Energy management for user’s thermal and power needs: A survey <s> Generation <s> According to operation characteristics of a microgrid with fluctuant energy, such as solar energy, wind energy and alike, a multi-objective economic dispatching model for microgrid is proposed. These objectives are to minimize the production cost, customer outage cost and emission pollution cost. Taking into account characteristics of the proposed model, the maximum fuzzy satisfaction degree method is used for fuzzy multi-objective optimization problem to transform the multi-objective optimization problem into a non-linear single-objective optimum problem, which is solved by using particle swarm algorithm at the hour-level commitment of DGs and the output power distributions of DGs. Simulation results show that multi-objective model is better than single-objective model in reflecting the actual operation characteristics of microgrid more precisely and reaching a higher reliability and environmental benefit at as low operation cost as possible. <s> BIB001 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Abstract Renewable energy sources (RES) are an “indigenous” environmental option, economically competitive with conventional power generation where good wind and solar resources are available. Hybrid systems can help in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The aim of this paper is to present a dynamic model able to integrate different RES and one storage device to feed a “Green” building for its thermal and electrical energy needs in a sustainable way. The system model is embedded in a dynamic decision model and is used to optimize a quite complex hybrid system connected to the grid which can exploit different renewable energy sources. A Model Predictive Control (MPC) is adopted to find the optimal solution. The optimization model has been applied to a case study where electric energy is also used to pump water for domestic use. Optimal results are reported for two main cases: the presence/absence of the energy storage system. <s> BIB002 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Abstract A combined cooling, heating and power (CCHP) microgrid with distributed cogeneration units and renewable energy sources provides an effective solution to energy-related problems, including increasing energy demand, higher energy costs, energy supply security, and environmental concerns. This paper presents an overall review of the modeling, planning and energy management of the CCHP microgrid. The performance of a CCHP microgrid from the technical, economical and environmental viewpoints are closely dependent on the microgrid’s design and energy management. Accurate modeling is the first and most important step for planning and energy management of the CCHP microgrid, so this paper first presents an review of modeling of the CCHP microgrid. With regard to planning of the CCHP microgrid, several widely accepted evaluation methods and indicators for cogeneration systems are given. Research efforts on the planning methods of the CCHP microgrid are then introduced. Finally, the energy management of the CCHP microgrid is briefly reviewed in terms of cogeneration decoupling, control strategies, emission reduction and problem solving methods. <s> BIB003 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> This paper addresses a hybrid renewable system that consists of a micro-Combined Cooling Heat and Power (CCHP) unit and a solar energy conversion device. In addition to a traditional PV system, a High Concentrator Photovoltaic (HCPV) device, the design of which is suitable for building integration application, was also modelled and embedded in the hybrid system. The work identifies the optimal management strategies for the hybrid renewable system in an effort to minimise the primary energy usage, the carbon dioxide emissions and the operational costs for variable electricity prices that result from the day-ahead electricity market. An "ad hoc" model describes the performance of the HCPV module, PV and Internal Combustion Engine, whilst the other units were simulated based on their main characteristic parameters. The developed algorithm was applied to three different building typologies. The results indicate that the best configuration is the hybrid renewable system with PV, which can provide a yearly primary energy reduction of between 20% and 30% compared to separate production. The hybrid renewable system with HCPV becomes competitive with the PV technology when the level of solar radiation is high. <s> BIB004 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> This paper considers heat and power production from micro Combined Heat and Power systems and heat storage in a network of households. The goal is to balance the local heat demand and supply in combination with balancing the power supply and demand in the network. The on-off decisions of the local generators are done completely distributed based on local information and information exchange with a few neighbors in the network. This is achieved by using an information sharing model with a distributed model predictive control method based on dual-decomposition and sub-gradient iterations. Because of the binary nature of the decisions, a mixed integer quadratic problem is solved at each agent. The approach is tested with simulation, using realistic heat and power demand patterns. We conclude that the distributed control approach is suitable for embedding the distributed generation at a household level. <s> BIB005 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Integrated distributed energy resources play a crucial role in modernized power systems. They can decrease emissions, decrease the resistive losses and add to the security and reliability of electric networks. They can be of different nature and may contain fossil-fuelled generating units, wind units, fuel cells, storage devices and solar panels. In this article, first different distributed energy resources are introduced briefly, then, the operation and control strategies of integrated distributed energy resources will be reviewed. The review of existing research works in this field and finding the research gaps can lead to useful directions for future researchers who are interested to work in this field. <s> BIB006 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Abstract Nowadays with the emerging of smart micro-grids(SM-Gs) in residential sectors, a large portion of energy consumption can be saved through optimal scheduling of household devices