Pagtumong sa Household Energy Efficiency Management Strategy Batas sa Distributed PV Plants ug ESS

1 Sistema nga Smart Home Batas sa ZigBee

Batasan ang patulobong pagkamadani sa teknolohiya sa kompyuter ug sa kontrol sa impormasyon, ang mga smart home mahimong molihok kaayo. Ang mga smart home dili lamang gipanatili ang tradisyonal nga mga pangutana sa balay apan usab gigikanan sa mga gumagamit og maong paagi sa pagbuhat sa mga butang sa balay. Kahit asa ra sila, mao kini ang magpadayon sa ilang pagmonitor sa status sa sulod sa balay, nagpabilin sa pagmaneho sa energy efficiency ug nagsugyot sa kalidad sa kinabuhi.

Ang paper na siya miyembroha usa ka sistema nga batas sa ZigBee nga adunay tulo ka bahin: home network, home server, ug mobile terminal. Ang sistema simple, efisiente, ug maluwag mapalapad, ang iyang struktura makita sa Figure 1.

1 Struktura sa Smart Home Batas sa ZigBee
1.1 Home Network

Isip ang core foundation, ang home network nagpakonekta sa mga controllable loads isip mga nodes alang sa internal data transmission ug multi-energy management. Ang pagpipili sa wireless (ZigBee) labi kay sa wired solutions nagdumala sa flexibility, reliability, ug scalability. Ang ZigBee, gibasehan sa IEEE 802.15.4, naghandog og low cost, power, ug complexity uban sa high security. Ang iyang affordable chips nakakurta sa system hardware costs. Ang network adunay:

• Coordinator: Nagmamaneho sa ZigBee network (CC2530-based, IAR-compiled), nakakubra sa tipikal nga mga balay pinaagi sa direct-connected topology.

• Terminal Nodes: Integrated sa metering/relays (isip smart sockets), nagkuha og data ug nagpatuman sa mga command para sa “control + monitoring” closure.

1.2 Home Server

Ang server nagserbiha isip ang “data-control core” sa sistema, nagproseso niini:

• Data Hub: Nagpapalit og impormasyon tali sa ZigBee (pinaagi sa serial port) ug mobile terminals (pinaagi sa Socket).

• Operation Monitoring: Nag-trace sa status sa load, nagmamaneho sa switches, ug nag-store sa electricity data.

• Energy Efficiency Brain: Nag-analyze sa load/photovoltaic data aron mapahimulos ang scheduling, nagpapahimulos sa energy management loop.

1.3 Mobile Terminal

Android-based (Eclipse + Java), ang terminal nag-enable niining:

• Status Visibility: Real-time display sa server-pushed electricity info.

• Remote Control: Nagpadala og commands aron mapamaneho ang loads indirectly.

• Flexible Scheduling: Nag-set sa custom load timings (e.g., for time-of-use pricing).

2 Pagdisenyo sa Home Energy Efficiency Management
2.1 System Architecture & Logic

Integrating “smart home + PV + energy storage”, ang sistema nag-embed og efficiency strategies sa server, formando ang “collect → model → optimize” loop:

• Data Layer: Nag-combine sa load ug PV data.

• Model Layer: Nag-balance sa PV use, storage, ug load pinaagi sa optimal schemes.

• Control Layer: Nag-coordinate sa PV/storage operations ug load scheduling para sa “cost-efficiency” goals (structure sa Figure 2).

2.2 Core Components & Collaboration

Key components (PV arrays, batteries, inverters, server, loads) nagtrabaho isip:

• PV Arrays: MPPT-enabled pinaagi sa inverters, nag-transmit sa real-time output sa server.

• Energy Storage: Grid-connected, nag-charging sa panahon sa PV surplus ug nag-discharging sa panahon sa shortages (metered para sa grid interaction).

• Server: Nag-link sa inverters/sockets, nag-adjust sa devices batas sa efficiency rules aron mapahimulos ang energy flow.

2.3 Load Classification & Scheduling

Loads gipartitionha sa tulo ka klase para sa time-of-use pricing-driven scheduling:

• Critical Loads (e.g., lighting): Fixed-time, non-adjustable.

• Adjustable Loads (e.g., AC): Variable-demand, power-tunable.

• Shiftable Loads (e.g., washers): Time-flexible, core for efficiency.

Ang server nag-maneho sa shiftable loads pinaagi sa smart sockets, shaving peaks/filling valleys aron mapakurta ang costs ug istabilizar ang grid.

3 Mathematical Model and Control Strategy for Home Energy Efficiency Management
3.1 Mathematical Model for Home Energy Efficiency Management

Arong makamit ang precise home energy efficiency management, kinahanglan i-establish ang mathematical model for total electricity cost. Ang paper na siya miyembroha usa ka “daily” control cycle, giparison ang 24 oras sa n equal time intervals. Sa pag-discretize sa continuous problems (kapag ang n kasagaran, ang bawg interval mogamit isip “micro-element,” ug ang variables mahimong ipresumpyon nga constant sa interval).Sa t-th interval, batas sa dynamic balance sa “home load power, photovoltaic generation power, battery charging/discharging power, ug grid interaction power,” ang sistema power balance equation gipasabot isip:

Sa t-th time interval, ang power variables gidefine isip sumala:

• P_G^t: Grid interaction power (positive for power absorption, negative for power injection);

• P_A^t: Total household load power;

• P_b^t: Battery charging/discharging power (positive for discharge, negative for charging);

• P_PV^t: Photovoltaic (PV) output power (influenced by solar irradiance, temperature, humidity, etc., and predictable via PV power forecasting models).

