics in five modified scenarios (MS-I, MS-II, MS-III, MS-IV and MS-V) apart from the baseline scenario. The MS – IV was found to be the best scenario, as this scenario projects the stabilized population in the Karnal city, giving an edge over the other four modified scenarios policies. In this case, the population would rise to 0.46 million (2041) from 0.28 million (2011), while the energy demand will rise to 559 Gwh (2041) from 346 Gwh showing an increase of 213 Gwh (38%) over 30 years. The MS – I was found to be very critical, as the maximum energy demand was found to be very high (668 Gwh) with a total raise of 322 Gwh (48%).

Foraging conditions for breeding penguins improve with distance from colony and progression of the breeding season at the South Orkney Islands

BackgroundAccording to central place foraging theory, animals will only increase the distance of their foraging trips if more distant prey patches offer better foraging opportunities. Thus, theory predicts that breeding seabirds in large colonies could create a zone of food depletion around the colony, known as “Ashmole’s halo”. However, seabirds’ decisions to forage at a particular distance are likely also complicated by their breeding stage. After chicks hatch, parents must return frequently to feed their offspring, so may be less likely to visit distant foraging patches, even if their quality is higher. However, the interaction between prey availability, intra-specific competition, and breeding stage on the foraging decisions of seabirds is not well understood. The aim of this study was to address this question in chinstrap penguins Pygoscelis antarcticus breeding at a large colony. In particular, we aimed to investigate how breeding stage affects foraging strategy; whether birds foraging far from the colony visit higher quality patches than available locally; and whether there is evidence for intraspecific competition, indicated by prey depletions near the colony increasing over time, and longer foraging trips.MethodsWe used GPS and temperature-depth recorders to track the foraging movements of 221 chinstrap penguins from 4 sites at the South Orkney Islands during incubation and brood. We identified foraging dives and calculated the index of patch quality based on time allocation during the dive to assess the quality of the foraging patch.ResultsWe found that chinstrap penguin foraging distance varied between stages, and that trips became shorter as incubation progressed. Although patch quality was lower near the colony than at more distant foraging patches, patch quality near the colony improved over the breeding season.ConclusionsThese results suggest chinstrap penguin foraging strategies are influenced by both breeding stage and prey distribution, and the low patch quality near the colony may be due to a combination of depletion by intraspecific competition but compensated by natural variation in prey. Reduced trip durations towards the end of the incubation period may be due to an increase in food availability, as seabirds time their reproduction so that the period of maximum energy demand in late chick-rearing coincides with maximum resource availability in the environment. This may also explain why patch quality around the colony improved over the breeding season. Overall, our study sheds light on drivers of foraging decisions in colonial seabirds, an important question in foraging ecology.

Oxygen supply capacity breathes new life into critical oxygen partial pressure (Pcrit).

The critical oxygen partial pressure (Pcrit), typically defined as the PO2below which an animal's metabolic rate (MR) is unsustainable, is widely interpreted as a measure of hypoxia tolerance. Here, Pcrit is defined as the PO2at which physiological oxygen supply (α0) reaches its maximum capacity (α; µmol O2 g-1h-1kPa-1). α is a species- and temperature-specific constant describing the oxygen dependency of the maximum metabolic rate (MMR=PO2×α) or, equivalently, the MR dependence of Pcrit (Pcrit=MR/α). We describe the α-method, in which the MR is monitored as oxygen declines and, for each measurement period, is divided by the corresponding PO2to provide the concurrent oxygen supply (α0=MR/PO2). The highest α0 value (or, more conservatively, the mean of the three highest values) is designated as α. The same value of α is reached at Pcrit for any MR regardless of previous or subsequent metabolic activity. The MR need not be constant (regulated), standardized or exhibit a clear breakpoint at Pcrit for accurate determination of α. The α-method has several advantages over Pcrit determination and non-linear analyses, including: (1) less ambiguity and greater accuracy, (2) fewer constraints in respirometry methodology and analysis, and (3) greater predictive power and ecological and physiological insight. Across the species evaluated here, α values are correlated with MR, but not Pcrit. Rather than an index of hypoxia tolerance, Pcrit is a reflection of α, which evolves to support maximum energy demands and aerobic scope at the prevailing temperature and oxygen level.

Renewable Wave Energy Potential for the Sustainable Offshore Oil Platforms in South China Sea

The Jacket platform needs gas and diesel to run its turbines, and in the end, they produce catastrophic emissions annually. The environmental concerns regarding these platforms have forced us to utilize an alternative source of energy that is sustainable and clean. In this study 51 locations, are of interest where oil and gas activities are in progress at present in the shape of a jacket platform or pipelines. The significant wave height and wave period scatter diagram data are collected from the platforms in the South China Sea. The linear wave theory is used to find the wave power. The given time period is converted into an equivalent time period first before wave energy is determined. The study shows that location no. 20 is the ideal location to deploy the wave energy converter Pelamis P2 with a potential mean wave power of 6.61 kW/m A single unit of Pelamis P2 can produce on an average electricity output of 91.37 kW/m including, the losses and machine efficiencies, whereas a wave farm can generate an average output of 62 GWh/yr. The electricity supply of 70.3 % of the minimum and 14.1 % of the maximum energy demand, while using only wave energy converter. If hybrid wind and wave energy system is used, then energy production will increase. The results show that the wave farm could also reduce the use of natural gas up to 17.6E06 m3/year, avoiding the emission of 12000 tonnes of CO and 54000 tonnes of NOx annually, and can save up to RM 20 billion annually with the reduction of natural gas emissions.