and management of domestic hybrid energy sources. By the aid of such technologies, residential consumers have the capability to mitigate their energy costs and satisfy their own requirements paying less attention to the configuration of the energy supply system. This paper presents a novel residential energy management system (REMS) to improve the efficiency of energy consumption in a typical SM-G taking into account minimum cost of energy as well as maximum user's comfort level as competitive objectives. The optimization model is also formulated as a mixed integer nonlinear problem (MINLP) and its performance is tested under different operating scenarios with real data. The simulation results show that the proposed model not only reduces energy consumption costs, but also ensures a comfortable lifestyle for occupants. <s> BIB007 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Abstract In this paper, a new methodology has been discussed on economical power management of a grid-connected CHP system which consists of a wind turbine, photovoltaic array, polymer exchange membrane fuel cell and an electrolyzer. Hence, the paper also attempts to present the thorough modeling of energy management of the hybrid system in the form of a nonlinear optimization problem; through which offline energy management is regarded to use the available options in order to determine the role of each generator in producing heat, power and hydrogen in the system under study. In addition to this, variable tariffs of daily exchange with local grid have been taken into account in different operation conditions so as to reach real utilization requirements. Based on these facts, choosing the most suitable model for each element of the hybrid system has been considered in regard to their dynamic behavior. The proposed hybrid system is to supply the electrical and thermal demands of renewable energy laboratory of Shahid Bahonar University of Kerman (SBUK). The economical energy management is comprehensively studied and surveyed in the form of various scenarios while the hybrid system is connected to the grid. <s> BIB008 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Intermittent generation is challenging for the existing power systems, which have difficulties in following varying electricity production. To help the generation and demand be in balance, demand response (DR) provides one promising approach. Among many DR applications, residential micro-CHP systems can be advantageous, as these systems typically comprise storage in addition to a controllable cogeneration unit. Current state-of-the-art control strategies for residential micro-CHP systems utilize time-varying electricity price to optimally operate the system. Thus, such systems have the ability to export or import electricity when either one is beneficial. <s> BIB009 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Microgrids (MGs) are considered as a key solution for integrating renewable and distributed energy resources, combined heat and power (CHP) systems, as well as distributed energy-storage systems. This paper presents a stochastic programming framework for conducting optimal 24-h scheduling of CHP-based MGs consisting of wind turbine, fuel cell, boiler, a typical power-only unit, and energy storage devices. The objective of scheduling is to find the optimal set points of energy resources for profit maximization considering demand response programs and uncertainties. The impact of the wind speed, market, and MG load uncertainties on the MG scheduling problem is characterized through a stochastic programming formulation. This paper studies three cases to confirm the performance of the proposed model. The effect of CHP-based MG scheduling in the islanded and grid-connected modes, as well as the effectiveness of applying the proposed DR program is investigated in the case studies. <s> BIB010 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> The development of technologies such as micro turbines and gas furnaces has been the major driving force towards integration of electricity and natural gas networks in the EH (energy hubs). Besides, the existing power grids are getting smarter by implementing the new generation of information technologies and communication systems. In smart grid, the electricity suppliers can modify the customers' electrical load consumption by employing appropriate scheduling schemes such as DR (demand response) programs. In this paper, we consider the S. E. Hubs (smart energy hubs) framework, in which the customers can use EMS (energy management system) to access to the electricity and natural gas prices data and wisely manage their daily energy consumption. We extend the existing DR programs to the IDR (integrated demand response) programs with the aim of modifying both electricity and natural gas consumption on the customer side. The interaction between S.E. hubs in the IDR program is formulated as a non-cooperative game. The goal of the IDR game is to maximize the natural gas and electricity utility companies' profit and to minimize the customers' consumption cost. It is shown that the proposed game model is an ordinal potential game with unique Nash equilibrium. Simulations are performed on an energy system with 6 S. E. Hubs, one electricity utility, and one natural gas utility companies. The results confirm that the IDR program can benefit both the customer side, by reducing the electricity and gas consumption cost, and the supplier side, by reducing the peak load demand in the electricity and natural gas load profiles. <s> BIB011 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Pre-packaged cogeneration systems are popular as lead supply in distributed and isolated energy systems aimed at empowering remote off-grid communities and in supporting eco-villages in nature reserves. Energy cooperatives and independent power producers deploy cogeneration systems in community shared microgrid configurations as building blocks in smart localised multi-carrier energy grids. Small-scale renewable energy and distributed energy resources in the energy mix of multi-carrier combined heat and power microgrids call for the development of intelligent control automation solutions. This paper describes a multi-objective optimization solution where hierarchical digital microgrid control is integrated into solar powered micro-cogeneration. The control solution includes an integrated cost-competitive economic and environmental optimization algorithm customized around the needs of small off-grid isolated