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This paper proposes a Resistance perturbation based maximum power point tracking (MPPT) with an adaptive control limit algorithm to extract the maximum power from solar photovoltaic (PV) array. This algorithm consists of two main functions, namely 1) resistance perturbation & observation (RP&O) and 2) adaptive resistance control (ARC) limit. The RP&O operates the PV array at maximum power point (MPP), and the ARC limit continuously monitors the resistance of the PV Rpv to determine the operating limit of MPP. The ultimate aim of proposing this algorithm is to reduce the oscillations and improve MPP's tracking performance for sudden variation in temperature and irradiance conditions. Furthermore, it does not require an expensive pyranometer or temperature sensor to track the MPP of the PV array. This paper also compares the proposed and conventional MPPT algorithm's performance. Its validation results in both MATLAB/Simulink and experimental studies are presented under constant and sudden changes in irradiance conditions.

Energy storage is entering in the energy distribution supply chain due to the global goal of achieving carbon neutrality in human activities, especially those related to energy production. Renewable energies integrated with energy storage play an important role in this framework [1]. The purpose of the study is to evaluate through simulations the impact of new renewable energy technologies in a microgrid to minimize fossil fuels consumption. The case study considers a hybrid microgrid including: a gas microturbine, organic photovoltaic panels (OPV), a point absorber wave energy converter, a vanadium redox flow battery and a load. The microgrid is placed in an offshore hydrocarbon plant near the northern coast of Australia. Firstly, Australian meteorological data have been studied and three seasons identified (named ST1, ST2 and ST3). Then a correlation has been established between meteorological data and OPVs performances, analyzing data collected on OPVs panels installed. This relationship has been used to assess OPVs potential production at the site of interest. Similar correlation was made between the performances of a wave energy converter placed in the Adriatic Sea and the wave power matrix, to determine a suitable power data reference for the potential production of a wave energy converter to the Australian coast. Finally, the behavior of the microgrid was modeled. Different scenarios have been considered and the best one with optimal meteorological conditions enables lead to drastically decrease of the use of gas micro turbine resulting in lowest CO2 emissions. In fact, the consumption of natural gas has been summarized as follow: Season 1 (ST1): during this season the load is entirely fed by the renewable sources and by the battery, with consequent zeroing of the daily consumption of natural gas. Season 2(ST2): the battery is charged from 09:00am to 07:00pm with the exceeding power from the renewable sources. This configuration involves a daily natural gas consumption of 10.73 Sm3/d, which is equivalent to 987.16 Sm3/ ST2 (accounting for 92 days). Season 3(ST3): the battery is charged from 09:00am to 07:00pm with the exceeding power from the renewable sources. This configuration involves a daily natural gas consumption of 6.58 Sm3/d, which is equivalent to 1006.74 Sm3/ ST3 (accounting for 120 days). The avoided CO2 emissions are 2062 tons/year. This case study showed how the new renewable technologies, such as organic photovoltaics and wave energy converter, coupled with a long duration storage system, can be conveniently applied in sites with limited space for the decarbonization purpose of an offshore platform.

This paper presents a multi-objective model predictive control algorithm to implement the control of a bidirectional double stage ac-dc power conversion system, used to interface a Vanadium redox flow battery with a power grid. The converter topology is based on two stages conversion, consisting in a dual active bridge, controlled using the phase shift modulation, in cascade with a grid-connected inverter/rectifier. In order to control the charge and discharge of the battery, the dc-link and the grid current, a multi-objective predictive control is introduced embedding the control of both conversion stages in a single control action. The computed steady state and dynamic performance are compared to what can be achieved with standard controllers. The proposed algorithm is tested in simulation using a model developed with the PLECS block library on Matlab/Simulink.

