Records with Subject: Planning & Scheduling
Showing records 1 to 25 of 100. [First] Page: 1 2 3 4 Last
Research on a Micro-Grid Frequency Modulation Strategy Based on Optimal Utilization of Air Conditioners
Qingzhu Wan, Yuan Bian, Yalan Chen
February 27, 2019 (v1)
Keywords: energy storage system, frequency control, micro-grid, thermostatically controlled loads
With the proportion of air conditioners increasing gradually, they can provide a certain amount of frequency-controlled reserves for a micro-grid. Optimizing utilization of air conditioners and considering load response characteristics and customer comfort, the frequency adjustment model is a quadratic function model between the trigger temperature of the air conditioner compressor, and frequency variation is provided, which can be used to regulate the trigger temperature of the air conditioner when the micro-grid frequency rises and falls. This frequency adjustment model combines a primary frequency modulation method and a secondary frequency modulation method of the energy storage system, in order to optimize the frequency of a micro-grid. The simulation results show that the frequency modulation strategy for air conditioners can effectively improve the frequency modulation ability of air conditioners and frequency modulation effects of a micro-grid in coordination with an energy sto... [more]
Evaluation of Conservation Voltage Reduction with Analytic Hierarchy Process: A Decision Support Framework in Grid Operations Planning
Kyungsung An, Hao Jan Liu, Hao Zhu, Zhao Yang Dong, Kyeon Hur
February 27, 2019 (v1)
Keywords: analytic hierarchy process (AHP), conservation voltage reduction (CVR), CVR factor, integer programming, power transfer distribution factor (PTDF), voltage sensitivity factor (VSF)
This paper presents a systematic framework to evaluate the performance of conservation voltage reduction (CVR) by determining suitable substations for CVR in operations planning. Existing CVR planning practice generally only focuses on the energy saving aspect without taking other underlying attributes into account, i.e., network topology and reduced voltage effects on other substations. To secure the desired operating reserve and avoid any adverse impacts, these attributes should be considered for implementing CVR more effectively. This research develops a practical decision-making framework based on the analytic hierarchy process (AHP) to quantify several of the aforementioned attributes. Candidate substations for CVR deployment are prioritized such that performances are compared in terms of power transfer distribution factor (PTDF), voltage sensitivity factor (VSF), and CVR factor. In addition, to meet a specified reserve requirement, an integer programming approach is adopted to se... [more]
Green Small Cell Operation of Ultra-Dense Networks Using Device Assistance
Gilsoo Lee, Hongseok Kim
February 27, 2019 (v1)
Keywords: belief propagation, cellular networks, Energy Efficiency, Optimization, small cell
As higher performance is demanded in 5G networks, energy consumption in wireless networks increases along with the advances of various technologies, so enhancing energy efficiency also becomes an important goal to implement 5G wireless networks. In this paper, we study the energy efficiency maximization problem focused on finding a suitable set of turned-on small cell access points (APs). Finding the suitable on/off states of APs is challenging since the APs can be deployed by users while centralized network planning is not always possible. Therefore, when APs in small cells are randomly deployed and thus redundant in many cases, a mechanism of dynamic AP turning-on/off is required. We propose a device-assisted framework that exploits feedback messages from the user equipment (UE). To solve the problem, we apply an optimization method using belief propagation (BP) on a factor graph. Then, we propose a family of online algorithms inspired by BP, called DANCE, that requires low computati... [more]
Profitability Variations of a Solar System with an Evacuated Tube Collector According to Schedules and Frequency of Hot Water Demand
Carlos J. Porras-Prieto, Susana Benedicto-Schönemann, Fernando R. Mazarrón, Rosa M. Benavente
February 27, 2019 (v1)
Keywords: active solar water-heating system, evacuated-tube collector, hot water, profitability, schedule of demand
The use of solar water heating systems with evacuated tube collectors has been experiencing a rapid growth in recent years. Times when there is demand for hot water, the days of use and the volumes demanded may determine the profitability of these systems, even within the same city. Therefore, this paper characterizes the behavior of a solar system with active circulation with the objective of determining the profitability variations according to the timing and schedule of demand. Through a simplified methodology based on regression equations, calculated for each hour of the day based on data from an experimental facility, the useful energy is estimated from the time and frequency of the demand for hot water at 60 °C. The analysis of the potential profitability of the system in more than 1000 scenarios analyzed shows huge differences depending on the number of days when the water is demanded, the time when demand occurs, the irradiation and the average price of energy. In cities with h... [more]
