Demand Response (DR) programs under the umbrella of Demand Side Management (DSM) tend to involve end users in optimizing their Power Consumption (PC) patterns and offer financial incentives to shift the load at “low-priced” hours. However, users have their own preferences of anticipating the amount of consumed electricity. While installing an Energy Management System (EMS), the user must be assured that this investment gives optimum comfort of bill savings, as well as appliance utility considering Time of Use (ToU). Moreover, there is a difference between desired load distribution and optimally-scheduled load across a 24-h time frame for lowering electricity bills. This difference in load usage timings, if it is beyond the tolerance level of a user, increases frustration. The comfort level is a highly variable phenomenon. An EMS giving optimum comfort to one user may not be able to provide the same level of satisfaction to another who has different preferences regarding electricity bill... [more]

The goal of maintaining users’ thermal comfort conditions in indoor environments may require complex regulation procedures and a proper energy management. This problem is being widely analyzed, since it has a direct effect on users’ productivity. This paper presents an economic model-based predictive control (MPC) whose main strength is the use of the day-ahead price (DAP) in order to predict the energy consumption associated with the heating, ventilation and air conditioning (HVAC). In this way, the control system is able to maintain a high thermal comfort level by optimizing the use of the HVAC system and to reduce, at the same time, the energy consumption associated with it, as much as possible. Later, the performance of the proposed control system is tested through simulations with a non-linear model of a bioclimatic building room. Several simulation scenarios are considered as a test-bed. From the obtained results, it is possible to conclude that the control system has a good beha... [more]

In recent years, demand side management (DSM) techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a heuristic algorithms-based energy management controller is designed for a residential area in a smart grid. In essence, five heuristic algorithms (the genetic algorithm (GA), the binary particle swarm optimization (BPSO) algorithm, the bacterial foraging optimization algorithm (BFOA), the wind-driven optimization (WDO) algorithm and our proposed hybrid genetic wind-driven (GWD) algorithm) are evaluated. These algorithms are used for scheduling residential loads between peak hours (PHs) and off-peak hours (OPHs) in a real-time pricing (RTP) environment while maximizing user comfort (UC) and minimizing both electricity cost and the peak to average ratio (PAR). Moreover, these algorithms are tested in two scenarios: (i) scheduling the load of a... [more]

This work analyzes the effects of a BMS (battery management system) on the characterization and modeling of series and parallel connections of Li-ion cell packs. The Li-ion pack studied consists of four series modules connected in parallel. This pack has been characterized by means of charge, discharge and frequency tests. As a result of these tests, series and parallel influence on battery parameters have been determined. A model considering the effects of a BMS is established and compared with a model based on a single-cell approach. Experimental validations show that the single cell based approach gives poor results in comparison with a model that considers BMS effects.

This paper presents an optimal cooperative voltage control approach, which coordinates storage units in a distribution network. This technique is developed for storage systems’ active power management with a local strategy to provide robust voltage control and a distributed strategy to deliver optimal storage utilization. Accordingly, three control criteria based on predefined node voltage limits are used for network operation including normal, over-voltage, and under-voltage control modes. The contribution of storage units for voltage support is determined using the control modes and the coordination strategies proposed in this paper. This technique is evaluated in two case studies to assess its capability.

This paper presents the analysis and design of a smart battery management system for Field Programmable Gate Array (FPGA) based portable electronic devices. It is a novel concept of incorporating the functionality of a smart battery management system into the FPGA used by portable electronic devices, which provides the following advantages. (1) It lowers cost since the conventional commercial independent battery management circuit can be eliminated; (2) It offers more flexibility because FPGA based battery management algorithms can be specifically designed for different battery chemistries of different devices and can provide the flexibility of algorithms and functionalities updating as well. Smart battery management system concepts include four aspects: (1) smart charging; (2) battery balancing; (3) smart discharging; and (4) safety operating. One novel charging algorithm, which combines the merits of multistage charging and pulse charging, is proposed to charge a Li-ion battery pack... [more]

The recent growing diffusion of dispersed generation in low voltage (LV) distribution networks is entailing new rules to make local generators participate in network stability. Consequently, national and international grid codes, which define the connection rules for stability and safety of electrical power systems, have been updated requiring distributed generators and electrical storage systems to supply stabilizing contributions. In this scenario, specific attention to the uncontrolled islanding issue has to be addressed since currently required anti-islanding protection systems, based on relays locally measuring voltage and frequency, could no longer be suitable. In this paper, the effects on the interface protection performance of different LV generators’ stabilizing functions are analysed. The study takes into account existing requirements, such as the generators’ active power regulation (according to the measured frequency) and reactive power regulation (depending on the local m... [more]