The article of record as published may be found at https://doi.org/10.1109/TIA.2019.2923380 This paper presents a novel power flow control system for a remote military microgrid with hybrid energy storage. A combination of batteries and supercapacitors (SCs) is managed by the novel control system to increase the battery life by redirecting the higher frequency current that would have to flow in the battery if SCs were not present. This paper offers a practical solution to manage the SC current and ensure that the SCs are never overcharged or commanded to support the system when they are discharged to the lower operating limit chosen. The new controller allows the independent selection of the low-pass filter parameter and the number of SCs. By making the most out of these two degrees of freedom, we investigate different configurations, identifying the one achieving the highest cash flow for the overall system. Modeling, simulations, and experimental verification are presented and linked to the sensitivity analysis of the economics of the military microgrid. This work was supported by the Energy Systems Technology Evaluation Program, US Office of Naval Research

This paper presents a novel cascaded multilevel converter topology with reconfigurable battery modules able to merge the power conversion and the battery management functionalities for electric powertrain application. In the proposed topology, each battery cell can be individually connected or bypassed according to the required voltage and current levels. Both the charging and discharging processes can be controlled to avoid voltage imbalances between the cells and to enhance fault tolerance, battery life, and safety. Converter switching and conduction losses are evaluated and used as key parameters for the optimization of the proposed architecture. Furthermore, an efficiency comparison between a conventional three-phase IGBT-based inverter and the proposed topology is carried out. The two topologies are evaluated according to the WLTP Class 3 driving cycles, showing their average efficiency in each cycle. The comparison results show that the performance achieved with the proposed topology is extremely promising to combine state-of-the-art functionalities with the new paradigm of battery management.

A novel control strategy to manage the integration of a wind turbine and an energy storage unit to an existing oil and gas (O&G) stand-alone microgrid is the topic of this paper. The control strategy includes a primary and a secondary controller that, using the battery in tandem with the wind turbine, do not require any dump load. The secondary controller includes an energy management system which uses the estimated wind production so that the energy stored in the batteries is enough to supply the load, while providing the ground for the economic assessment. Additionally, a primary controller operates the original microgrid's source, a gas turbine, at its maximum efficiency through an active power control strategy. The microgrid is simulated and the combined control of the battery and GT bench-tested.

The penetration of solar photovoltaic (PV) generation is increasing in many countries, with significant implications for the adequacy and operation of power systems. This work considers the Nord bidding zone within Italy, which hosts 7.7 GW of PV and almost no wind power. We simulate the implications of different PV penetration levels on the need for firm generation capacity and on ramping requirements over one to several hours. We compare ten years of synthetic hourly PV generation series derived from CM-SAF SARAH satellite data and observed load. The analysis also provides insights into the storage capacity required to smooth residual load over different time horizons. Results show that without storage (i) the penetration of PV in the region does not sensibly reduce the need for firm generation; (ii) the marginal contribution of PV to meet power demand decreases with its penetration; and (iii) high penetrations lead to larger and more frequent ramps, although extreme ramp rates do not last more than 1 h. The availability of storage significantly alters these results, but large storage capacities are required. Smoothing net load by a few hours requires 2–7 GWh of storage per GW of PV installed.

This paper proposes a novel power flow control and optimization method for microgrid in grid-connected mode. The important factors, including the electricity cost under different electricity trading policies, battery degradation cost under different state of charge (SOC) and depth of discharge (DOD) conditions, as well as the different battery charging/discharging efficiencies have been explored. A universal normalized mathematical relation at critical operation points between all the costs has been developed and verified. Based on the dynamic programming algorithm, our proposed optimization approach can find the global optimal solution to microgrid power flow dispatch, for different electricity trading and battery storage conditions. Typical cases have been studied, modelled, simulated, and experimentally validated in this research.

This paper proposes an economically optimal energy management approach for grid-connected photovoltaic microgrid. The approach is derived based on the dynamic programming algorithm and grid Input/Output (grid I/O) strategy, to satisfy the load demand, fully utilize the solar energy, minimize the battery lifecycle losses, and maximize the economic benefits for end-users, simultaneously. The performances of this approach are explored for different weather scenarios (including sunny weather and cloudy weather) with forecast and measured photovoltaic (PV) power profiles. The simulations are done in Matlab and experimental validations are performed on a small scale microgrid. The benefits of this research are also compared to another method of rule-based algorithm combined with grid I/O.