A Flexible Ramping Capacity Model for Generation Scheduling with High Levels of Wind Energy Penetration
Hungyu Kwon, Jong-Keun Park, Dam Kim, Jihyun Yi, Hyeongon Park
February 27, 2019 (v1)
Keywords: demand curve, flexible ramping capacity, renewable generation, uncertainty, variability
The penetration level of renewable generation has increased significantly in recent years, which has led to operational concerns associated with the system ramping capability. Here, we propose the flexible ramping capacity (FRC) model, which considers the practical ramping capability of generation resources as well as the uncertainty in net load. The FRC model also incorporates the demand curve of the ramping capacity, which represents the hourly economic value of the ramping capacity. The model is formulated mathematically using ramp constraints, which are incorporated into unit commitment (UC) and economic dispatch (ED) processes. Simulations are carried out using a 10-unit system to compare the FRC model with conventional methods. We show that the FRC method can improve reliability and reduce expected operating costs. The simulation results also show that, by using the FRC model, system reliability can be satisfied at high wind power generation levels while achieving economic effici... [more]
A Novel Approach for Microgrid Protection Based upon Combined ANFIS and Hilbert Space-Based Power Setting
Ali Hadi Abdulwahid, Shaorong Wang
February 27, 2019 (v1)
Keywords: adaptive network-based fuzzy inference system (ANFIS), Hilbert space-based power (HSBP), microgrid protection, total harmonic distortion (THD)
Nowadays, the use of distributed generation (DG) has increased because of benefits such as increased reliability, reduced losses, improvement in the line capacity, and less environmental pollution. The protection of microgrids, which consist of generation sources, is one of the most crucial concerns of basic distribution operators. One of the key issues in this field is the protection of microgrids against permanent and temporary failures by improving the safety and reliability of the network. The traditional method has a number of disadvantages. The reliability and stability of a power system in a microgrid depend to a great extent on the efficiency of the protection scheme. The application of Artificial Intelligence approaches was introduced recently in the protection of distribution networks. The fault detection method depends on differential relay based on Hilbert Space-Based Power (HSBP) theory to achieve fastest primary protection. It is backed up by a total harmonic distortion (... [more]
A Parallel Probabilistic Load Flow Method Considering Nodal Correlations
Jun Liu, Xudong Hao, Peifen Cheng, Wanliang Fang, Shuanbao Niu
February 27, 2019 (v1)
Keywords: Correlation Latin hypercube sampling Monte Carlo Simulation (CLMCS), correlation matrix, cumulants, distributed generation (DG), parallel computing, probabilistic load flow (PLF)
With the introduction of more and more random factors in power systems, probabilistic load flow (PLF) has become one of the most important tasks for power system planning and operation. Cumulants-based PLF is an effective algorithm to calculate PLF in an analytical way, however, the correlations among the nodal injections to the system level have rarely been studied. A novel parallel cumulants-based PLF method considering nodal correlations is proposed in this paper, which is able to deal with the correlations among all system nodes, and avoid the Jacobian matrix inversion in the traditional cumulants-based PLF as well. In addition, parallel computing is introduced to improve the efficiency of the numerical calculations. The accuracy of the proposed method is validated by numerical tests on the standard IEEE-14 system, comparing with the results from Correlation Latin hypercube sampling Monte Carlo Simulation (CLMCS) method. And the efficiency and parallel performance is proven by the... [more]
A Privacy-Preserving Distributed Optimal Scheduling for Interconnected Microgrids
Nian Liu, Cheng Wang, Minyang Cheng, Jie Wang
February 27, 2019 (v1)
Keywords: cybersecurity, distributed optimization, microgrid, optimal scheduling
With the development of microgrids (MGs), interconnected operation of multiple MGs is becoming a promising strategy for the smart grid. In this paper, a privacy-preserving distributed optimal scheduling method is proposed for the interconnected microgrids (IMG) with a battery energy storage system (BESS) and renewable energy resources (RESs). The optimal scheduling problem is modeled to minimize the coalitional operation cost of the IMG, including the fuel cost of conventional distributed generators and the life loss cost of BESSs. By using the framework of the alternating direction method of multipliers (ADMM), a distributed optimal scheduling model and an iteration solution algorithm for the IMG is introduced; only the expected exchanging power (EEP) of each MG is required during the iterations. Furthermore, a privacy-preserving strategy for the sharing of the EEP among MGs is designed to work with the mechanism of the distributed algorithm. According to the security analysis, the EE... [more]
Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation
Jin-Sun Yang, Jin-Young Choi, Geon-Ho An, Young-Jun Choi, Myoung-Hoe Kim, Dong-Jun Won
February 27, 2019 (v1)
Keywords: energy management, energy storage system (ESS), frequency regulation (FR), optimal scheduling, state-of-charge (SOC)
An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This... [more]
Increasing the Benefit from Cost-Minimizing Loads via Centralized Adjustments
Antti Alahäivälä, Matti Lehtonen
February 27, 2019 (v1)
Keywords: aggregator, demand response (DR), imbalance power, regulating power
Several demand response (DR) strategies rely on real-time pricing and selfish local optimization, which may not result in optimal electricity consumption patterns from the viewpoint of an energy supplier or a power system. Thus, this paper proposes a strategy enabling centralized adjustments to cost-minimize consumers’ load. By employing the strategy, an aggregator is able to alter electricity consumption in order to remove power imbalances and to participate in the balancing power market (BPM). In this paper, we focus on direct electric space heating (DESH) loads that aim to minimize their heating cost locally. The consumers and an aggregator agree about an indoor temperature band, within which the aggregator is allowed to alter the temperature, and thus the electricity consumption. Centrally, the aggregator procures its electricity demand from a day-ahead (DA) market by utilizing the allowed temperature band and employs the band later in real-time (RT) operation for the balancing of... [more]
Accelerated Model Predictive Control for Electric Vehicle Integrated Microgrid Energy Management: A Hybrid Robust and Stochastic Approach
Zhenya Ji, Xueliang Huang, Changfu Xu, Houtao Sun
February 5, 2019 (v1)
Keywords: Benders decomposition, electric vehicle, energy management system, microgrid, robust optimization, scenario-based model predictive control, Stochastic Optimization
A microgrid with an advanced energy management approach is a feasible solution for accommodating the development of distributed generators (DGs) and electric vehicles (EVs). At the primary stage of development, the total number of EVs in a microgrid is fairly small but increases promptly. Thus, it makes most prediction models for EV charging demand difficult to apply at present. To overcome the inadaptability, a novel robust approach is proposed to handle EV charging demand predictions along with demand-side management (DSM) on the condition of satisfying each EV user’s demand. Variables with stochastic forecast models join the objective function in the form of probability-constrained scenarios. This paper proposes a scenario-based model predictive control (MPC) approach combining both robust and stochastic models to minimize the total operational cost for energy management. To overcome the concern about the convergence time increasing from the combination of scenarios, the Benders dec... [more]
An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †
Shi You, Junjie Hu, Charalampos Ziras
February 5, 2019 (v1)
Keywords: aggregation-based, fleet, integration, modeling approaches, plug-in electric vehicle
The design and implementation of management policies for plug-in electric vehicles (PEVs) need to be supported by a holistic understanding of the functional processes, their complex interactions, and their response to various changes. Models developed to represent different functional processes and systems are seen as useful tools to support the related studies for different stakeholders in a tangible way. This paper presents an overview of modeling approaches applied to support aggregation-based management and integration of PEVs from the perspective of fleet operators and grid operators, respectively. We start by explaining a structured modeling approach, i.e., a flexible combination of process models and system models, applied to different management and integration studies. A state-of-the-art overview of modeling approaches applied to represent several key processes, such as charging management, and key systems, such as the PEV fleet, is then presented, along with a detailed descri... [more]
Robust Unit Commitment Including Frequency Stability Constraints
Felipe Pérez-Illanes, Eduardo Álvarez-Miranda, Claudia Rahmann, Camilo Campos-Valdés
February 5, 2019 (v1)
Keywords: frequency regulation, inertial response, photovoltaic generation, unit commitment, wind power
An increased use of variable generation technologies such as wind power and photovoltaic generation can have important effects on system frequency performance during normal operation as well as contingencies. The main reasons are the operational principles and inherent characteristics of these power plants like operation at maximum power point and no inertial response during power system imbalances. This has led to new challenges for Transmission System Operators in terms of ensuring system security during contingencies. In this context, this paper proposes a Robust Unit Commitment including a set of additional frequency stability constraints. To do this, a simplified dynamic model of the initial system frequency response is used in combination with historical frequency nadir data during contingencies. The proposed approach is especially suitable for power systems with cost-based economic dispatch like those in most Latin American countries. The study is done considering the Northern I... [more]