The achievement of the so-called 2020 targets requested by the European Union (EU) has determined a significant growth of proposals of solutions and of technical projects aiming at reducing the CO₂ emissions and increasing the energy efficiency, as well as the penetration of Renewable Energy Sources (RES) in the electric network. As many of them ask for funding from the EU itself, there is the necessity to define a methodology to rank them and decide which projects should be sponsored to obtain the maximum effect on the EU 2020 targets. The present paper aims at (i) defining a set of Key Performance Indicators (KPIs) to compare different proposals, (ii) proposing an analytical methodology to evaluate the defined KPIs and (iii) evaluating the maximum impact that the considered action is capable of producing. The proposed methodology is applied to a set of possible interventions performed on a benchmark transmission network test case, in order to show that the defined indicators can be e... [more]

Recently, several environmental problems are beginning to affect all aspects of life. For this reason, many governments and international agencies have expressed great interest in using more renewable energy sources (RESs). However, integrating more RESs with distribution networks resulted in several critical problems vis-à-vis the frequency stability, which might lead to a complete blackout if not properly treated. Therefore, this paper proposed a new Under Frequency Load Shedding (UFLS) scheme for islanding distribution network. This scheme uses three meta-heuristics techniques, binary evolutionary programming (BEP), Binary genetic algorithm (BGA), and Binary particle swarm optimization (BPSO), to determine the optimal combination of loads that needs to be shed from the islanded distribution network. Compared with existing UFLS schemes using fixed priority loads, the proposed scheme has the ability to restore the network frequency without any overshooting. Furthermore, in terms of ex... [more]

The article deals with the use of modern materials and technologies that can improve the thermal comfort in buildings. The article describes the design and usage of a special accumulation device, which is composed of thermal panels based on phase change materials (PCMs). The thermal panels have an integrated tube heat exchanger and heating foils. The technology can be used as a passive or active system for heating and cooling. It is designed as a “green technology”, so it is able to use renewable energy sources, e.g., photovoltaic (PV) panels, solar thermal collectors and heat pumps. Moreover, an interesting possibility is the ability to use thermoelectric coolers. In the research, measurements of the different operating modes were made, and the results are presented in the text. The measurement approves that the technology improves the thermal capacity of the building, and it is possible to use it for active heating and cooling.

In this article, a thermodynamic study was conducted on the energetic and exergy performance of a new configuration of liquid chemical looping gasification (LCLG) plant integrated with a power block to assess the overall performance of the system including exergy partitioned in syngas and first law efficiency (FLE). LCLG is a relatively new concept for the production of high-quality synthetic gas from solid feedstock such as biomass. As the temperature and pressure of the looping system are high, there is thermodynamic potential to co-produce chemical products, power and heat. Hence, in the present work, three different configurations of a power cycle were thermodynamically assessed. In the first proposed power cycle, the produced syngas from the gasifier was combusted in a combustion chamber and the exhausted gases were fed into a gas turbine. In the second and third proposed power cycles, the hot air was directly fed into a gas turbine or was used to produce steam for the steam turbi... [more]

Fossil fuels are the primary sources of electricity generation in Pakistan. The energy demand and supply gap have intensified recently due to the massive population and fossil fuels are unable to meet the gigantic energy requirement of the country. Meanwhile, they also have adverse environmental impacts. Remote rural regions that are far away from the national grid do not have any means to fulfill their energy needs. The off-grid solar photovoltaic (PV) system has emerged to be the best energy option to electrify these remote regions. However, the strategic problem pertaining to local electricity generation is the absence of the area-specific generation capacity and economic feasibility data for solar energy. To address this problem, this study aims to assess the potential and economic viability of utilizing an off-grid solar PV system for rural electrification in the Punjab province of Pakistan. The research results reveal that there is an excellent solar irradiance in the rural areas... [more]

This paper focuses on total quality management (TQM) processes and their applications to increase the management performance of enterprises in the renewable energy sector (RES). TQM is a modern tool used by enterprises to increase their management performance. We start with a description of Edwards Deming’s conceptualized model, highlighting different phases of its development as described in the literature. The TQM process is then used for an application to the RES in Romania. The quantitative model analyzes the influence of TQM process implementation in achieving competitive advantage and the management performance of the undertakings in the RES. Data was collected through a survey based on a questionnaire addressed to employees and managers in the RES. Structural equation modeling (SEM) was used and the research hypotheses were tested with the partial least squares path method (PLS). Data analysis was performed with the statistical software SmartPLS 3.2.8. The main contribution of t... [more]