The article of record as published may be found at http://dx.doi.org/10.1109/TIA.2018.2853041 Published in: IEEE Transactions on Industry Applications (Volume: 54 , Issue: 6 , Nov.-Dec. 2018) This paper presents a novel power flow control strategy, combined with an economic analysis, for an energy management system (EMS) involving a hybrid energy storage. The EMS operates a remote microgrid and directs the power flow to either batteries or supercapacitors to increase the life of the batteries. This paper demonstrates how the use of supercapacitors increases the lifetime of the batteries and ultimately how it affects the economics of the system. The proposed EMS controller also compensates for the 120-Hz ripple on the dc bus. Modeling, simulations, and experimental verification are presented together with the procedure to perform the assessment of the battery lifetime, according to the tuning parameters of the controller.

In this paper we present MELiSsa, a local multi-regional energy system model of a specific area: the Lombardy region. MELiSsa, implemented through an open-code modeling framework (OSeMOSYS), is built upon transparent relations and open data. Building this model is a first step towards four main goals: (i) extending the energy planning process of the region to citizens and experts usually not involved; (ii) exploiting this uncommon participation for a crowd-source development; (iii) providing a simple tool for interested local citizens to get consciousness of the technological and behavioral limits of their energy system; (iv) providing a real-case-based platform for interdisciplinary research and academic purposes possibly beyond the region boundaries. The current structure and input data of MELiSsa are presented and discussed together with a demonstrative analysis. Preliminary results show that interdisciplinary participation is enabled as an opportunity and it is needed to properly model technological dynamics as well as non-technological issues that will be relevant within the path to reach environmental, economic and social targets.

Optimal techniques are actually unused during the design phase of a compressor room. In this article, a novel application of the mixed-integer linear programming (MILP) technique is proposed as a tool for sizing and choosing the best configuration of an air compressor room, aiming at improving its energy efficiency. Two optimization problems are presented to cover different case studies. These formulations provide the optimal size, type, and number of compressors along with a room controller. The presented formulations are tested using both the simulated and real case studies. As a result of such a new approach, interesting energy savings are obtained when compared to the way the choices are usually performed. Very often, heuristic methodologies drive the design and the management of such facilities.

This paper presents an integrated thermal and electromagnetic modeling process for a small permanent magnet brushed motor and its experimental validation. The modeling has been achieved by means of two commercial software, based on lumped-parameters circuit analysis, whereas its validation has been performed by means of infrared thermography. The realization of this model is aimed to give insights on the thermal behavior of the motor in different duty cycle conditions to improve its performance in various applications. This model meets the needs of a company with high level of automation to evaluate during the design phase the characteristics of the suitable duty cycles for a particular motor; now it is employed as an aid in the prototyping of new products.

This paper introduces a new configuration in the compressed air production, which aims for a more efficient energy layout and innovative air network control and feeding. The target is achieved by applying a real-time earliest-deadline-first (EDF) scheduling technique to the management of the air production and delivery, seen as an energy service. The control action in a closed loop is applied to the activation/deactivation of valves, delivering air to networks operating at different pressure levels. The new configuration deals with a single compressor, which has a fixed speed and is electrically driven, and a centralized type of production, which is an alternative and is more efficient to a decentralized one. A set of suitably controlled valves intercepts air at the desired pressure level and feeds the networks while their operation guarantees that each pressure level is kept inside safe ranges. The algorithm integrates with a previous work. Future developments are also anticipated.

Electric vehicles are expected to greatly increase their market share in the near future. Their impact on the energy system will depend also on the way electricity will be generated. Renewable energy sources and intelligent control strategies will offer relevant solutions to mitigate that impact. In this paper we study the combination of photovoltaic energy and electric vehicles under uncontrolled charging regime and under the application of smart charging and vehicle-to-grid strategies. The analysis assumes different levels of photovoltaic generation and different penetrations of the electric vehicles. The assignment is carried out by means of an open source linear optimization model named EVLS, which simulates the interactions between the electric vehicles and the upstream energy system by considering market, technical and behavioral constraints. The results show that a high photovoltaic capacity could cover only a small portion of the transportation demand, if the charge is uncontrolled. In such a case, the non-photovoltaic generation would be required to severely ramp up in the late afternoon hours. An intelligent control of the charge could better accommodate the photovoltaic energy and reduce the ramps. The vehicle-to-grid could additionally help harnessing the photovoltaic energy to shave the peaks of the conventional load profile.