The Demand Side Management Potential to Balance a Highly Renewable European Power System
Alexander Kies, Bruno U. Schyska, Lueder von Bremen
February 5, 2019 (v1)
Keywords: demand side management, energy system modelling, European power system, renewable energy systems, solar energy, wind energy
Shares of renewables continue to grow in the European power system. A fully renewable European power system will primarily depend on the renewable power sources of wind and photovoltaics (PV), which are not dispatchable but intermittent and therefore pose a challenge to the balancing of the power system. To overcome this issue, several solutions have been proposed and investigated in the past, including storage, backup power, reinforcement of the transmission grid, and demand side management (DSM). In this paper, we investigate the potential of DSM to balance a simplified, fully renewable European power system. For this purpose, we use ten years of weather and historical load data, a power-flow model and the implementation of demand side management as a storage equivalent, to investigate the impact of DSM on the need for backup energy. We show that DSM has the potential to reduce the need for backup energy in Europe by up to one third and can cover the need for backup up to a renewable... [more]
SoC-Based Output Voltage Control for BESS with a Lithium-Ion Battery in a Stand-Alone DC Microgrid
Seung-Yeong Yu, Hyun-Jun Kim, Jae-Hyuk Kim, Byung-Moon Han
February 5, 2019 (v1)
Keywords: battery energy storage system (BESS), droop control, engine generator (EG), lithium-ion (Li-ion) battery, photovoltaic (PV) panel, stand-alone DC microgrid, state of charge (SoC)
This paper proposes a new DC output voltage control for a battery energy storage system (BESS) with a lithium-ion battery based on the state of charge (SoC). The proposed control scheme was verified through computer simulations for a typical stand-alone DC microgrid, which consists of a BESS, photovoltaic (PV) panel, engine generator (EG), and DC load. A scaled hardware prototype for a stand-alone DC microgrid was set up in the lab, in which the proposed control scheme was loaded in a DSP controller. The experimental results were compared with the simulation results for performance verification. The proposed control scheme provides relatively lower variation of the DC grid voltage than the conventional droop control.
Multi-Objective Distribution Network Expansion Incorporating Electric Vehicle Charging Stations
Yue Xiang, Wei Yang, Junyong Liu, Furong Li
January 31, 2019 (v1)
Keywords: charging station, distribution network expansion planning, multi-objectives, multi-stage search strategy, traffic flow
The paper develops a multi-objective planning framework for distribution network expansion with electric vehicle charging stations. Charging loads are modeled in the first place, and then integrated into the optimal distribution network expansion planning. The formulation is extended from the single objective of the economic cost minimization into three objectives with the additional maximization of the charging station utilization, and maximization of the reliability level. Compared with the existing models, it captures the interactive impacts between charging infrastructures planning and distribution network planning from the aspects of economy, utilization, and reliability. A multi-stage search strategy is designed to solve the multi-objective problem. The models and the strategy are demonstrated by the test case. The results show that the proposed planning framework can make a trade-off among the three objectives, and offer a perspective to effectively integrate the network constra... [more]
Design and Analysis of Generic Energy Management Strategy for Controlling Second-Life Battery Systems in Stationary Applications
Mohamed Abdel-Monem, Omar Hegazy, Noshin Omar, Khiem Trad, Sven De Breucker, Peter Van Den Bossche, Joeri Van Mierlo
January 31, 2019 (v1)
Keywords: battery management system (BMS), energy storage system (ESS), energy/power management strategy, lithium-ion (Li-ion) batteries, multi-port power converter, rule-based control strategy, second-life batteries, self-consumption of photo-voltaic profile, stationary applications
Recently, second-life battery systems have received a growing interest as one of the most promising alternatives for decreasing the overall cost of the battery storage systems in stationary applications. The high-cost of batteries represents a prominent barrier for their use in traction and stationary applications. To make second-life batteries economically viable for stationary applications, an effective power-electronics converter should be selected as well. This converter should be supported by an energy management strategy (EMS), which is needed for controlling the power flow among the second-life battery modules based on their available capacity and performance. This article presents the design, analysis and implementation of a generic energy management strategy (GEMS). The proposed GEMS aims to control and distribute the load demand between battery storage systems under different load conditions and disturbances. This manuscript provides the experimental verification of the propo... [more]