Tabular Q-learning (QL) can be easily implemented into a controller to realize self-learning energy management control of a plug-in hybrid electric bus (PHEB). However, the “curse of dimensionality” problem is difficult to avoid, as the design space is huge. This paper proposes a QL-PMP algorithm (QL and Pontryagin minimum principle (PMP)) to address the problem. The main novelty is that the difference between the feedback SOC (state of charge) and the reference SOC is exclusively designed as state, and then a limited state space with 50 rows and 25 columns is proposed. The off-line training process shows that the limited state space is reasonable and adequate for the self-learning; the Hardware-in-Loop (HIL) simulation results show that the QL-PMP strategy can be implemented into a controller to realize real-time control, and can on average improve the fuel economy by 20.42%, compared to the charge depleting−charge sustaining (CDCS) strategy.

With the high degree of wind power penetration integrated into multi-area AC/DC interconnected power grids, the frequency regulation capacity of automatic generation control (AGC) units is not sufficient in the wind power-penetrated area, making it difficult to effectively suppress the frequency stability caused by the fluctuation of wind power. Therefore, a coordinated control strategy for AGC units across areas based on bi-level model predictive control is proposed in this paper to achieve resource sharing. The control scheme uses economic model predictive control to realize steady power optimal allocation of the AGC units across areas in the upper layer and distributed model predictive control to realize dynamic frequency optimization control of the multi-area AGC units in the lower layer. Taking a three-area AC/DC interconnected power grid with a wind farm as an example, the simulation results show that, compared with model predictive control using tie-line frequency bias control (... [more]

Due to environmental and economic drawbacks of fossil fuels, global renewable energy (RE) capacity has increased significantly over the last decade. Solar photovoltaic (PV) is one of the fastest-growing RE technologies. Selecting an appropriate site is one of the most critical steps in utility-scale solar PV planning. This paper aims at proposing a rational multi-criteria decision-making (MCDM) approach based on the Brown−Gibson model for optimal site selection for utility-scale solar PV projects. The proposed model considers the project’s net present value (NPV) along with seven suitability factors and six critical (constraint) factors. The RETScreen software was applied in calculating the NPV, the simple payback period and the carbon emission savings of the project at each alternative site. The weights of the suitability factors were determined using the analytical hierarchy process. Applied to the case study of finding the best location for a 5 MW solar PV project in northern Camero... [more]

Thermoelectric generators (TEGs) can harvest thermal energy from waste heat sources to supply various power levels due to the Seebeck effect. The power generated by a TEG is dependent not only on the temperature difference across them but also on the electrical load applied. Typically, waste heat sources have variable operating conditions which means maximum power point tracking (MPPT) must be employed through the use of power converters to produce the desired operating point of the system and thus increase the system efficiency. This paper presents a new MPPT scheme which has not been previously applied to thermoelectric generators, the high frequency injection (HFI) scheme to achieve a fast and accurate tracking of the maximum power operation point for TEGs. The proposed MPPT scheme is implemented with a power converter, and the tracking scheme performance is experimentally evaluated on a commercial TEG module through three different experiments. The proposed scheme is also compared... [more]

The complicated coupling of component design together with energy management has brought a significant challenge to the design, optimization, and control of plug-in hybrid electric buses (PHEBs). This paper proposes an integrated optimization methodology to ensure the optimum performance of a PHEB with a view toward designing and applications. First, a novel co-optimization method is proposed for redesigning the driveline parameters offline, which combines a nondominated sorting genetic algorithm-II (NSGA-II) with dynamic programming to eliminate the impact of the coupling between the component design and energy management. Within the new method, the driveline parameters are optimally designed based on a global optimal energy management strategy, and fuel consumption and acceleration time can be respectively reduced by 4.71% and 4.59%. Second, a model-free adaptive control (MFAC) method is employed to realize the online optimal control of energy management on the basis of Pontryagin’s... [more]

Carbon emissions and environmental protection issues have become the pressure from the international community during the current transitional stage of China’s energy transformation. China has set a macro carbon emission target, which will reduce carbon emissions per unit of Gross Domestic Product (GDP) by 40% in 2020 and 60−65% in 2030 than that in 2005. To achieve the emission reduction target, the industrial structure must be adjusted and upgraded. Furthermore, it must start from a high-pollution and high-emission industry. Therefore, it is of practical significance to construct a low-carbon sustainability and green operation benefits of power generation enterprises to save energy and reduce emissions. In this paper, an intuitionistic fuzzy comprehensive analytic hierarchy process based on improved dynamic hesitation degree (D-IFAHP) and an improved extreme learning machine algorithm optimized by RBF kernel function (RELM) are proposed. Firstly, we construct the evaluation indicator... [more]