The article of record as published may be found at http://dx.doi.org/10.1109/ECCE.2017.8095976 Published in: 2017 IEEE Energy Conversion Congress and Exposition (ECCE) This paper presents a novel power flow control strategy for an energy management system (EMS) with hybrid energy storage. The EMS operates a remote microgrid and directs the power flow to either batteries or supercapacitors to increase the life of the batteries. This paper demonstrates that the use of supercapacitors increases the lifetime of the batteries and ultimately improves the economics of the system. The proposed EMS controller also compensates for the 120Hz ripple on the DC bus. Modeling, simulations and experimental verification are presented together with the procedure to perform the assessment of the battery lifetime, according to the tuning parameters of the controller. US Office of Naval Research as part of the Energy Systems Technology Evaluation Program

Long-term energy system models can be used to plan the expansion of generation capacity within a holistic view of the energy system. Some of them are based on linear optimization problems that make use of heuristics to reduce the calculation effort. Nonetheless, most of the existing frameworks lack of heuristics describing the impact of solar photovoltaic (PV) penetration on capacity adequacy. Within this work we propose an important step to include such feature into long-term energy systems models. We based our work on a prior study, which is needed, dealing with the impact of PV penetration on the area under focus. For the considered case study, the (i) peak reduction, the (ii) increase of ramp rates and the (iii) increase of excess energy are not linear and change behavior with PV penetration. We thus define the best piecewise linear functions that linearize such dynamics, by fixing an acceptable error and then choosing those with the lowest number of segments. We finally propose an approach to include such equations into models like OSeMOSYS.

This paper presents an optimized energy management system (OEMS) to control the microgrid of a remote temporary military base (FOB) featuring diesel generators, a battery energy storage system (BESS), and photovoltaic (PV) panels. The information of the expected electric demand is suitably used to improve the sizing and management of the BESS, according to the days of operation. The OEMS includes power electronics to charge the batteries from either the PV source or the diesel generators, and it can function as a current source when it is supplementing the power from one of the generators or as a voltage source when it is the sole source of power for the loads. The new contribution of this paper includes the optimization of a FOB's microgrid, where critical loads must be serviced at all times. The proposed optimization, which uses Special Order Sets for the semicontinuous function handling, also integrates economic evaluations by properly taking into account how the size of BESS affects its charge/discharge cycle; thus, the FOBs’ battery lifetime, in addition to its fuel consumption. Results from optimization are employed by the OEMS to coordinate the energy sources, and match the critical and noncritical loads with the available supply. Fuel savings of $\approx {\text{30}}\%$ (and $\approx {\text{50}}\%$ adding the PV source) can be achieved with respect to the already improved, but not optimal, solution of a previous work.

The recent worldwide measures for energy savings call for a larger awareness of the household energy consumption, given the relevant contribution of domestic load to the national energy balance. On the other hand, electricity smart meters together with gas, heat, and water meters can be interconnected in a large network offering a potential value to implement energy savings and other energy-related services, as long as an efficient interface with the final user is implemented. Unfortunately, so far, the interface of such devices is mostly designed and addressed at the utilities supervising the system, giving them relevant advantages, while the communication with the household is often underestimated. This paper addresses this topic by proposing the definition of a local interface for smart meters, by looking at the actual European Union and international regulations, at the technological solutions available on the market, and at those implemented in different countries, and, finally, by proposing specific architectures for a proper consumer-oriented implementation of a smart meter network.

As the share of photovoltaic (PV) generation is growing worldwide, so is the concerns about its stochastic nature that can complicate the operation and planning of energy systems. With this paper we give an overview on the topic, analyzing and quantifying the stochasticity of PV and its impact on energy systems, with a main focus on the generation sector. The impact is analyzed in terms of ability to replace conventional generation, required operating reserves, and requirements of related storage systems. The work is a literature review detecting concerning matters, interesting methods to quantify the problem, interesting results and open matters. The paper may be interesting for system operators, policy makers, researchers and producers.

