Optimal air-conditioning load control in distribution network with intermittent renewables

Wang, Dongxiao; Meng, Ke; Gao, Xiaodan; Coates, Colin; Dong, Zhaoyang

doi:10.1007/s40565-016-0254-z

Cited by 29 publications

(19 citation statements)

References 28 publications

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“…Equation (18) denotes that the outputs of GPGs are constrained by the availability of gas in gas networks. Equation (19) states DR is bounded by the maximum DR ratio f.…”

Section: ) Power Balance Constraintmentioning

confidence: 99%

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Coordinated expansion co-planning of integrated gas and power systems

Wang

Qiu

Meng

et al. 2017

J. Mod. Power Syst. Clean Energy

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As a significant clean energy source, natural gas plays an important role in modern energy context. The growing utilization of natural gas brings uncertainties into the power system, which requires an integrated way to plan natural gas and power systems. In this paper, the co-planning process is formulated as a mixed integer nonlinear programming problem to address emerging challenges, such as system reliability evaluation, market time line mismatch, market uncertainties, demand response effect, etc. An innovative expansion co-planning (ECP) framework is established in this paper to find the best augmentation plan which comes with the minimum cost. Specifically, to cope with uncertainties in market share, decision analysis is introduced. Meanwhile, the energy conversion efficiency between gas and electricity in the coupled load center is considered in the ECP constraints. Comprehensive case studies are applied to validate the performance of proposed approach.

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“…Equation (18) denotes that the outputs of GPGs are constrained by the availability of gas in gas networks. Equation (19) states DR is bounded by the maximum DR ratio f.…”

Section: ) Power Balance Constraintmentioning

confidence: 99%

“…With the application of smart grids, demand response (DR) programs have attracted significant attentions in terms of enhancing system efficiency [19,20]. According to [21], DR programs are categorized into incentive-based DR (IBDR) (e.g.…”

Section: Introductionmentioning

confidence: 99%

Coordinated expansion co-planning of integrated gas and power systems

Wang

Qiu

Meng

et al. 2017

J. Mod. Power Syst. Clean Energy

Self Cite

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“…The overall load shedding was conducted for five consecutive days, started from 10:00 to 17:00 each day. The sampling interval of computer server to retrieve the controllable load of every customer and to conduct load curtailment through gateway are both set as T s = 15 min, as recommended by most previous studies, such as those in [11,12,19,20,22,26]. The averaging interval T m in (3) and the waiting interval T w in (4) for the gateway to calculate the average controllable load before and after every sampling time are both set as three minutes.…”

Section: Computer Simulationmentioning

confidence: 99%

“…Different customers are assigned with different shedding times as well as load shedding ratios due to different capacity and time constrains assigned. In order to show the effectiveness of the filtering scheme defined in (20), a metric used to consider the standard deviation ofs accumulated shedding contribution ratios at every k-th scheduling step is formulated as:…”

Section: Computer Simulationmentioning

confidence: 99%

A Soft Curtailment of Wide-Area Central Air Conditioning Load

Yao

Lim

2018

Energies

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An innovative solution to provide a demand response for power system is proposed in this paper by considering the feasibility of two-way direct load control (TWDLC) of central air conditioning chiller system for wide-area in real-time manner. Particularly, the proposed TWDLC scheme is designed to tackle the load shedding ratio optimization problem for all under-controlled customers, aiming to satisfy the target load curtailment defined in each scheduling step. Another notable contribution of this work is the utilization of constraint loosening concept on actual load, curtailed to overcome the uncertainties of load reduction during TWDLC. Given the presence of fuzzy constraints, the proposed load shedding ratio optimization problem can be tackled using fuzzy linear programming. A delicate strategy is then formulated to transform the proposed fuzzy linear programming problem into a regular linear programming problem. A selection scheme used to obtain the feasible candidates set for load shedding at every sampling interval of TWDLC is also designed along with the fuzzy linear programming.

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“…A more generalized approach for mixed-integer predictive control of HVAC systems using (mixed integer linear programming) MILP is presented in [32]. To improve the wind power utilization level in the distribution network and minimize the total system operation costs, Wang et al in [33] propose a MILP based approach to schedule the interruptible air-conditioning loads. In [18], Afram et al implement and validate a model predictive control (MPC) based supervisory controller which is designed to shift the heating and cooling load of a house in Toronto to off-peak hours.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control Home Energy Management and Optimization Strategy with Demand Response

et al. 2018

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Abstract:The growing demand for electricity is a challenge for the electricity sector as it not only involves the search for new sources of energy, but also the increase of generation capacity of the existing electrical infrastructure and the need to upgrade the existing grid. Therefore, new ways to reduce the consumption of energy are necessary to be implemented. When comparing an average house with an energy efficient house, it is possible to reduce annual energy bills up to 40%. Homeowners and tenants should consider developing an energy conservation plan in their homes. This is both an ecological and economically rational action. With this goal in mind, the need for the energy optimization arises. However, this has to be made by ensuring a fair level of comfort in the household, which in turn spawns a few control challenges. In this paper, the ON/OFF, proportional-integral-derivative (PID) and Model Predictive Control (MPC) control methods of an air conditioning (AC) of a room are compared. The model of the house of this study has a PV domestic generation. The recorded climacteric data for this case study are for Évora, a pilot Portuguese city in an ongoing demand response (DR) project. Six Time-of-Use (ToU) electricity rates are studied and compared during a whole week of summer, typically with very high temperatures for this period of the year. The overall weekly expense of each studied tariff option is compared for every control method and in the end the optimal solution is reached.

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Optimal air-conditioning load control in distribution network with intermittent renewables

Cited by 29 publications

References 28 publications

Coordinated expansion co-planning of integrated gas and power systems

Coordinated expansion co-planning of integrated gas and power systems

A Soft Curtailment of Wide-Area Central Air Conditioning Load

Model Predictive Control Home Energy Management and Optimization Strategy with Demand Response

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