Two-Stage Multi-Objective Collaborative Scheduling for Wind Farm and Battery Switch Station
Zhe Jiang, Xueshan Han, Zhimin Li, Wenbo Li, Mengxia Wang, Mingqiang Wang
January 31, 2019 (v1)
Keywords: battery switch station, dependent chance programming, electric vehicle, power system, wind farm
In order to deal with the uncertainties of wind power, wind farm and electric vehicle (EV) battery switch station (BSS) were proposed to work together as an integrated system. In this paper, the collaborative scheduling problems of such a system were studied. Considering the features of the integrated system, three indices, which include battery swapping demand curtailment of BSS, wind curtailment of wind farm, and generation schedule tracking of the integrated system are proposed. In addition, a two-stage multi-objective collaborative scheduling model was designed. In the first stage, a day-ahead model was built based on the theory of dependent chance programming. With the aim of maximizing the realization probabilities of these three operating indices, random fluctuations of wind power and battery switch demand were taken into account simultaneously. In order to explore the capability of BSS as reserve, the readjustment process of the BSS within each hour was considered in this stage... [more]
Master⁻Slave Based Hierarchical Control for a Small Power DC-Distributed Microgrid System with a Storage Device
Seung-Woon Lee, Bo-Hyung Cho
January 31, 2019 (v1)
Keywords: bus quality, communication-less master–slave, DC microgrid with ESS, master–slave control with battery
In this paper, we analyze one of the main drawbacks of droop control-based DC microgrid systems, and propose a novel control method to overcome this problem. Typically, DC microgrid systems use droop control techniques to enable communication independency and expandability. However, as these advantages are based on bus quality and regulation abandonment, droop-based schemes have limitations in terms of high bus impedance and bus regulation. This paper proposes a novel master⁻slave based hierarchical control technique for a DC distribution system, in which a DC bus signaling method is used to overcome the communication dependency and the expandability limitations of conventional master⁻slave control methods. The concept and design considerations of the proposed control method are presented, and a 1 kW simulation under a Powersim (PSIM) environment and hardware prototype—built to verify the system—is described.
An Interoperable Approach for Energy Systems Simulation: Electricity Market Participation Ontologies
Gabriel Santos, Tiago Pinto, Isabel Praça, Zita Vale
January 31, 2019 (v1)
Keywords: electricity markets simulation, multi-agent systems interoperability, ontologies
Electricity markets are complex environments with very particular characteristics. Some of the main ones for this complexity are the need for an adequate integration of renewable energy sources and the electricity markets’ restructuring process. The growth of simulation tool usage is driven by the need to understand those mechanisms and how the involved players’ interactions affect the markets’ outcomes. Several modelling tools directed to the study of restructured wholesale electricity markets have emerged. Although, they share a common limitation: the lack of interoperability between the various systems to allow the exchange of information and knowledge, to test different market models and to allow players from different systems to interact in common market environments. This paper proposes the use of ontologies for semantic interoperability between multi-agent platforms in the scope of electricity markets simulation. The achieved results allow the identification of the added value g... [more]
Risk-Limiting Scheduling of Optimal Non-Renewable Power Generation for Systems with Uncertain Power Generation and Load Demand
Shin-Yeu Lin, Ai-Chih Lin
January 31, 2019 (v1)
Keywords: artificial neural network (ANN), demand response, optimal power flow (OPF), point estimation method, renewable power generation, risk-limiting scheduling, security constraints
This study tackles a risk-limiting scheduling problem of non-renewable power generation for large power systems, and addresses potential violations of the security constraints owing to the volatility of renewable power generation and the uncertainty of load demand. To cope with the computational challenge that arises from the probabilistic constraints in the considered problem, a computationally efficient solution algorithm that involves a bisection method, an off-line constructed artificial neural network (ANN) and an on-line point estimation method is proposed and tested on the IEEE 118-bus system. The results of tests and comparisons reveal that the proposed solution algorithm is applicable to large power systems in real time, and the solution obtained herein is much better than the conventional optimal power flow (OPF) solution in obtaining a much higher probability of satisfying the security constraints.