Photovoltaic generation has reached high penetration levels in many countries. Photovoltaic like other variable renewables can have significant implications for the adequacy and operation of the power system and in general these implications can be location specific. This work focuses on the Lombardy region, in Italy, to study the implications that different penetrations of photovoltaic would have on the need for firm generation capacity and on the variability that this firm capacity would have to face. This is done by analyzing a the combination of real historical irradiance and demand data for the year 2012. Results show that even high penetrations of photovoltaic in the region would not reduce the need for firm generation. Moreover, high levels of generation from PVwould lead to higher and more frequent changes in generation. These considerations must be properly taken into account when encouraging the penetration of photovoltaic and when modeling power systems for planning purposes.

Cameroon is a Sub-Saharan African country, situated in central Africa, located at latitude 6°00 N and longitude 12°00 E, it is crossed by the 10th parallel north of the equatorial plane. The current electricity production is based only on hydro power and more than 95% of the whole electricity production comes from hydroelectricity. There are three separate grids and the transmission grids are completely isolated from one to another and no exchange of available surpluses can be made between the grids. This paper explores the potential of solar and wind energy and how hydro power can contribute for power fluctuation compensation as a key for economical success and better development in Cameroon and in the central African region. Despite great potential, development in the energy sector has been limited and in the country there are permanent energy shortages of electricity supply. A viable and alternative solution can be taking into account the specificities of each region and see which type of renewable resources are available and how the combination of different type of renewable resources can be made in the most appropriate way for energy supply. Work on reliability and cost-effective measurements to determine the potential, the fluctuation rate and the balancing effects of the different sources. In most equatorial African countries, it is difficult to satisfy power demand all year long by hydro sources alone. In some remote areas, where this is the case, a judicious combination with other renewable sources to form a hybrid system can help solve rural electrification problems.

Cameroon is a Sub-Saharan African country, situated in central Africa, located at latitude 6°00 N and longitude 12°00 E, it is crossed by the 10th parallel north of the equatorial plane. Solar and wind energy potential can be the key for economical success and better development in Cameroon and the whole central African region. According to Solargis database, Meteonorm Software, RETScreen International, NASA (surface meteorological and solar energy), SWERA (Solar and Wind Energy Assessment) and NREL (National Renewable Energy Laboratory), the solar radiation average across the country is 4.9 kWh/ m2/day and the wind speed average across the country is 6 m/s. The exact sizes of the different renewable energy sources, their benefits and the market potential that can stimulate their uptake are not well-known. There is no reliable information about the potential of renewable energy resources in Cameroon and free available information is very rough. Cameroon like most developing countries does not have a reliable network of surface observation stations for collecting weather data. A viable and alternative solution can be, taking into account the specificities of each region and see which type of renewable resources are available and how the combination of different type of renewable resources can be made in the most appropriate way for energy supply. Work on reliability and cost-effective measurements to determine the potential of renewable resources in Cameroon for energy supply. A photovoltaic cell instead of a pyranometer can be employed because of it cost competiveness and the errors will be corrected. The collected data can be a good base for decentralization of the electrical production base choice of microgrids with the main objectives to make the different regions be autonomous.

This paper presents a review of different schemes of hybrid energy systems (HES) in islanding mode for remote areas with a focus on solutions for remote electrification which are basically composed by one or a mixed of different energy sources and storage systems. The paper analysis the widely used mathematical approaches for optimization, sizing and modeling of HES for isolated electrification areas including the role of storage system. This paper also analysis the advantages and disadvantages of different solutions proposed.