Towards a sustainable 2022 FIFA World Cup in Qatar: Evaluation of wind energy potential for three football stadiums

This study analyzes the feasibility of satisfying the demand of three Football Stadiums for the 2022 FIFA World Cup in Qatar, using the wind’s kinetic energy. For all three selected locations (Lusail, Al Rayyan, and Al Wakrah), the wind potentiality is calculated through an environmental parameters study, from which the wind power density is obtained. Furthermore, a commercial wind turbine with proper characteristics is selected, and the same case study for each location is presented, to quantify the capacity that wind energy offers for satisfying the maximum energy demand of each associated stadium. In addition, the environmental benefits and the time required by each wind farm to satisfy the energy demand are computed. The results reveal that the conditions enable the use of wind energy for this purpose, based on a 5.06 m/s, 4.63 m/s, and 5.18 m/s velocity mean for Lusail, Al Rayyan, and Al Wakrah, respectively; from which values of 187.49 W/m2, 150.96 W/m2, and 187.29 W/m2 of wind power density are obtained. Also, the proposed wind farms could produce 69,952.56 MWh/year, 59,550.19 MWh/year, and 75,333.70 MWh/year, respectively. Moreover, the wind farms should produce energy for a period of 5.64 h, 4.41 h, and 5.23 h, to satisfy the maximum demand by a football match in its associated location. Additionally, to avoid the implementation of a storage system, the electricity obtained from the wind is connected to the power grid, decreasing the quota of fossil fuel power plants. In consequence, Qatar will eliminate the emissions of approximately 23.376 tons of CO2 in total per trio of matches held in these stadiums. Finally, a post 2022 FIFA World Cup scenario is analyzed, obtaining a positive outcome from both environmental and economic perspectives, in which an average of 14,675 tons of CO2 and 6.03 Million US$ can be saved annually.

Performance of peak shaving policies for quay cranes at container terminals with double cycling

Double cycling is used to improve the efficiency of quay cranes (QCs). However, higher QCs utilization increases the highest observed peak power demand of QCs, leading to a higher energy-related costs. Thus, this paper investigates the opportunities for peak shaving the power demand of QCs with double cycling by limiting the number of lifting QCs or the maximal energy demands of QCs. And some evaluation indicators are selected for assessment including the observed peak power demand, the productivity and utilization of QCs and the average waiting time of yard trucks (YTs). Considering the complexity and uncertainty of container terminals, this study establishes an agent-based simulation model to describe the operation processes of QCs, YTs and yard cranes (YCs), and visualize the power demands of QCs with double cycling. Finally, a series of computational experiments are carried out to explore the possibility of peak shaving the energy demand of QCs. The results show that both peak shaving policies are capable to reduce the power peaks of QCs with double cycling. And the policy of limiting maximal energy demands of QCs performs better which reduces the maximum energy demand as well as protecting electrical equipment without compromising higher QCs’ productivity. And the established agent-based simulation model can provide decision support for terminal operators to manage their energy consumption more smartly.

Multivariable interactions in simulation-based energy-saving glass roof designs

Energy-saving has been a central point considered in green architectural designs and researches for decades. However, in the majority of previous studies, the variables in energy-efficient building designs were treated separately by using bivariate-orthogonal methods, and the effects of multivariable interactions were largely neglected. This study focused on the impact and relationships of multiple design factors in three classical glass roof forms (flat, arch and zigzag) in Nanjing, China. Architectural features including glass roof shape flatness, glazing orientation, glazing distribution, glazing material properties were parameterized. The response surface methodology was applied to the simulation design, mathematical model generation and optimization. This study revealed that when compared to the maximum energy demand, up to 87%, 92% and 89% of total energy demand could be saved in the flat, arch and zigzag glass roof designs, respectively. Moreover, in hot summer/cold winter climate regions like the city Nanjing, glazing material properties (U and Tvis) and shape flatness (tan α) had significant impacts on energy demands while glass roof glazing orientation could be neglected. Although generally a glass roof with a flatten shape using low Tvis and U-value material was preferable, multiple optimal solutions with the same desirability of energy-saving were obtained in different settings for arch and zigzag glass roofs. The optimal values for factors U, Tvis and tan α of the zigzag glass roof were distributed over a significant larger range than those of the arch form. The results indicated that the more factors with interactions were taken into considerations, the more possible solutions might be obtained to reach optimal goals, and the restrictions on each factor would be less. The findings regarding the substitutional relations of the research factors have challenged the belief that the relationship between a design factor and energy demand is unidirectional, and therefore may be important for decision-making in energy-saving designs.