MMCS: Multi-Module Charging Strategy for Increasing the Lifetime of Wireless Rechargeable Sensor Networks
Hong-Yi Chang, Jia-Chi Lin, Yu-Fong Wu, Shih-Chang Huang
January 31, 2019 (v1)
Keywords: optimized charging path problem, wireless rechargeable sensor networks (WRSNs), wireless sensor networks (WSNs)
In recent years, wireless charging technology has provided an alternative to charging equipment. Wireless charging technology has already proved to be useful in our daily lives in phones, buses, restaurants, etc. Wireless charging technology can also be applied in energy-bounded wireless sensor networks (WSNs), and these are called wireless rechargeable sensor networks (WRSNs). The optimized charging path problem is the most widely discussed issue in employing WRSNs with wireless charging vehicles (WCVs). This problem involves determining the most efficient path for charging sensor nodes. Further, charging-scheduling problems also need to be considered in the optimized charging path problem. In this paper, we proposed a multi-module charging strategy (MMCS) used to prolong the lifetime of the entire WRSN. MMCS can be divided into three stages: the charging topology, charging scheduling, and charging strategy stages, with multiple modules in each stage. The best module combination of MM... [more]
Robust Peak-Shaving for a Neighborhood with Electric Vehicles
Marco E. T. Gerards, Johann L. Hurink
January 7, 2019 (v1)
Keywords: adaptive scheduling, demand side management, electric vehicles, optimal scheduling, smart grids
Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly used DSM methods either have no look ahead feature and risk deploying flexibility too early, or they plan ahead using predictions, which are in general not very reliable. To counter this, a DSM approach is presented that does not rely on detailed power predictions, but only uses a few easy to predict characteristics. By using these characteristics alone, near optimal results can be achieved for electric vehicle (EV) charging, and a bound on the maximal relative deviation is given. This result is extended to an algorithm that controls a group of EVs such that a transformer peak is avoided, while simultaneously keeping the individual house profiles as flat as possible to avoid cable overloading and for improved power quality. This approach is evaluated using different data sets to compare the results with the state-of-the-art research. The evaluation shows that the presented approach is capa... [more]
Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing
Muhammad Babar Rasheed, Nadeem Javaid, Ashfaq Ahmad, Mohsin Jamil, Zahoor Ali Khan, Umar Qasim, Nabil Alrajeh
January 7, 2019 (v1)
Keywords: binary knapsack, demand response, energy optimization, peak load avoidance, smart grid, time of use pricing
In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable) in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.
Optimal Cooling Load Sharing Strategies for Different Types of Absorption Chillers in Trigeneration Plants
Benedetto Conte, Joan Carles Bruno, Alberto Coronas
January 7, 2019 (v1)
Keywords: absorption chillers, optimal operation, partial load, trigeneration
Trigeneration plants can use different types of chillers in the same plant, typically single effect and double effect absorption chillers, vapour compression chillers and also cooling storage systems. The highly variable cooling demand of the buildings connected to a district heating and cooling (DHC) network has to be distributed among these chillers to achieve lower operating costs and higher energy efficiencies. This problem is difficult to solve due to the different partial load behaviour of each chiller and the different chiller combinations that can cover a certain cooling demand using an appropriate sizing of the cooling storage. The objective of this paper is to optimize the daily plant operation of an existing trigeneration plant based on cogeneration engines and to study the optimal cooling load sharing between different types of absorption chillers using a mixed integer linear programming (MILP) model. Real data from a trigeneration plant connected to a DHC close to Barcelon... [more]
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