In this corrspondence, we investigate the application of linear and neurodynamic models to solve the critical problem of obtaining the most cost-effective electrical load forecast for an industrial site. This is done from the perspective of an energy service company (ESCo). The ESCos' business model is based on the notion of making money by providing a means to enable their commercial customers to lower their electric bills. This in turn is based on the idea that the energy supplier's cost of doing business is reduced if its commercial customers can provide a reliable load forecast. A portion of that cost savings is passed on to the user as a discount in the selling price. Since it is not cost effective for the customer to install extensive monitoring instrumentation, the load forecast must be made on the basis of a model that is determined by applying systems identification techniques to the user's consumption pattern. By a single-point observation of the electrical energy consumption in a dairy plant at quarter-hour intervals over a two-year period, we were able to identify a model and use it to devise a straightforward strategy for nontrivial cost savings to the user and a profitable line of service for the ESCo. The performance of several models is compared. The results for the weekly-based models are reported and the effective cost reduction along with the implementation time to set up the service package are quantified and verified in the proposed final business plan. The project produces overall revenues of roughly euro13 600 over a five-year contracting period

Due to the possibility to drastically reduce the Solid State Transformer (SST) volume and weight, its use is becoming a reality in traction and wind power plant applications, while, in the electric distribution system, it is still considered futuristic. A SST, with managerial role in the electric distribution grid, is generally called Smart Transformer (ST). Unfortunately the low efficiency, the low reliability and the high cost still act as barriers for its widespread use in the real world. This paper focuses on the impact of a modular design, by benchmarking different ST topologies. Moreover, the paper provides guidelines on how to choose the semiconductor modules and assessments on how the choice affects the efficiency of the ST.

The long term benefits and costs of many technologies and control applications of the next future will depend on short time span dynamics. The resolution of most available economic energy system models is not able to detect their impact on the long time horizon. By adding equations to the code of OSeMOSYS, the open source energy system model, we enabled electric vehicles and related smart control strategies to be taken into account in a long term perspective. An application to a local case study explores the effect of the penetration of the electric vehicles on the power load and the role of the smart control strategies in shaving the additional peaks and pursuing environmental targets.

The stabilization of pressure fluctuation is of paramount importance in the management of compressed air systems. In a multi compressor room where load/unload controlled machines can operate along with adjustable speed ones (ASD), the latter usually operate with a set point activation level which lays in between the upper and the lower thresholds of the network operating pressure. By keeping such set point as low as possible, further savings in energy consumptions can be achieved. The presented work deals with the application of a new strategy for the control of an ASD screw air compressor. This strategy-if compared with a PI strategy- can reduce pressure swings, consequently the AS compressor set point, while ensuring the network pressure's requirements. To the utmost, such value can be set equal to the lowest network operative pressure. The above objective is pursued by controlling the ASD screw compressor with a model predictive control scheme (MPC). The comparison with a PI regulated control shows the potential of MPC both from a pressure stabilization standpoint and, slightly, also from an energy saving standpoint. For a comprehensive implementation of the control scheme, forecasting techniques need to be applied to assess end-users air requirements: this topic, though, is not investigated in the current work.

The paper presents how to cope the outcomes of an energy model like Markal with a new model aiming at having more insights on the role, thus the impact, that Electric drive train Vehicles (EVs) can play on a local grid and eventually how to minimize it. A MarkAl local model, which is a multi-period energy model, is coupled with a static transportation model (EVLS-V2G) including the vehicle to grid (V2G) option and integrating the Markal multi-period analysis with a more detailed time horizon reference. The formulation of a linear problem (LP) is proposed for the EVLS model and the relationships between the two models' input/output are discussed. An example allowing the understanding of how this coupling works is also given with respect to three different strategies: the smart charging, the uncontrolled and the V2G strategy.

The substitution of the conventional fleet with plug-in Electric Vehicles (EVs) is one possible path towards the decarbonisation and more sustainability of private transportation. However, benefits related to a high number of vehicles, and the measures that could mitigate negative effects on the electric grid have to be assessed. In this paper a new model is presented for investigating the effect of a high-medium penetration of EVs on a local grid and their role on the emissions reduction. Besides it allows analyzing how the smart charging and the Vehicle-to-Grid (V2G) options can reduce the additional load or even support the power grid stability. Pro and cons are presented and a case study is proposed.