Air-conditionings have energy storage functions. Through reasonable aggregation control, the output tracking can be implemented for wind power with stronger fluctuation to enhance its utilization rate. Cloud technology and intelligent appliances enable the appliance vendor to implement information interaction with the air-conditioning through cloud platforms to realize flexible regulation. In this paper, a management and control method of air-conditioning based on cloud platform is established. Based on this structure, the air-conditionings are divided into several aggregation groups according to the similarity of parameters, and each group completes the consumption task collaboratively. The consumption evaluation model of the air-conditioning group is established. On this basis, the allocation problem on consumption task for the aggregated group is constructed to implement the optimal solution under the condition of guaranteeing the degree of completion and user comfort. Each group im... [more]

Bioenergy supply chains can offer social benefits. In most related research, the total number of created jobs is used as the indicator of social benefits. Only a few of them quantify social benefits considering the different impact of economic activities in different locations. In this paper, a new method of measuring the social benefits of bioethanol supply chains is proposed that considers job creation, biomass purchase, and the different impacts of economic activities in different locations. A multi-objective mixed integer linear programming (MILP) model is developed to address the optimal design of a bioethanol supply chain that maximizes both economic and social benefits. The ε-constraint method is employed to solve the model and a set of Pareto-optimal solutions is obtained that shows the relationship between the two objectives. The developed model is applied to case studies in Liaoning Province in Northeast China. Actual data are collected as practical as possible for the feasib... [more]

The unique situation of utility power curtailment unveils opportunities in the fields of energy management and digital resource management. During utility load shedding events, campuses are typically driven as Photo Voltaic (PV)−diesel generator hybrid systems, of which the main fossil resource driver is diesel. With the appropriate Supervisory Control and Data Acquisition (SCADA) systems, discrete departmental energy policies along with control, forecasting and Internet of Things (IoT) infrastructure, the campus hybrid system could be optimized on a short timescale during the shedding event. In this paper the optimization methodology, required technology infrastructure, possible forecasting algorithms and potential implementation will be discussed.

Concentrated solar power (CSP) is a leading renewable energy technology, and the parabolic trough (PT) is one of the most used configurations of CSP. In the present study, the performance improvement and energy cost reduction of a 50 MWe PT plant for Abu Dhabi, United Arab Emirates (UAE) is presented. The simulations were carried out using the System Advisor Model software. The analyses of a PT plant with different technologies/parameters are undertaken in the first instance for seven cases. These cases include solar multiple, solar collectors, receivers, heat transfer fluid, cooling system (evaporative and air-cooled), thermal energy storage system (4−12 h), and fossil dispatch mode (0.25 to 1.0). Based on these analysis, the eighth case, which is found to be the best-case scenario in this study, was considered by taking into account the best of preceding case results and was determined to be the most suitable both in terms of performance and cost reduction. It is, therefore, conclude... [more]

Air conditioning loads are important resources for demand response. With the help of thermal energy storage capacity, they can reduce peak load, improve the reliability of power grid operations, and enhance the emergency capacity of a power grid, without affecting the comfort of the users. In this paper, a virtual energy storage model for inverter air conditioning loads, which reflects their operating characteristics and is more conducive to practical application, is established. Two parts are involved in the virtual energy storage model: An electrical parameter part, based on the operating characteristics, and a thermal parameter part, based on the equivalent thermal parameter model. The control function and restrictive conditions of the virtual energy storage are analyzed and a control strategy, based on virtual state-of-charge ranking, is proposed. The strategy controls the inverter air conditioners through re-assigning indoor temperature set-points within the pre-agreed protocol in... [more]

This paper presents a statistical analysis of wind speed data that can be extremely useful for installing a wind generation as a stand-alone system. The main objective is to define the wind power capacity’s contribution to the adequacy of generation systems for the purpose of selecting wind farm locations at specific sites in Malaysia. The combined Sequential Monte Carlo simulation (SMCS) technique and the Weibull distribution models are employed to demonstrate the impact of wind power in power system reliability. To study this, the Roy Billinton Test System (RBTS) is considered and tested using wind data from two sites in Peninsular Malaysia, Mersing and Kuala Terengganu, and one site, Kudat, in Sabah. The results showed that Mersing and Kudat were best suitable for wind sites. In addition, the reliability indices are compared prior to the addition of the two wind farms to the considered RBTS system. The results reveal that the reliability indices are slightly improved for the RBTS sy... [more]