village settlements. A secondary stage optimization loop functions as a storage capacity decision support system, to alert the community when operating costs can be reduced through an investment into increased storage capacity for the village microgrid. This cost-aware control optimization algorithm is tested in a rural village microgrid by using parametric computer simulation models of a hybrid residential solar cogeneration system. Digital simulation experiments evaluate the operational plans and operational cost performances of energy management for different storage scenarios at an isolated remote rural location in Africa. <s> BIB012 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Abstract Residential fuel cell based combined heat and power (FC-CHP) systems have been commercialized and are penetrating the marketed in Japan. In order to utilize FC-CHP systems efficiently, operational strategies are required. Energy interchange among consumers improves efficiency by allowing flexible operation of equipment. An energy management system (EMS), which is installed at the consumer dwelling, can integrate the control and management of energy equipment by using an optimized planning approach that incorporates the energy interchange and can operates equipment whilst adjusting to real conditions. An EMS has been developed, which achieves optimal operation of FC-CHP systems with energy interchange between dwellings in a residential area. Case studies were performed to evaluate the EMS model by using evaluation indices including energy costs, CO2 emissions, and primary energy consumption. The results showed that 1) energy management and energy interchange were effective and contributed to cost reductions, CO2 mitigation, and reduction of primary energy consumption and 2) the developed EMS model achieved optimal operations. <s> BIB013 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> Abstract Optimal operation of hybrid energy systems is a big challenge in power systems. Nowadays, in addition to the optimum performance of energy systems, their pollution issue has been a hot topic between researchers. In this paper, a multi-objective model is proposed for economic and environmental operation of a battery/fuel cell/photovoltaic (PV) hybrid energy system in the presence of demand response program (DRP). In the proposed paper, the first objective function is minimization of total cost of hybrid energy system. The second objective function is minimization of total CO 2 emission which is in conflict with the first objective function. So, a multi-objective optimization model is presented to model the hybrid system’s optimal and environmental performance problem with considering DRP. The proposed multi-objective model is solved by e-constraint method and then fuzzy satisfying technique is employed to select the best possible solution. Also, positive effects of DRP on the economic and environmental performance of hybrid system are analyzed. A mixed-integer linear program is used to simulate the proposed model and the obtained results are compared with weighted sum approach to show the effectiveness of proposed method. <s> BIB014 </s> Energy management for user’s thermal and power needs: A survey <s> Generation <s> In this paper, an optimal probabilistic scheduling model of energy hubs operations is presented. The scheduling of energy hub determines the energy carriers to be purchased as input and converted or stored, in order to meet the energy requests, while minimizing the total hub's cost. However, as many other engineering endeavors, future operating criteria of energy hubs could not be forecasted with certainty. Load and price uncertainties are the most unclear parameters that hub operators deal with. In this regard, this paper proposes a 2 $m$ + 1 point estimation probabilistic scheduling scheme for energy hubs with multiple energy inputs and outputs. One of the applicable tools of energy hubs to have an efficient participation in the liberalized power market with volatile prices is demand response programs (DRPs). While there is plenty of experience in investigating the effect of DRP, it is electricity DRP that receives increasing attention by research and industry. Therefore, the proposed DRP investigates the effect of both responsive thermal and electric loads in reducing the total cost and participation of different facilities in supplying multiple loads. The proposed model envisages the most technical constraints of converters and storages. Several test systems have been investigated in order to confirm the effectiveness of the proposed model. The results verify the capability of the proposed model in covering the energy hub time-varying output demands as well as the economic advantages of implementing the suggested strategy. In addition, the results are compared with 2 $m$ point estimate method and Monte Carlo simulation. <s> BIB015
Generation resources produce electricity and/or heat from primary energy sources (e.g., fossil fuels, solar or wind energy). They are dispatchable, if their output can be controlled and adjusted, or non-dispatchable, if their output is not adjustable BIB006 . The most common ones are included in Fig. 3 within hexagons. Dispatchable generating DERs include all controllable generation systems that can be turned on or off and whose output can be adjusted on demand, such as gas turbines (GTs), micro turbines (MTs), fuel cells (FCs), internal combustion engine (ICE), hydro, CHP systems, boilers, Stirling engine, etc. BIB012 FCs produce electricity and heat, by burning natural gas (e.g.,  BIB014 BIB013 BIB007 or hydrogen (e.g., BIB015 BIB008 . CHPs are complex systems that generate electricity by burning fuel and, by recovering the waste heat, supply heat for space or water heating. If properly expanded with cooling units, such as absorption chillers and electric chillers BIB003 , CHPs can satisfy also cooling demand (CCHPs). In particular, the main generation units of these systems are the prime movers, such as ICEs BIB009 BIB004 , FCs BIB013 BIB001 BIB010  BIB007  BIB005 , and MTs BIB001 BIB011 , and the auxiliary boiler or furnace. They both burn fuel to generate electricity and heat, respectively. Biomass units are included among the dispatchable generating DERs as well BIB002 . The most common non-dispatchable DERs are PV units and WTs. As their output is intermittent and it is difficult to predict, several techniques are commonly employed to model the stochastic behavior of non-dispatchable DERs, as we discuss in Section 4.6.