Ang household PV system nagoperar batas sa “self-consumption + surplus power grid-feeding” model, diin ang surplus electricity generates grid-feeding revenue ug PV generation qualifies for subsidies. Considering time-of-use (TOU) pricing (higher peak rates, lower off-peak rates), ang total electricity cost gicalculate isip:Total Cost=Grid Purchase Cost−Grid-Feeding Revenue−PV Subsidies

Para sa daily cycle discretized sa n intervals, ang total cost model mahimong mapalapad pa sa summation sa interval-specific costs, precisely adapting to dynamic pricing scenarios.

Sa formula: C represents the total daily electricity cost of the household; f_PV is the unit price of the photovoltaic power generation subsidy; 24/n is the duration of one time interval.
The expression for f_t in Formula (2) is

Sa formula: f^t_Cis the electricity price for the user during the t-th time period, which is divided into peak-time electricity price and off-peak electricity price according to different time periods; f_R is the electricity price for surplus electricity fed into the grid. The values of f_C^t, f_R and f_PV at any moment of the day are all known.The total power P_A^t of the household load is equal to the sum of the power of all shiftable loads and other loads during the t-th time period.

Sa formula: P_L,i is the operating power of the i-th shiftable load; T_L,i is the start-up time of the i-th shiftable load; Δ t_i is the operating duration of the i-th shiftable load; [t_i^s, t_i^e] is the range of the start-up time of the i-th shiftable load. P_L,i, Δ t_i, t_i^s and t_i^e are all definite values.

The electric power P_else,j^t of other loads is known, while the electric power of shiftable loads changes according to different start-up times, and T_L,i is an undetermined value. When T_L,i is different, the total power P_A^t of the household load changes accordingly, thus changing the total household electricity cost C.

3.2 Control Strategy

The core goal of home energy efficiency management is maximizing economic benefits, specifically translated into constructing an objective function for "minimizing the total household electricity cost C".

Based on the shiftable load model and combined with the time-of-use pricing mechanism, adjusting the start-up time \(T_{\text{L},i}\) of shiftable loads can dynamically optimize the total household load power curve, reducing the total cost from the perspective of electricity consumption timing.

Coordinated Control Logic for PV and Energy Storage

For photovoltaic (PV) power generation and energy storage batteries, control strategies are formulated for different time periods:

• Peak Periods: Prioritize full consumption of PV power generation. If PV output > load power, surplus electricity is fed into the grid for revenue. If PV output < load power, the battery is prioritized for power supply (when the battery state of charge > minimum value). When the battery is depleted, the insufficient part is supplemented by the grid.

• Off-Peak Periods: The battery is charged at the maximum charging power for energy storage. All load electricity is supplied by the grid, utilizing low-price off-peak electricity to "fill the valley" and store energy for peak periods.

Battery Constraints

It is necessary to simultaneously consider the charging/discharging power limits and capacity restrictions of the battery to constrain its charging and discharging behaviors (specific constraints need to be supplemented with formulas/models, not fully presented in the original text), ensuring equipment safety and system stability.

In Formula (6): P_b,max is the maximum charging/discharging power of the battery; in Formula (7), SOC^t is the state of charge (SOC) of the battery during the t-th time period; SOC_min is the minimum value of the battery's SOC; SOC_max is the maximum value of the battery's SOC.

According to the control strategy, optimize and control the charging/discharging power of the energy storage battery. During the peak period t ∈[t₁, t₂, where t₁ is the start time of the electricity peak period and t₂ is the end time of the electricity peak period, the discharge power of the battery is set as

During the off-peak period t ∈ [1, t₁], the discharge power of the storage battery is set as

It is necessary to calculate the state of charge (SOC) of the storage battery. The relationship between the state of charge during the charging and discharging process of the storage battery and the charging/discharging power is as follows:

Formula (10) describes the relationship between the storage battery's SOC and charging power during charging (here P_b^t < 0; Formula (11) describes that during discharging (here P_b^t > 0. SOC^{t + 1} is the SOC in the t + 1th period; &sigma; (self-discharge rate, nearly 0% for small time intervals), &eta;_ch (charging efficiency), &eta;_dis (discharging efficiency), and E_b,max (max capacity) are battery parameters.In summary, home energy efficiency optimization aims to minimize total electricity cost by determining shiftable loads' start times and energy storage charging/discharging power at each moment, stated as:

Objective function

Constraint conditions

4 Case Analysis

To verify the effectiveness of the proposed home energy efficiency management method, simulations and analyses are conducted using the household electrical equipment of a typical household in Shanghai. The home energy efficiency management system consists of photovoltaic panels, batteries, an inverter, a home server, and household loads. The system configuration parameters are shown in Table 1.

Shanghai implements time-of-use electricity pricing for residential living electricity, with peak hours from 6:00 to 22:00 at 0.617 CNY/kWh, and off-peak hours from 22:00 to 6:00 the next day at 0.307 CNY/kWh. The feed-in tariff for surplus PV electricity is