Impact of adjustment strategies on building design process in different climates oriented by multiple performance

Adjustment strategies including window ventilation and shading have important improvements in energy consumption, thermal and light environments, furthermore, the upper limit for improvement is affected by design parameters. However, studies incorporating adjustment strategies in the building design process are very limited. To address this research gap, we explore the effects of window ventilation and shading on building design performance from uncertainty analysis, sensitivity analysis, and multi-objective optimization. Furthermore, China’s typical climate zones are compared given climate effects. Results indicate that (1) the uncertainty of total energy demand in the severe cold climate is most affected with the uncertainty increase rate being 32.0%, the uncertainty of thermal comfort ratio in the hot summer and cold winter climate and the hot summer and warm winter climate is most affected with the uncertainty increase rate being 16.3% and 14.0%, respectively. (2) the sensitivity analysis of the thermal comfort ratio is more sensitive to adjustment strategies than to total energy demand. The severe cold climate is more vulnerable than in other climates. (3) when multi-objective optimization is performed with maximum thermal comfort and minimum total energy demand when considering adjustment strategies, the severe cold climate has the greatest energy-saving potential (38.1%) and the hot summer and cold winter climate has the largest potential to improve thermal comfort (17.6%). More importantly, the light environment is within the comfort range from the daylight glare index, the illuminance, and illuminance uniformity ratios.

A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

A growing number of households benefit from government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefit from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand, and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.

Simulation and Management Strategy of Energy Flow in Hybrid System

This paper presents a control algorithm based on energy dispatch strategy in a remote area of Niger in West Africa region. . The system is a micro grid equipped with solar panels, conventional source and energy storage units. The hybrid energy management system presented is meant for rural and remote area power supply. The hybrid system configuration focuses on providing an uninterrupted power supply the maximum loads energy demand. This approach can improve the living conditions through the increase the economy and easiness of access to energy through a reasonable cost from an economic point of view to avoid over-sizing of production sources. The optimal configuration and model details of the proposed hybrid energy system has been described. The aim of this paper was to improve the design, operation and control requirement of a hybrid system in a specific area of Dakoro in Niger. The proposed control energy flow management strategy has been brought out by performing experimental studies on a laboratory prototype.

Is Deployment of Charging Station the Barrier to Electric Vehicle Fleet Development in EU Urban Areas? An Analytical Assessment Model for Large-Scale Municipality-Level EV Charging Infrastructures

This work investigates minimum charging infrastructure size and cost for two typical EU urban areas and given passenger car electric vehicle (EV) fleets. Published forecasts sources were analyzed and compared with actual EU renewal fleet rate, deriving realistic EV growth figures. An analytical model, accounting for battery electric vehicle-plug-in hybrid electric vehicle (BEV-PHEV) fleets and publicly accessible and private residential charging stations (CS) were developed, with a novel data sorting method and EV fleet forecasts. Through a discrete-time Markov chain, the average daily distribution of charging events and related energy demand were estimated. The model was applied to simulated Florence and Bruxelles scenarios between 2020 and 2030, with a 1-year timestep resolution and a multiple scenario approach. EV fleet at 2030 ranged from 2.3% to 17.8% of total fleet for Florence, 4.6% to 16.5% for Bruxelles. Up to 2053 CS could be deployed in Florence and 5537 CS in Bruxelles, at estimated costs of ~8.3 and 21.4 M€ respectively. Maximum energy demand of 130 and 400 MWh was calculated for Florence and Bruxelles (10.3 MW and 31.7 MW respectively). The analysis shows some policy implications, especially as regards the distribution of fast vs. slow/medium CS, and the associated costs. The critical barrier for CS development in the two urban areas is thus likely to become the time needed to install CS in the urban context, rather than the related additional electric power and costs.

Impact of DNI nowcasting on annual revenues of CSP plants for a time of delivery based feed in tariff

The impact of a combined nowcast for direct normal irradiation on revenues of two different concentrating solar power plant technologies under a time-of delivery-tariff is investigated. The nowcasts merge several satellite and NWP based nowcasts together with a smart persistence approach in order to generate a best-of nowcast for all now- and forecast time horizons up to 9 hours and in a 15 min temporal resolution. The applied tariff scheme is similar to that used in South Africa for some of the CSP plants erected in that country with considerably increased remuneration during the evening hours with maximum energy demand. The study investigates the impact both with respect to the annual energy yield and the economic annual revenues of CSP plants. The results for the combined nowcast are compared with results using ECMWF IFS based DNI forecasts which are commercially available for plant operators as well as with a persistence approach and the ideal forecast derived from ground-based observations.